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Sample records for students correctly predicted

  1. Exploring viewing behavior data from whole slide images to predict correctness of students' answers during practical exams in oral pathology.

    Science.gov (United States)

    Walkowski, Slawomir; Lundin, Mikael; Szymas, Janusz; Lundin, Johan

    2015-01-01

    The way of viewing whole slide images (WSI) can be tracked and analyzed. In particular, it can be useful to learn how medical students view WSIs during exams and how their viewing behavior is correlated with correctness of the answers they give. We used software-based view path tracking method that enabled gathering data about viewing behavior of multiple simultaneous WSI users. This approach was implemented and applied during two practical exams in oral pathology in 2012 (88 students) and 2013 (91 students), which were based on questions with attached WSIs. Gathered data were visualized and analyzed in multiple ways. As a part of extended analysis, we tried to use machine learning approaches to predict correctness of students' answers based on how they viewed WSIs. We compared the results of analyses for years 2012 and 2013 - done for a single question, for student groups, and for a set of questions. The overall patterns were generally consistent across these 3 years. Moreover, viewing behavior data appeared to have certain potential for predicting answers' correctness and some outcomes of machine learning approaches were in the right direction. However, general prediction results were not satisfactory in terms of precision and recall. Our work confirmed that the view path tracking method is useful for discovering viewing behavior of students analyzing WSIs. It provided multiple useful insights in this area, and general results of our analyses were consistent across two exams. On the other hand, predicting answers' correctness appeared to be a difficult task - students' answers seem to be often unpredictable.

  2. Publisher Correction: Predicting unpredictability

    Science.gov (United States)

    Davis, Steven J.

    2018-06-01

    In this News & Views article originally published, the wrong graph was used for panel b of Fig. 1, and the numbers on the y axes of panels a and c were incorrect; the original and corrected Fig. 1 is shown below. This has now been corrected in all versions of the News & Views.

  3. Accurately Detecting Students' Lies regarding Relational Aggression by Correctional Instructions

    Science.gov (United States)

    Dickhauser, Oliver; Reinhard, Marc-Andre; Marksteiner, Tamara

    2012-01-01

    This study investigates the effect of correctional instructions when detecting lies about relational aggression. Based on models from the field of social psychology, we predict that correctional instruction will lead to a less pronounced lie bias and to more accurate lie detection. Seventy-five teachers received videotapes of students' true denial…

  4. Neural networks to predict exosphere temperature corrections

    Science.gov (United States)

    Choury, Anna; Bruinsma, Sean; Schaeffer, Philippe

    2013-10-01

    Precise orbit prediction requires a forecast of the atmospheric drag force with a high degree of accuracy. Artificial neural networks are universal approximators derived from artificial intelligence and are widely used for prediction. This paper presents a method of artificial neural networking for prediction of the thermosphere density by forecasting exospheric temperature, which will be used by the semiempirical thermosphere Drag Temperature Model (DTM) currently developed. Artificial neural network has shown to be an effective and robust forecasting model for temperature prediction. The proposed model can be used for any mission from which temperature can be deduced accurately, i.e., it does not require specific training. Although the primary goal of the study was to create a model for 1 day ahead forecast, the proposed architecture has been generalized to 2 and 3 days prediction as well. The impact of artificial neural network predictions has been quantified for the low-orbiting satellite Gravity Field and Steady-State Ocean Circulation Explorer in 2011, and an order of magnitude smaller orbit errors were found when compared with orbits propagated using the thermosphere model DTM2009.

  5. Innovation in prediction planning for anterior open bite correction.

    Science.gov (United States)

    Almuzian, Mohammed; Almukhtar, Anas; O'Neil, Michael; Benington, Philip; Al Anezi, Thamer; Ayoub, Ashraf

    2015-05-01

    This study applies recent advances in 3D virtual imaging for application in the prediction planning of dentofacial deformities. Stereo-photogrammetry has been used to create virtual and physical models, which are creatively combined in planning the surgical correction of anterior open bite. The application of these novel methods is demonstrated through the surgical correction of a case.

  6. Hypothesis, Prediction, and Conclusion: Using Nature of Science Terminology Correctly

    Science.gov (United States)

    Eastwell, Peter

    2012-01-01

    This paper defines the terms "hypothesis," "prediction," and "conclusion" and shows how to use the terms correctly in scientific investigations in both the school and science education research contexts. The scientific method, or hypothetico-deductive (HD) approach, is described and it is argued that an understanding of the scientific method,…

  7. Coaching, Not Correcting: An Alternative Model for Minority Students

    Science.gov (United States)

    Dresser, Rocío; Asato, Jolynn

    2014-01-01

    The debate on the role of oral corrective feedback or "repair" in English instruction settings has been going on for over 30 years. Some educators believe that oral grammar correction is effective because they have noticed that students who learned a set of grammar rules were more likely to use them in real life communication (Krashen,…

  8. Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures.

    Science.gov (United States)

    Keller, Joshua P; Chang, Howard H; Strickland, Matthew J; Szpiro, Adam A

    2017-05-01

    Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data. We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap. Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35). This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.

  9. Student Beliefs towards Written Corrective Feedback: The Case of Filipino High School Students

    Science.gov (United States)

    Balanga, Roselle A.; Fidel, Irish Van B.; Gumapac, Mone Virma Ginry P.; Ho, Howell T.; Tullo, Riza Mae C.; Villaraza, Patricia Monette L.; Vizconde, Camilla J.

    2016-01-01

    The study identified the beliefs of high school students toward Written Corrective Feedback (WCF), based on the framework of Anderson (2010). It also investigated the most common errors that students commit in writing stories and the type of WCF students receive from teachers. Data in the form of stories which were checked by teachers were…

  10. "When does making detailed predictions make predictions worse?": Correction to Kelly and Simmons (2016).

    Science.gov (United States)

    2016-10-01

    Reports an error in "When Does Making Detailed Predictions Make Predictions Worse" by Theresa F. Kelly and Joseph P. Simmons ( Journal of Experimental Psychology: General , Advanced Online Publication, Aug 8, 2016, np). In the article, the symbols in Figure 2 were inadvertently altered in production. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-37952-001.) In this article, we investigate whether making detailed predictions about an event worsens other predictions of the event. Across 19 experiments, 10,896 participants, and 407,045 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes useless or redundant information more accessible and thus more likely to be incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of events will and will not be susceptible to the negative effect of making detailed predictions. PsycINFO Database Record (c) 2016 APA, all rights reserved

  11. Validating strengths use and deficit correction behaviour scales for South African first-year students

    Directory of Open Access Journals (Sweden)

    Karina Mostert

    2017-01-01

    Research purpose: To examine the validity, measurement invariance and reliability of the proactive strengths use and deficit correction scales for South African first-year university students. Motivation for the study: In order to cope in the demanding university environment, first-year university students need to develop and apply proactive strategies, including using their strengths and developing in their areas of weaknesses. Several studies have indicated that proactive behaviour, specifically strengths use and deficit correction behaviour, lead to favourable outcomes such as higher engagement, lower burnout and more life satisfaction. Therefore, it is important to validate scales that measure these constructs for first-year students. Research design, approach and method: A cross-sectional research approach was used. A sample of South African first-year university students aged between 18 and 23 years (N = 776 was collected. The two scales were tested for their factor structure, measurement invariance, reliability, and convergent and criterion validity. Main findings: A two-factor structure was found for the strengths use and deficit correction behaviour scales. Measurement invariance testing showed that the two scales were interpreted similarly by participants from different campuses and language groups. Cronbach’s alpha coefficients (α ≥ 0.70 indicated that both scales were reliable. In addition, the scales demonstrated convergent validity (comparing them with a general strengths use and proactive behaviour scale. Strengths use and deficit correction behaviour both predicted student burnout, student engagement and life satisfaction, with varying strengths of the relationships for strengths use and deficit correction behaviour. Practical implications: Strengths use and deficit correction behaviour could enable students to manage study demands and enhance well-being. Students will experience favourable outcomes from proactively using strengths and

  12. Correction

    DEFF Research Database (Denmark)

    Pinkevych, Mykola; Cromer, Deborah; Tolstrup, Martin

    2016-01-01

    [This corrects the article DOI: 10.1371/journal.ppat.1005000.][This corrects the article DOI: 10.1371/journal.ppat.1005740.][This corrects the article DOI: 10.1371/journal.ppat.1005679.].......[This corrects the article DOI: 10.1371/journal.ppat.1005000.][This corrects the article DOI: 10.1371/journal.ppat.1005740.][This corrects the article DOI: 10.1371/journal.ppat.1005679.]....

  13. The Effects of Writing Anxiety and Motivation on EFL College Students' Self-Evaluative Judgments of Corrective Feedback.

    Science.gov (United States)

    Tsao, Jui-Jung; Tseng, Wen-Ta; Wang, Chaochang

    2017-04-01

    Feedback is regarded as a way to foster students' motivation and to ensure linguistic accuracy. However, mixed findings are reported in the research on written corrective feedback because of its multifaceted nature and its correlations with learners' individual differences. It is necessary, therefore, to conduct further research on corrective feedback from the student's perspective and to examine how individual differences in terms of factors such as writing anxiety and motivation predict learners' self-evaluative judgments of both teacher-corrected and peer-corrected feedback. For this study, 158 Taiwanese college sophomores participated in a survey that comprised three questionnaires. Results demonstrated that intrinsic motivation and different types of writing anxiety predicted English as foreign language learners' evaluative judgments of teacher and peer feedback. The findings have implications for English-writing instruction.

  14. Exploring viewing behavior data from whole slide images to predict correctness of students′ answers during practical exams in oral pathology

    Directory of Open Access Journals (Sweden)

    Slawomir Walkowski

    2015-01-01

    Full Text Available The way of viewing whole slide images (WSI can be tracked and analyzed. In particular, it can be useful to learn how medical students view WSIs during exams and how their viewing behavior is correlated with correctness of the answers they give. We used software-based view path tracking method that enabled gathering data about viewing behavior of multiple simultaneous WSI users. This approach was implemented and applied during two practical exams in oral pathology in 2012 (88 students and 2013 (91 students, which were based on questions with attached WSIs. Gathered data were visualized and analyzed in multiple ways. As a part of extended analysis, we tried to use machine learning approaches to predict correctness of students′ answers based on how they viewed WSIs. We compared the results of analyses for years 2012 and 2013 - done for a single question, for student groups, and for a set of questions. The overall patterns were generally consistent across these 3 years. Moreover, viewing behavior data appeared to have certain potential for predicting answers′ correctness and some outcomes of machine learning approaches were in the right direction. However, general prediction results were not satisfactory in terms of precision and recall. Our work confirmed that the view path tracking method is useful for discovering viewing behavior of students analyzing WSIs. It provided multiple useful insights in this area, and general results of our analyses were consistent across two exams. On the other hand, predicting answers′ correctness appeared to be a difficult task - students′ answers seem to be often unpredictable.

  15. Examining Factors Predicting Students' Digital Competence

    Science.gov (United States)

    Hatlevik, Ove Edvard; Guðmundsdóttir, Gréta Björk; Loi, Massimo

    2015-01-01

    The purpose of this study was to examine factors predicting lower secondary school students' digital competence and to explore differences between students when it comes to digital competence. Results from a digital competence test and survey in lower secondary school will be presented. It is important to learn more about and investigate what…

  16. Predicting Success Study Using Students GPA Category

    Directory of Open Access Journals (Sweden)

    Awan Setiawan

    2015-07-01

    Full Text Available Abstract. Maintaining student graduation rates are the main tasks of a University. High rates of student graduation and the quality of graduates is a success indicator of a university, which will have an impact on public confidence as stakeholders of higher education and the National Accreditation Board as a regulator (government. Making predictions of student graduation and determine the factors that hinders will be a valuable input for University. Data mining system facilitates the University to create the segmentation of students’ performance and prediction of their graduation. Segmentation of student by their performance can be classified in a quadrant chart is divided into 4 segments based on grade point average and the growth rate of students performance index per semester. Standard methodology in data mining i.e CRISP-DM (Cross Industry Standard Procedure for Data Mining will be implemented in this research. Making predictions, graduation can be done through the modeling process by utilizing the college database. Some algorithms such as C5, C & R Tree, CHAID, and Logistic Regression tested in order to find the best model. This research utilizes student performance data for several classes. Parameters used in addition to GPA also included the master's students data are expected to build the student profile data. The outcome of the study is the student category based on their study performance and prediction of graduation. Based on this prediction, the  university may recommend actions to be taken to improve the student  achievement index and graduation rates.Keywords: graduation, segmentation, quadrant GPA, data mining, modeling algorithms

  17. Predicting Success Study Using Students GPA Category

    Directory of Open Access Journals (Sweden)

    Awan Setiawan

    2015-06-01

    Full Text Available Abstract. Maintaining student graduation rates are the main tasks of a University. High rates of student graduation and the quality of graduates is a success indicator of a university, which will have an impact on public confidence as stakeholders of higher education and the National Accreditation Board as a regulator (government. Making predictions of student graduation and determine the factors that hinders will be a valuable input for University. Data mining system facilitates the University to create the segmentation of students’ performance and prediction of their graduation. Segmentation of student by their performance can be classified in a quadrant chart is divided into 4 segments based on grade point average and the growth rate of students performance index per semester. Standard methodology in data mining i.e CRISP-DM (Cross Industry Standard Procedure for Data Mining will be implemented in this research. Making predictions, graduation can be done through the modeling process by utilizing the college database. Some algorithms such as C5, C & R Tree, CHAID, and Logistic Regression tested in order to find the best model. This research utilizes student performance data for several classes. Parameters used in addition to GPA also included the master's students data are expected to build the student profile data. The outcome of the study is the student category based on their study performance and prediction of graduation. Based on this prediction, the university may recommend actions to be taken to improve the student achievement index and graduation rates. Keywords: graduation, segmentation, quadrant GPA, data mining, modeling algorithms

  18. Assessing the implementation of bias correction in the climate prediction

    Science.gov (United States)

    Nadrah Aqilah Tukimat, Nurul

    2018-04-01

    An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.

  19. Using Machine Learning to Predict Student Performance

    OpenAIRE

    Pojon, Murat

    2017-01-01

    This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

  20. EFL Students' Preferences toward the Lecturer's Corrective Feedback in Business Letters Writing

    Science.gov (United States)

    Sanu, La Ode

    2016-01-01

    This study aimed to investigate the students' preferences toward the lecturer's corrective feedback in the business letter writing and their reasons why they preferred particular corrective feedback types. A case study was used by involving 15 EFL students who enrolled in the Business Correspondence Course. The questionnaire and interview were…

  1. Students' Preferences and Attitude toward Oral Error Correction Techniques at Yanbu University College, Saudi Arabia

    Science.gov (United States)

    Alamri, Bushra; Fawzi, Hala Hassan

    2016-01-01

    Error correction has been one of the core areas in the field of English language teaching. It is "seen as a form of feedback given to learners on their language use" (Amara, 2015). Many studies investigated the use of different techniques to correct students' oral errors. However, only a few focused on students' preferences and attitude…

  2. A two-dimensional matrix correction for off-axis portal dose prediction errors

    International Nuclear Information System (INIS)

    Bailey, Daniel W.; Kumaraswamy, Lalith; Bakhtiari, Mohammad; Podgorsak, Matthew B.

    2013-01-01

    Purpose: This study presents a follow-up to a modified calibration procedure for portal dosimetry published by Bailey et al. [“An effective correction algorithm for off-axis portal dosimetry errors,” Med. Phys. 36, 4089–4094 (2009)]. A commercial portal dose prediction system exhibits disagreement of up to 15% (calibrated units) between measured and predicted images as off-axis distance increases. The previous modified calibration procedure accounts for these off-axis effects in most regions of the detecting surface, but is limited by the simplistic assumption of radial symmetry. Methods: We find that a two-dimensional (2D) matrix correction, applied to each calibrated image, accounts for off-axis prediction errors in all regions of the detecting surface, including those still problematic after the radial correction is performed. The correction matrix is calculated by quantitative comparison of predicted and measured images that span the entire detecting surface. The correction matrix was verified for dose-linearity, and its effectiveness was verified on a number of test fields. The 2D correction was employed to retrospectively examine 22 off-axis, asymmetric electronic-compensation breast fields, five intensity-modulated brain fields (moderate-high modulation) manipulated for far off-axis delivery, and 29 intensity-modulated clinical fields of varying complexity in the central portion of the detecting surface. Results: Employing the matrix correction to the off-axis test fields and clinical fields, predicted vs measured portal dose agreement improves by up to 15%, producing up to 10% better agreement than the radial correction in some areas of the detecting surface. Gamma evaluation analyses (3 mm, 3% global, 10% dose threshold) of predicted vs measured portal dose images demonstrate pass rate improvement of up to 75% with the matrix correction, producing pass rates that are up to 30% higher than those resulting from the radial correction technique alone. As

  3. Predicting Students Drop Out: A Case Study

    Science.gov (United States)

    Dekker, Gerben W.; Pechenizkiy, Mykola; Vleeshouwers, Jan M.

    2009-01-01

    The monitoring and support of university freshmen is considered very important at many educational institutions. In this paper we describe the results of the educational data mining case study aimed at predicting the Electrical Engineering (EE) students drop out after the first semester of their studies or even before they enter the study program…

  4. Predicting students drop out : a case study

    NARCIS (Netherlands)

    Dekker, G.W.; Pechenizkiy, M.; Vleeshouwers, J.M.; Barnes, T.; Desmarais, M.; Romero, C.; Ventura, S.

    2009-01-01

    The monitoring and support of university freshmen is considered very important at many educational institutions. In this paper we describe the results of the educational data mining case study aimed at predicting the Electrical Engineering (EE) students drop out after the first semester of their

  5. Parent, Teacher, and Student Perspectives on How Corrective Lenses Improve Child Wellbeing and School Function.

    Science.gov (United States)

    Dudovitz, Rebecca N; Izadpanah, Nilufar; Chung, Paul J; Slusser, Wendelin

    2016-05-01

    Up to 20 % of school-age children have a vision problem identifiable by screening, over 80 % of which can be corrected with glasses. While vision problems are associated with poor school performance, few studies describe whether and how corrective lenses affect academic achievement and health. Further, there are virtually no studies exploring how children with correctable visual deficits, their parents, and teachers perceive the connection between vision care and school function. We conducted a qualitative evaluation of Vision to Learn (VTL), a school-based program providing free corrective lenses to low-income students in Los Angeles. Nine focus groups with students, parents, and teachers from three schools served by VTL explored the relationships between poor vision, receipt of corrective lenses, and school performance and health. Twenty parents, 25 teachers, and 21 students from three elementary schools participated. Participants described how uncorrected visual deficits reduced students' focus, perseverance, and class participation, affecting academic functioning and psychosocial stress; how receiving corrective lenses improved classroom attention, task persistence, and willingness to practice academic skills; and how serving students in school rather than in clinics increased both access to and use of corrective lenses. for Practice Corrective lenses may positively impact families, teachers, and students coping with visual deficits by improving school function and psychosocial wellbeing. Practices that increase ownership and use of glasses, such as serving students in school, may significantly improve both child health and academic performance.

  6. Correction

    CERN Multimedia

    2002-01-01

    Tile Calorimeter modules stored at CERN. The larger modules belong to the Barrel, whereas the smaller ones are for the two Extended Barrels. (The article was about the completion of the 64 modules for one of the latter.) The photo on the first page of the Bulletin n°26/2002, from 24 July 2002, illustrating the article «The ATLAS Tile Calorimeter gets into shape» was published with a wrong caption. We would like to apologise for this mistake and so publish it again with the correct caption.

  7. A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [Universite catholique de Louvain

    2017-07-25

    This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.

  8. Correction

    Directory of Open Access Journals (Sweden)

    2012-01-01

    Full Text Available Regarding Gorelik, G., & Shackelford, T.K. (2011. Human sexual conflict from molecules to culture. Evolutionary Psychology, 9, 564–587: The authors wish to correct an omission in citation to the existing literature. In the final paragraph on p. 570, we neglected to cite Burch and Gallup (2006 [Burch, R. L., & Gallup, G. G., Jr. (2006. The psychobiology of human semen. In S. M. Platek & T. K. Shackelford (Eds., Female infidelity and paternal uncertainty (pp. 141–172. New York: Cambridge University Press.]. Burch and Gallup (2006 reviewed the relevant literature on FSH and LH discussed in this paragraph, and should have been cited accordingly. In addition, Burch and Gallup (2006 should have been cited as the originators of the hypothesis regarding the role of FSH and LH in the semen of rapists. The authors apologize for this oversight.

  9. Correction

    CERN Multimedia

    2002-01-01

    The photo on the second page of the Bulletin n°48/2002, from 25 November 2002, illustrating the article «Spanish Visit to CERN» was published with a wrong caption. We would like to apologise for this mistake and so publish it again with the correct caption.   The Spanish delegation, accompanied by Spanish scientists at CERN, also visited the LHC superconducting magnet test hall (photo). From left to right: Felix Rodriguez Mateos of CERN LHC Division, Josep Piqué i Camps, Spanish Minister of Science and Technology, César Dopazo, Director-General of CIEMAT (Spanish Research Centre for Energy, Environment and Technology), Juan Antonio Rubio, ETT Division Leader at CERN, Manuel Aguilar-Benitez, Spanish Delegate to Council, Manuel Delfino, IT Division Leader at CERN, and Gonzalo León, Secretary-General of Scientific Policy to the Minister.

  10. Correction

    Directory of Open Access Journals (Sweden)

    2014-01-01

    Full Text Available Regarding Tagler, M. J., and Jeffers, H. M. (2013. Sex differences in attitudes toward partner infidelity. Evolutionary Psychology, 11, 821–832: The authors wish to correct values in the originally published manuscript. Specifically, incorrect 95% confidence intervals around the Cohen's d values were reported on page 826 of the manuscript where we reported the within-sex simple effects for the significant Participant Sex × Infidelity Type interaction (first paragraph, and for attitudes toward partner infidelity (second paragraph. Corrected values are presented in bold below. The authors would like to thank Dr. Bernard Beins at Ithaca College for bringing these errors to our attention. Men rated sexual infidelity significantly more distressing (M = 4.69, SD = 0.74 than they rated emotional infidelity (M = 4.32, SD = 0.92, F(1, 322 = 23.96, p < .001, d = 0.44, 95% CI [0.23, 0.65], but there was little difference between women's ratings of sexual (M = 4.80, SD = 0.48 and emotional infidelity (M = 4.76, SD = 0.57, F(1, 322 = 0.48, p = .29, d = 0.08, 95% CI [−0.10, 0.26]. As expected, men rated sexual infidelity (M = 1.44, SD = 0.70 more negatively than they rated emotional infidelity (M = 2.66, SD = 1.37, F(1, 322 = 120.00, p < .001, d = 1.12, 95% CI [0.85, 1.39]. Although women also rated sexual infidelity (M = 1.40, SD = 0.62 more negatively than they rated emotional infidelity (M = 2.09, SD = 1.10, this difference was not as large and thus in the evolutionary theory supportive direction, F(1, 322 = 72.03, p < .001, d = 0.77, 95% CI [0.60, 0.94].

  11. Haptic Data Processing for Teleoperation Systems: Prediction, Compression and Error Correction

    OpenAIRE

    Lee, Jae-young

    2013-01-01

    This thesis explores haptic data processing methods for teleoperation systems, including prediction, compression, and error correction. In the proposed haptic data prediction method, unreliable network conditions, such as time-varying delay and packet loss, are detected by a transport layer protocol. Given the information from the transport layer, a Bayesian approach is introduced to predict position and force data in haptic teleoperation systems. Stability of the proposed method within stoch...

  12. New Software to Help EFL Students Self-Correct Their Writing

    Science.gov (United States)

    Lawley, Jim

    2015-01-01

    This paper describes the development of web-based software at a university in Spain to help students of EFL self-correct their free-form writing. The software makes use of an eighty-million-word corpus of English known to be correct as a normative corpus for error correction purposes. It was discovered that bigrams (two-word combinations of words)…

  13. The Detection and Correction of Bias in Student Ratings of Instruction.

    Science.gov (United States)

    Haladyna, Thomas; Hess, Robert K.

    1994-01-01

    A Rasch model was used to detect and correct bias in Likert rating scales used to assess student perceptions of college teaching, using a database of ratings. Statistical corrections were significant, supporting the model's potential utility. Recommendations are made for a theoretical rationale and further research on the model. (Author/MSE)

  14. Correction Equations to Adjust Self-Reported Height and Weight for Obesity Estimates among College Students

    Science.gov (United States)

    Mozumdar, Arupendra; Liguori, Gary

    2011-01-01

    The purposes of this study were to generate correction equations for self-reported height and weight quartiles and to test the accuracy of the body mass index (BMI) classification based on corrected self-reported height and weight among 739 male and 434 female college students. The BMIqc (from height and weight quartile-specific, corrected…

  15. Relationship between Counseling Students' Childhood Memories and Current Negative Self-Evaluations When Receiving Corrective Feedback

    Science.gov (United States)

    Stroud, Daniel; Olguin, David; Marley, Scott

    2016-01-01

    This article entails a study focused on the relationship between counseling students' negative childhood memories of receiving corrective feedback and current negative self-evaluations when receiving similar feedback in counselor education programs. Participants (N = 186) completed the Corrective Feedback Instrument-Revised (CFI-R; Hulse-Killacky…

  16. Evaluation of multiple protein docking structures using correctly predicted pairwise subunits

    Directory of Open Access Journals (Sweden)

    Esquivel-Rodríguez Juan

    2012-03-01

    Full Text Available Abstract Background Many functionally important proteins in a cell form complexes with multiple chains. Therefore, computational prediction of multiple protein complexes is an important task in bioinformatics. In the development of multiple protein docking methods, it is important to establish a metric for evaluating prediction results in a reasonable and practical fashion. However, since there are only few works done in developing methods for multiple protein docking, there is no study that investigates how accurate structural models of multiple protein complexes should be to allow scientists to gain biological insights. Methods We generated a series of predicted models (decoys of various accuracies by our multiple protein docking pipeline, Multi-LZerD, for three multi-chain complexes with 3, 4, and 6 chains. We analyzed the decoys in terms of the number of correctly predicted pair conformations in the decoys. Results and conclusion We found that pairs of chains with the correct mutual orientation exist even in the decoys with a large overall root mean square deviation (RMSD to the native. Therefore, in addition to a global structure similarity measure, such as the global RMSD, the quality of models for multiple chain complexes can be better evaluated by using the local measurement, the number of chain pairs with correct mutual orientation. We termed the fraction of correctly predicted pairs (RMSD at the interface of less than 4.0Å as fpair and propose to use it for evaluation of the accuracy of multiple protein docking.

  17. A Combination of Terrain Prediction and Correction for Search and Rescue Robot Autonomous Navigation

    Directory of Open Access Journals (Sweden)

    Yan Guo

    2009-09-01

    Full Text Available This paper presents a novel two-step autonomous navigation method for search and rescue robot. The algorithm based on the vision is proposed for terrain identification to give a prediction of the safest path with the support vector regression machine (SVRM trained off-line with the texture feature and color features. And correction algorithm of the prediction based the vibration information is developed during the robot traveling, using the judgment function given in the paper. The region with fault prediction will be corrected with the real traversability value and be used to update the SVRM. The experiment demonstrates that this method could help the robot to find the optimal path and be protected from the trap brought from the error between prediction and the real environment.

  18. Robust recurrent neural network modeling for software fault detection and correction prediction

    International Nuclear Information System (INIS)

    Hu, Q.P.; Xie, M.; Ng, S.H.; Levitin, G.

    2007-01-01

    Software fault detection and correction processes are related although different, and they should be studied together. A practical approach is to apply software reliability growth models to model fault detection, and fault correction process is assumed to be a delayed process. On the other hand, the artificial neural networks model, as a data-driven approach, tries to model these two processes together with no assumptions. Specifically, feedforward backpropagation networks have shown their advantages over analytical models in fault number predictions. In this paper, the following approach is explored. First, recurrent neural networks are applied to model these two processes together. Within this framework, a systematic networks configuration approach is developed with genetic algorithm according to the prediction performance. In order to provide robust predictions, an extra factor characterizing the dispersion of prediction repetitions is incorporated into the performance function. Comparisons with feedforward neural networks and analytical models are developed with respect to a real data set

  19. [Correcting influence of music on the students' functional state].

    Science.gov (United States)

    Gevorkian, É S; Minasian, S M; Abraamian, É T; Adamian, Ts I

    2013-01-01

    The influence of listening to classical music on integral indices of the activity of the regulatory mechanisms of the heart rhythm in students after teaching load was tested with the method of variational pulsometry accordingly to R.M Baevsky procedure. Registration and analysis of ECG was realized on Pentium 4 in three experimental situations: before the start of lessons (norm), after lessons, after listening to the music. Two types of response of students 'functional state to the teaching load: sympathetic and parasympathetic have been established. After teaching load music therapy session was found to led to the shift of levels of all examined indices of heart rhythm toward the original data (norm), most expressed in students with a sympathetic response type.

  20. Student Views of Technology-Mediated Written Corrective Feedback

    DEFF Research Database (Denmark)

    Kjærgaard, Hanne Wacher

    2017-01-01

    and practices concerning the specific – and time-consuming – language-teacher activity of providing WCF and 2) potential changes in student attitudes when technology is used to mediate the feedback. At the core of the study is an eight-month intervention which was carried out with three teachers of English...

  1. Using individual differences to predict job performance: correcting for direct and indirect restriction of range.

    Science.gov (United States)

    Sjöberg, Sofia; Sjöberg, Anders; Näswall, Katharina; Sverke, Magnus

    2012-08-01

    The present study investigates the relationship between individual differences, indicated by personality (FFM) and general mental ability (GMA), and job performance applying two different methods of correction for range restriction. The results, derived by analyzing meta-analytic correlations, show that the more accurate method of correcting for indirect range restriction increased the operational validity of individual differences in predicting job performance and that this increase primarily was due to general mental ability being a stronger predictor than any of the personality traits. The estimates for single traits can be applied in practice to maximize prediction of job performance. Further, differences in the relative importance of general mental ability in relation to overall personality assessment methods was substantive and the estimates provided enables practitioners to perform a correct utility analysis of their overall selection procedure. © 2012 The Authors. Scandinavian Journal of Psychology © 2012 The Scandinavian Psychological Associations.

  2. Correction for Measurement Error from Genotyping-by-Sequencing in Genomic Variance and Genomic Prediction Models

    DEFF Research Database (Denmark)

    Ashraf, Bilal; Janss, Luc; Jensen, Just

    sample). The GBSeq data can be used directly in genomic models in the form of individual SNP allele-frequency estimates (e.g., reference reads/total reads per polymorphic site per individual), but is subject to measurement error due to the low sequencing depth per individual. Due to technical reasons....... In the current work we show how the correction for measurement error in GBSeq can also be applied in whole genome genomic variance and genomic prediction models. Bayesian whole-genome random regression models are proposed to allow implementation of large-scale SNP-based models with a per-SNP correction...... for measurement error. We show correct retrieval of genomic explained variance, and improved genomic prediction when accounting for the measurement error in GBSeq data...

  3. Saudi EFL Preparatory Year Students' Perception about Corrective Feedback in Oral Communication

    Science.gov (United States)

    Alhaysony, Maha

    2016-01-01

    This study sought to investigate the attitudes of Saudi EFL students towards corrective feedback (henceforth CF) on classroom oral errors. The subjects were 3200 (1223 male and 1977 female) students enrolled in an intensive English language programme in the preparatory year at the University of Ha'il. A questionnaire was the main instrument. This…

  4. Using Example Problems to Improve Student Learning in Algebra: Differentiating between Correct and Incorrect Examples

    Science.gov (United States)

    Booth, Julie L.; Lange, Karin E.; Koedinger, Kenneth R.; Newton, Kristie J.

    2013-01-01

    In a series of two "in vivo" experiments, we examine whether correct and incorrect examples with prompts for self-explanation can be effective for improving students' conceptual understanding and procedural skill in Algebra when combined with guided practice. In Experiment 1, students working with the Algebra I Cognitive Tutor were randomly…

  5. Heisenberg coupling constant predicted for molecular magnets with pairwise spin-contamination correction

    Energy Technology Data Exchange (ETDEWEB)

    Masunov, Artëm E., E-mail: amasunov@ucf.edu [NanoScience Technology Center, Department of Chemistry, and Department of Physics, University of Central Florida, Orlando, FL 32826 (United States); Photochemistry Center RAS, ul. Novatorov 7a, Moscow 119421 (Russian Federation); Gangopadhyay, Shruba [Department of Physics, University of California, Davis, CA 95616 (United States); IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120 (United States)

    2015-12-15

    New method to eliminate the spin-contamination in broken symmetry density functional theory (BS DFT) calculations is introduced. Unlike conventional spin-purification correction, this method is based on canonical Natural Orbitals (NO) for each high/low spin coupled electron pair. We derive an expression to extract the energy of the pure singlet state given in terms of energy of BS DFT solution, the occupation number of the bonding NO, and the energy of the higher spin state built on these bonding and antibonding NOs (not self-consistent Kohn–Sham orbitals of the high spin state). Compared to the other spin-contamination correction schemes, spin-correction is applied to each correlated electron pair individually. We investigate two binuclear Mn(IV) molecular magnets using this pairwise correction. While one of the molecules is described by magnetic orbitals strongly localized on the metal centers, and spin gap is accurately predicted by Noodleman and Yamaguchi schemes, for the other one the gap is predicted poorly by these schemes due to strong delocalization of the magnetic orbitals onto the ligands. We show our new correction to yield more accurate results in both cases. - Highlights: • Magnetic orbitails obtained for high and low spin states are not related. • Spin-purification correction becomes inaccurate for delocalized magnetic orbitals. • We use the natural orbitals of the broken symmetry state to build high spin state. • This new correction is made separately for each electron pair. • Our spin-purification correction is more accurate for delocalised magnetic orbitals.

  6. Are we assessing correctly our students? Spain versus Finland.

    OpenAIRE

    Camacho-Miñano, María del Mar; Del Campo, Cristina; Pascual-Ezama, David; Urquia-Grande, Elena; Rivero, Carlos; Akpinar, Murat

    2016-01-01

    [EN] The aim of this paper is twofold: first, to analyse the comparison of coursework and final examination between Finland and Spain to test if there are differences in assessment methodologies; second, to study whether there are different factors (such as gender, age, subject, students’ motivation, and preferences) that have an impact on the assessment of students from the two countries. The final grades obtained by 117 freshmen enrolled on the Statistics and/or Financial ...

  7. A Class of Prediction-Correction Methods for Time-Varying Convex Optimization

    Science.gov (United States)

    Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro

    2016-09-01

    This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.

  8. Color Fringe Correction by the Color Difference Prediction Using the Logistic Function.

    Science.gov (United States)

    Jang, Dong-Won; Park, Rae-Hong

    2017-05-01

    This paper proposes a new color fringe correction method that preserves the object color well by the color difference prediction using the logistic function. We observe two characteristics between normal edge (NE) and degraded edge (DE) due to color fringe: 1) the DE has relatively smaller R-G and B-G correlations than the NE and 2) the color difference in the NE can be fitted by the logistic function. The proposed method adjusts the color difference of the DE to the logistic function by maximizing the R-G and B-G correlations in the corrected color fringe image. The generalized logistic function with four parameters requires a high computational load to select the optimal parameters. In experiments, a one-parameter optimization can correct color fringe gracefully with a reduced computational load. Experimental results show that the proposed method restores well the original object color in the DE, whereas existing methods give monochromatic or distorted color.

  9. Dispersion corrected hartree-fock and density functional theory for organic crystal structure prediction.

    Science.gov (United States)

    Brandenburg, Jan Gerit; Grimme, Stefan

    2014-01-01

    We present and evaluate dispersion corrected Hartree-Fock (HF) and Density Functional Theory (DFT) based quantum chemical methods for organic crystal structure prediction. The necessity of correcting for missing long-range electron correlation, also known as van der Waals (vdW) interaction, is pointed out and some methodological issues such as inclusion of three-body dispersion terms are discussed. One of the most efficient and widely used methods is the semi-classical dispersion correction D3. Its applicability for the calculation of sublimation energies is investigated for the benchmark set X23 consisting of 23 small organic crystals. For PBE-D3 the mean absolute deviation (MAD) is below the estimated experimental uncertainty of 1.3 kcal/mol. For two larger π-systems, the equilibrium crystal geometry is investigated and very good agreement with experimental data is found. Since these calculations are carried out with huge plane-wave basis sets they are rather time consuming and routinely applicable only to systems with less than about 200 atoms in the unit cell. Aiming at crystal structure prediction, which involves screening of many structures, a pre-sorting with faster methods is mandatory. Small, atom-centered basis sets can speed up the computation significantly but they suffer greatly from basis set errors. We present the recently developed geometrical counterpoise correction gCP. It is a fast semi-empirical method which corrects for most of the inter- and intramolecular basis set superposition error. For HF calculations with nearly minimal basis sets, we additionally correct for short-range basis incompleteness. We combine all three terms in the HF-3c denoted scheme which performs very well for the X23 sublimation energies with an MAD of only 1.5 kcal/mol, which is close to the huge basis set DFT-D3 result.

  10. Looking for students' personal characteristics predicting study outcome.

    NARCIS (Netherlands)

    Dr. A. Bakx; Theo Bergen; Dr. Cyrille A.C. Van Bragt; Marcel Croon

    2011-01-01

    Abstract The central goal of this study is to clarify to what degree former education and students' personal characteristics (the 'Big Five personality characteristics', personal orientations on learning and students' study approach) may predict study outcome (required credits and study

  11. Advanced ESL Students' Prior EFL Education and Their Perceptions of Oral Corrective Feedback

    Science.gov (United States)

    Lee, Eun Jeong

    2016-01-01

    The author in this study examines how advanced-level adult English as a Second Language (ESL) students' previous English as a Foreign Language (EFL) classroom experiences influence their perceptions of their teachers' oral corrective feedback (CF). It uses in-depth qualitative data to characterize the participants' prior English learning, and to…

  12. Predictive modeling for corrective maintenance of imaging devices from machine logs.

    Science.gov (United States)

    Patil, Ravindra B; Patil, Meru A; Ravi, Vidya; Naik, Sarif

    2017-07-01

    In the cost sensitive healthcare industry, an unplanned downtime of diagnostic and therapy imaging devices can be a burden on the financials of both the hospitals as well as the original equipment manufacturers (OEMs). In the current era of connectivity, it is easier to get these devices connected to a standard monitoring station. Once the system is connected, OEMs can monitor the health of these devices remotely and take corrective actions by providing preventive maintenance thereby avoiding major unplanned downtime. In this article, we present an overall methodology of predicting failure of these devices well before customer experiences it. We use data-driven approach based on machine learning to predict failures in turn resulting in reduced machine downtime, improved customer satisfaction and cost savings for the OEMs. One of the use-case of predicting component failure of PHILIPS iXR system is explained in this article.

  13. An effective drift correction for dynamical downscaling of decadal global climate predictions

    Science.gov (United States)

    Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

    2018-04-01

    Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

  14. Characteristic of methods for prevention and correction of moral of alienation of students

    Directory of Open Access Journals (Sweden)

    Z. K. Malieva

    2014-01-01

    Full Text Available A moral alienation is a complex integrative phenomenon characterized by individual’s rejection of universal spiritual and moral values of society. The last opportunity to find a purposeful competent solution of the problem of individual’s moral alienation lies in the space of professional education.The subject of study of this article is to identify methods for prevention and correction of moral alienation of students that can be used by teachers both in the process of extracurricular activities, and in conducting classes in humanitarian disciplines.The purpose of the work is to study methods and techniques that enhance the effectiveness of the prevention and correction of moral alienation of students, identify their characteristics and application in the educational activities of teachers.The paper concretizes a definition of methods to prevent and correct the moral alienation of students who represent a system of interrelated actions of educator and students aimed at: redefining of negative values, rules and norms of behavior; overcoming the negative mental states, negative attitudes, interests and aptitudes of aducatees.The article distinguishes and characterizes the most effective methods for prevention and correction of moral alienation of students: the conviction, the method of "Socrates"; understanding; semiotic analysis; suggestion, method of "explosion." It also presents the rules and necessary conditions for the application of these methods in the educational process.It is ascertained that the choice of effective preventive and corrective methods and techniques is determined by the content of intrapersonal, psychological sources of moral alienation associated with the following: negative attitude due to previous experience; orientation to these or those negative values; inadequate self-esteem, having a negative impact on the development and functioning of the individual’s psyche and behavior; mental states.The conclusions of the

  15. The effect of assessment form to the ability of student to answer the problem correctly

    Directory of Open Access Journals (Sweden)

    Arifian Dimas

    2017-02-01

    Full Text Available Assessment is an important part of education. For educators, are collecting information about students learning and information about the learning process. For students, the assessment is the process of informing them about the progress of learning. Effective assessment process is responsive to the strengths, needs and clearly articulated student learning objectives. This research was aimed to know the effect of assessment form towards students ability in answering the problem correctly on kinematics and dynamics of motion. The method used in this research is descriptive qualitative. The data collecting method are assessment test and interview. Assessment test instrument are written test and animation form test. The question we use was taken "Force Concept Inventory" on kinematics and dynamics concepts. The sample are 36 student of 6th terms student of Physics Undergraduate Departement in Sebelas Maret University. The result shows that for kinematics concept, more students answer correctly for test presented in animation form but for dynamics concept conventional test is better.

  16. Next-Term Student Performance Prediction: A Recommender Systems Approach

    Science.gov (United States)

    Sweeney, Mack; Rangwala, Huzefa; Lester, Jaime; Johri, Aditya

    2016-01-01

    An enduring issue in higher education is student retention to successful graduation. National statistics indicate that most higher education institutions have four-year degree completion rates around 50%, or just half of their student populations. While there are prediction models which illuminate what factors assist with college student success,…

  17. Predicting Drop-Out from Social Behaviour of Students

    Science.gov (United States)

    Bayer, Jaroslav; Bydzovska, Hana; Geryk, Jan; Obsivac, Tomas; Popelinsky, Lubomir

    2012-01-01

    This paper focuses on predicting drop-outs and school failures when student data has been enriched with data derived from students social behaviour. These data describe social dependencies gathered from e-mail and discussion board conversations, among other sources. We describe an extraction of new features from both student data and behaviour…

  18. A Trillion-Dollar Question: What Predicts Student Loan Delinquencies?

    Science.gov (United States)

    Mezza, Alvaro; Sommer, Kamila

    2016-01-01

    The recent significant increase in student loan delinquencies has generated interest in understanding the key factors predicting the non-performance of these loans. However, despite the large size of the student loan market, existing analyses have been limited by lack of data. This paper studies predictors of student loan delinquencies using a…

  19. Do abundance distributions and species aggregation correctly predict macroecological biodiversity patterns in tropical forests?

    Science.gov (United States)

    Wiegand, Thorsten; Lehmann, Sebastian; Huth, Andreas; Fortin, Marie‐Josée

    2016-01-01

    Abstract Aim It has been recently suggested that different ‘unified theories of biodiversity and biogeography’ can be characterized by three common ‘minimal sufficient rules’: (1) species abundance distributions follow a hollow curve, (2) species show intraspecific aggregation, and (3) species are independently placed with respect to other species. Here, we translate these qualitative rules into a quantitative framework and assess if these minimal rules are indeed sufficient to predict multiple macroecological biodiversity patterns simultaneously. Location Tropical forest plots in Barro Colorado Island (BCI), Panama, and in Sinharaja, Sri Lanka. Methods We assess the predictive power of the three rules using dynamic and spatial simulation models in combination with census data from the two forest plots. We use two different versions of the model: (1) a neutral model and (2) an extended model that allowed for species differences in dispersal distances. In a first step we derive model parameterizations that correctly represent the three minimal rules (i.e. the model quantitatively matches the observed species abundance distribution and the distribution of intraspecific aggregation). In a second step we applied the parameterized models to predict four additional spatial biodiversity patterns. Results Species‐specific dispersal was needed to quantitatively fulfil the three minimal rules. The model with species‐specific dispersal correctly predicted the species–area relationship, but failed to predict the distance decay, the relationship between species abundances and aggregations, and the distribution of a spatial co‐occurrence index of all abundant species pairs. These results were consistent over the two forest plots. Main conclusions The three ‘minimal sufficient’ rules only provide an incomplete approximation of the stochastic spatial geometry of biodiversity in tropical forests. The assumption of independent interspecific placements is most

  20. Predicting the sparticle spectrum from GUTs via SUSY threshold corrections with SusyTC

    Energy Technology Data Exchange (ETDEWEB)

    Antusch, Stefan [Department of Physics, University of Basel,Klingelbergstr. 82, CH-4056 Basel (Switzerland); Max-Planck-Institut für Physik (Werner-Heisenberg-Institut),Föhringer Ring 6, D-80805 München (Germany); Sluka, Constantin [Department of Physics, University of Basel,Klingelbergstr. 82, CH-4056 Basel (Switzerland)

    2016-07-21

    Grand Unified Theories (GUTs) can feature predictions for the ratios of quark and lepton Yukawa couplings at high energy, which can be tested with the increasingly precise results for the fermion masses, given at low energies. To perform such tests, the renormalization group (RG) running has to be performed with sufficient accuracy. In supersymmetric (SUSY) theories, the one-loop threshold corrections (TC) are of particular importance and, since they affect the quark-lepton mass relations, link a given GUT flavour model to the sparticle spectrum. To accurately study such predictions, we extend and generalize various formulas in the literature which are needed for a precision analysis of SUSY flavour GUT models. We introduce the new software tool SusyTC, a major extension to the Mathematica package REAP http://dx.doi.org/10.1088/1126-6708/2005/03/024, where these formulas are implemented. SusyTC extends the functionality of REAP by a full inclusion of the (complex) MSSM SUSY sector and a careful calculation of the one-loop SUSY threshold corrections for the full down-type quark, up-type quark and charged lepton Yukawa coupling matrices in the electroweak-unbroken phase. Among other useful features, SusyTC calculates the one-loop corrected pole mass of the charged (or the CP-odd) Higgs boson as well as provides output in SLHA conventions, i.e. the necessary input for external software, e.g. for performing a two-loop Higgs mass calculation. We apply SusyTC to study the predictions for the parameters of the CMSSM (mSUGRA) SUSY scenario from the set of GUT scale Yukawa relations ((y{sub e})/(y{sub d}))=−(1/2), ((y{sub μ})/(y{sub s}))=6, and ((y{sub τ})/(y{sub b}))=−(3/2), which has been proposed recently in the context of SUSY GUT flavour models.

  1. STUDENT PREDICTION SYSTEM FOR PLACEMENT TRAINING USING FUZZY INFERENCE SYSTEM

    Directory of Open Access Journals (Sweden)

    Ravi Kumar Rathore

    2017-04-01

    Full Text Available Proposed student prediction system is most vital approach which may be used to differentiate the student data/information on the basis of the student performance. Managing placement and training records in any larger organization is quite difficult as the student number are high; in such condition differentiation and classification on different categories becomes tedious. Proposed fuzzy inference system will classify the student data with ease and will be helpful to many educational organizations. There are lots of classification algorithms and statistical base technique which may be taken as good assets for classify the student data set in the education field. In this paper, Fuzzy Inference system has been applied to predict student performance which will help to identify performance of the students and also provides an opportunity to improve to performance. For instance, here we will classify the student’s data set for placement and non-placement classes.

  2. Theoretical and methodological reasoning of correction technologies of the physical conditions of students of music speciality

    Directory of Open Access Journals (Sweden)

    Petro Marynchuk

    2017-08-01

    Full Text Available The article emphasizes the lack of development of the methodological basis for the physical education of students of Music Arts. Professionally dependent indicators of physical condition were taken into account. The article also outlines the main theoretical and methodological provisions that underlie the development of technology for correction of the physical condition of students of music arts. They are in particular actualization of life-giving motivation of students to increase the level of physical condition, regular physical exercises, the need for the development of professionally important physical qualities, ensuring the differentiation of physical activity, taking into account the level of physical state and physical conditions of students of Music Arts. The structure of the technology of correction of the physical condition of students of Music Arts is considered. The technology contains the purpose, tasks, principles, stages of implementation, the program with the use of physical culture, performance criteria. The main stages of the technology implementation – preparatory, main, final – are analyzed. The means of motor activity of innovative direction are described for use in the practice of higher educational institutions, which take into account the features of the student staff, their mode of educational activity.

  3. A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

    Science.gov (United States)

    Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

    2014-01-01

    A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

  4. Characterization, prediction, and correction of geometric distortion in 3 T MR images

    International Nuclear Information System (INIS)

    Baldwin, Lesley N.; Wachowicz, Keith; Thomas, Steven D.; Rivest, Ryan; Gino Fallone, B.

    2007-01-01

    The work presented herein describes our methods and results for predicting, measuring and correcting geometric distortions in a 3 T clinical magnetic resonance (MR) scanner for the purpose of image guidance in radiation treatment planning. Geometric inaccuracies due to both inhomogeneities in the background field and nonlinearities in the applied gradients were easily visualized on the MR images of a regularly structured three-dimensional (3D) grid phantom. From a computed tomography scan, the locations of just under 10 000 control points within the phantom were accurately determined in three dimensions using a MATLAB-based computer program. MR distortion was then determined by measuring the corresponding locations of the control points when the phantom was imaged using the MR scanner. Using a reversed gradient method, distortions due to gradient nonlinearities were separated from distortions due to inhomogeneities in the background B 0 field. Because the various sources of machine-related distortions can be individually characterized, distortions present in other imaging sequences (for which 3D distortion cannot accurately be measured using phantom methods) can be predicted negating the need for individual distortion calculation for a variety of other imaging sequences. Distortions were found to be primarily caused by gradient nonlinearities and maximum image distortions were reported to be less than those previously found by other researchers at 1.5 T. Finally, the image slices were corrected for distortion in order to provide geometrically accurate phantom images

  5. Factors predicting dropout in student nursing assistants

    DEFF Research Database (Denmark)

    Svensson, Annemarie Lyng; Strøyer, Jesper; Ebbehøj, Niels Erik

    2008-01-01

    BACKGROUND: The dropout rate among student nursing assistants (NAs) in Danish health and social care education is high at >20%. AIMS: To explore if recent low back pain (LBP) history is a predictor of dropout among NA students, taking into account conventional risk factors for LBP, general health...

  6. Predicting Student Attrition with Data Mining Methods

    Science.gov (United States)

    Delen, Dursun

    2012-01-01

    Affecting university rankings, school reputation, and financial well-being, student retention has become one of the most important measures of success for higher education institutions. From the institutional perspective, improving student retention starts with a thorough understanding of the causes behind the attrition. Such an understanding is…

  7. [Corrective effect of aromatherapy on indices of heart rate variability in students under exam stress conditions].

    Science.gov (United States)

    Abrahamyan, H T; Minasyan, S M

    2016-01-01

    There were investigated changes in indices of the activity of regulatory mechanisms of heart rhythm in student under exam stress conditions and the possibility of their correction with aid of aromatherapy. The examination stress was established to be accompanied by pronounced shifts of integral and spectral indices of heart rhythm in students, indicating to the activation of the sympathetic circuit of Autonomic Nervous System in conditions of examination stress. A positive, relaxation impact of the essential oil of orange on the investigated indices was also recorded. The latter is expressed by weakly pronounced changes or lack of them in data of integral and spectral heart rate indices in students from the experimental group, that indicates to the stabilizing effect of used ethereal oil on the psycho-physiological state of students in conditions of exam stress

  8. Comparison and Prediction of Preclinical Students' Performance in ...

    African Journals Online (AJOL)

    olayemitoyin

    The data support the hypothesis that students who performed well in one discipline were likely to .... predict success in the clinical curriculum (Baciewicz,. 1990). Similarly ... the International Association of Medical Science. Educators. 17-20.

  9. Impacts of Earth rotation parameters on GNSS ultra-rapid orbit prediction: Derivation and real-time correction

    Science.gov (United States)

    Wang, Qianxin; Hu, Chao; Xu, Tianhe; Chang, Guobin; Hernández Moraleda, Alberto

    2017-12-01

    Analysis centers (ACs) for global navigation satellite systems (GNSSs) cannot accurately obtain real-time Earth rotation parameters (ERPs). Thus, the prediction of ultra-rapid orbits in the international terrestrial reference system (ITRS) has to utilize the predicted ERPs issued by the International Earth Rotation and Reference Systems Service (IERS) or the International GNSS Service (IGS). In this study, the accuracy of ERPs predicted by IERS and IGS is analyzed. The error of the ERPs predicted for one day can reach 0.15 mas and 0.053 ms in polar motion and UT1-UTC direction, respectively. Then, the impact of ERP errors on ultra-rapid orbit prediction by GNSS is studied. The methods for orbit integration and frame transformation in orbit prediction with introduced ERP errors dominate the accuracy of the predicted orbit. Experimental results show that the transformation from the geocentric celestial references system (GCRS) to ITRS exerts the strongest effect on the accuracy of the predicted ultra-rapid orbit. To obtain the most accurate predicted ultra-rapid orbit, a corresponding real-time orbit correction method is developed. First, orbits without ERP-related errors are predicted on the basis of ITRS observed part of ultra-rapid orbit for use as reference. Then, the corresponding predicted orbit is transformed from GCRS to ITRS to adjust for the predicted ERPs. Finally, the corrected ERPs with error slopes are re-introduced to correct the predicted orbit in ITRS. To validate the proposed method, three experimental schemes are designed: function extrapolation, simulation experiments, and experiments with predicted ultra-rapid orbits and international GNSS Monitoring and Assessment System (iGMAS) products. Experimental results show that using the proposed correction method with IERS products considerably improved the accuracy of ultra-rapid orbit prediction (except the geosynchronous BeiDou orbits). The accuracy of orbit prediction is enhanced by at least 50

  10. Authentic Leadership and Emotional Intelligence: Predicting Student Success

    Science.gov (United States)

    Jasso, Sonia Lizette

    2016-01-01

    Student success has been predicted conservatively, using academic, demographic, and economic variables. Since many colleges are feeling the pressure to produce more graduates, student success is at the forefront of all universities. This study looks to find a relationship between traditional and non-traditional variables. The objective of the…

  11. Psychosocial Factors Predicting First-Year College Student Success

    Science.gov (United States)

    Krumrei-Mancuso, Elizabeth J.; Newton, Fred B.; Kim, Eunhee; Wilcox, Dan

    2013-01-01

    This study made use of a model of college success that involves students achieving academic goals and life satisfaction. Hierarchical regressions examined the role of six psychosocial factors for college success among 579 first-year college students. Academic self-efficacy and organization and attention to study were predictive of first semester…

  12. Prediction of Problematic Internet Use by Attachment in University Students

    Science.gov (United States)

    Kozan, Hatice Irem Ozteke; Kesici, Sahin; Buyukbayraktar, Cagla Girgin; Yalcin, S. Barbaros

    2017-01-01

    Aim of this research is to examine the predictive power of attachment style on problematic internet use among university students. Participants of study consist of 481 university students (230 girls). Results indicate that there is a negative correlation between secure attachment style and social benefit/social comfort and there is a positive…

  13. How Predictive Analytics and Choice Architecture Can Improve Student Success

    Science.gov (United States)

    Denley, Tristan

    2014-01-01

    This article explores the challenges that students face in navigating the curricular structure of post-secondary degree programs, and how predictive analytics and choice architecture can play a role. It examines Degree Compass, a course recommendation system that successfully pairs current students with the courses that best fit their talents and…

  14. STUDENT ACADEMIC PERFORMANCE PREDICTION USING SUPPORT VECTOR MACHINE

    OpenAIRE

    S.A. Oloruntoba1 ,J.L.Akinode2

    2017-01-01

    This paper investigates the relationship between students' preadmission academic profile and final academic performance. Data Sample of students in one of the Federal Polytechnic in south West part of Nigeria was used. The preadmission academic profile used for this study is the 'O' level grades(terminal high school results).The academic performance is defined using student's Grade Point Average(GPA). This research focused on using data mining technique to develop a model for predicting stude...

  15. Challenges of student selection: Predicting academic performance ...

    African Journals Online (AJOL)

    Finding accurate predictors of tertiary academic performance, specifically for disadvantaged students, is essential because of budget constraints and the need of the labour market to address employment equity. Increased retention, throughput and decreased dropout rates are vital. When making admission decisions, the

  16. Predicting academic success among deaf college students.

    Science.gov (United States)

    Convertino, Carol M; Marschark, Marc; Sapere, Patricia; Sarchet, Thomastine; Zupan, Megan

    2009-01-01

    For both practical and theoretical reasons, educators and educational researchers seek to determine predictors of academic success for students at different levels and from different populations. Studies involving hearing students at the postsecondary level have documented significant predictors of success relating to various demographic factors, school experience, and prior academic attainment. Studies involving deaf and hard-of-hearing students have focused primarily on younger students and variables such as degree of hearing loss, use of cochlear implants, educational placement, and communication factors-although these typically are considered only one or two at a time. The present investigation utilizes data from 10 previous experiments, all using the same paradigm, in an attempt to discern significant predictors of readiness for college (utilizing college entrance examination scores) and classroom learning at the college level (utilizing scores from tests in simulated classrooms). Academic preparation was a clear and consistent predictor in both domains, but the audiological and communication variables examined were not. Communication variables that were significant reflected benefits of language flexibility over skills in either spoken language or American Sign Language.

  17. How EFL students can use Google to correct their “untreatable” written errors

    Directory of Open Access Journals (Sweden)

    Luc Geiller

    2014-09-01

    Full Text Available This paper presents the findings of an experiment in which a group of 17 French post-secondary EFL learners used Google to self-correct several “untreatable” written errors. Whether or not error correction leads to improved writing has been much debated, some researchers dismissing it is as useless and others arguing that error feedback leads to more grammatical accuracy. In her response to Truscott (1996, Ferris (1999 explains that it would be unreasonable to abolish correction given the present state of knowledge, and that further research needed to focus on which types of errors were more amenable to which types of error correction. In her attempt to respond more effectively to her students’ errors, she made the distinction between “treatable” and “untreatable” ones: the former occur in “a patterned, rule-governed way” and include problems with verb tense or form, subject-verb agreement, run-ons, noun endings, articles, pronouns, while the latter include a variety of lexical errors, problems with word order and sentence structure, including missing and unnecessary words. Substantial research on the use of search engines as a tool for L2 learners has been carried out suggesting that the web plays an important role in fostering language awareness and learner autonomy (e.g. Shei 2008a, 2008b; Conroy 2010. According to Bathia and Richie (2009: 547, “the application of Google for language learning has just begun to be tapped.” Within the framework of this study it was assumed that the students, conversant with digital technologies and using Google and the web on a regular basis, could use various search options and the search results to self-correct their errors instead of relying on their teacher to provide direct feedback. After receiving some in-class training on how to formulate Google queries, the students were asked to use a customized Google search engine limiting searches to 28 information websites to correct up to

  18. Tax revenue and inflation rate predictions in Banda Aceh using Vector Error Correction Model (VECM)

    Science.gov (United States)

    Maulia, Eva; Miftahuddin; Sofyan, Hizir

    2018-05-01

    A country has some important parameters to achieve the welfare of the economy, such as tax revenues and inflation. One of the largest revenues of the state budget in Indonesia comes from the tax sector. Besides, the rate of inflation occurring in a country can be used as one measure, to measure economic problems that the country facing. Given the importance of tax revenue and inflation rate control in achieving economic prosperity, it is necessary to analyze the relationship and forecasting tax revenue and inflation rate. VECM (Vector Error Correction Model) was chosen as the method used in this research, because of the data used in the form of multivariate time series data. This study aims to produce a VECM model with optimal lag and to predict the tax revenue and inflation rate of the VECM model. The results show that the best model for data of tax revenue and the inflation rate in Banda Aceh City is VECM with 3rd optimal lag or VECM (3). Of the seven models formed, there is a significant model that is the acceptance model of income tax. The predicted results of tax revenue and the inflation rate in Kota Banda Aceh for the next 6, 12 and 24 periods (months) obtained using VECM (3) are considered valid, since they have a minimum error value compared to other models.

  19. Machine learning methods in predicting the student academic motivation

    Directory of Open Access Journals (Sweden)

    Ivana Đurđević Babić

    2017-01-01

    Full Text Available Academic motivation is closely related to academic performance. For educators, it is equally important to detect early students with a lack of academic motivation as it is to detect those with a high level of academic motivation. In endeavouring to develop a classification model for predicting student academic motivation based on their behaviour in learning management system (LMS courses, this paper intends to establish links between the predicted student academic motivation and their behaviour in the LMS course. Students from all years at the Faculty of Education in Osijek participated in this research. Three machine learning classifiers (neural networks, decision trees, and support vector machines were used. To establish whether a significant difference in the performance of models exists, a t-test of the difference in proportions was used. Although, all classifiers were successful, the neural network model was shown to be the most successful in detecting the student academic motivation based on their behaviour in LMS course.

  20. Does Correct Answer Distribution Influence Student Choices When Writing Multiple Choice Examinations?

    Directory of Open Access Journals (Sweden)

    Jacqueline A. Carnegie

    2017-03-01

    Full Text Available Summative evaluation for large classes of first- and second-year undergraduate courses often involves the use of multiple choice question (MCQ exams in order to provide timely feedback. Several versions of those exams are often prepared via computer-based question scrambling in an effort to deter cheating. An important parameter to consider when preparing multiple exam versions is that they must be equivalent in their assessment of student knowledge. This project investigated a possible influence of correct answer organization on student answer selection when writing multiple versions of MCQ exams. The specific question asked was whether the existence of a series of four to five consecutive MCQs in which the same letter represented the correct answer had a detrimental influence on a student’s ability to continue to select the correct answer as he/she moved through that series. Student outcomes from such exams were compared with results from exams with identical questions but which did not contain such series. These findings were supplemented by student survey data in which students self-assessed the extent to which they paid attention to the distribution of correct answer choices when writing summative exams, both during their initial answer selection and when transferring their answer letters to the Scantron sheet for correction. Despite the fact that more than half of survey respondents indicated that they do make note of answer patterning during exams and that a series of four to five questions with the same letter for the correct answer would encourage many of them to take a second look at their answer choice, the results pertaining to student outcomes suggest that MCQ randomization, even when it does result in short serial arrays of letter-specific correct answers, does not constitute a distraction capable of adversely influencing student performance. Dans les très grandes classes de cours de première et deuxième années, l

  1. Research and Teaching: Beyond Correctness--Using Qualitative Methods to Uncover Nuances of Student Learning in Undergraduate STEM Education

    Science.gov (United States)

    Dósa, Katalin; Russ, Rosemary

    2016-01-01

    Learning in higher education today is measured overwhelmingly on the basis of "correctness," that is, whether students sufficiently approached the preset "expert" answer to a test question. We posit that although conceptual correctness is at the core of good learning, there is much information instructors miss out on by relying…

  2. Factors predicting dropout in student nursing assistants.

    Science.gov (United States)

    Svensson, Annemarie Lyng; Strøyer, Jesper; Ebbehøj, Niels Erik; Mortensen, Ole Steen

    2008-12-01

    The dropout rate among student nursing assistants (NAs) in Danish health and social care education is high at >20%. To explore if recent low back pain (LBP) history is a predictor of dropout among NA students, taking into account conventional risk factors for LBP, general health and physical fitness. Prospective study with 14-month follow-up (the duration of the education) in two schools of health and social care in the Region of Copenhagen, Denmark. Participants completed a comprehensive questionnaire, and their physical fitness (balance, back extension endurance, back flexion endurance and sagittal flexibility) was assessed at baseline. Dropout was defined as failure to complete NA education. A total of 790 subjects, 87% of those invited, completed the questionnaire; 612 subjects also completed the physical tests and were included in the present study and 500 (83%) were women. Recent LBP was not an independent predictor of school dropout. However, only among women who had LBP were other factors (a history of previous exposure to heavy physical workload, a low mental health score and failure to pass the back extension endurance test) associated with risk of dropout, OR (95% CI)=2.5 (1.2-5.3). Among men, only low height was significantly associated with dropout risk. A recent LBP history was not an independent single predictor of dropout from NA education but was a risk factor in combination with other factors.

  3. IMPACT OF DIFFERENT TOPOGRAPHIC CORRECTIONS ON PREDICTION ACCURACY OF FOLIAGE PROJECTIVE COVER (FPC IN A TOPOGRAPHICALLY COMPLEX TERRAIN

    Directory of Open Access Journals (Sweden)

    S. Ediriweera

    2012-07-01

    Full Text Available Quantitative retrieval of land surface biological parameters (e.g. foliage projective cover [FPC] and Leaf Area Index is crucial for forest management, ecosystem modelling, and global change monitoring applications. Currently, remote sensing is a widely adopted method for rapid estimation of surface biological parameters in a landscape scale. Topographic correction is a necessary pre-processing step in the remote sensing application for topographically complex terrain. Selection of a suitable topographic correction method on remotely sensed spectral information is still an unresolved problem. The purpose of this study is to assess the impact of topographic corrections on the prediction of FPC in hilly terrain using an established regression model. Five established topographic corrections [C, Minnaert, SCS, SCS+C and processing scheme for standardised surface reflectance (PSSSR] were evaluated on Landsat TM5 acquired under low and high sun angles in closed canopied subtropical rainforest and eucalyptus dominated open canopied forest, north-eastern Australia. The effectiveness of methods at normalizing topographic influence, preserving biophysical spectral information, and internal data variability were assessed by statistical analysis and by comparing field collected FPC data. The results of statistical analyses show that SCS+C and PSSSR perform significantly better than other corrections, which were on less overcorrected areas of faintly illuminated slopes. However, the best relationship between FPC and Landsat spectral responses was obtained with the PSSSR by producing the least residual error. The SCS correction method was poor for correction of topographic effect in predicting FPC in topographically complex terrain.

  4. Evaluation of Different Topographic Corrections for Landsat TM Data by Prediction of Foliage Projective Cover (FPC in Topographically Complex Landscapes

    Directory of Open Access Journals (Sweden)

    Sisira Ediriweera

    2013-12-01

    Full Text Available The reflected radiance in topographically complex areas is severely affected by variations in topography; thus, topographic correction is considered a necessary pre-processing step when retrieving biophysical variables from these images. We assessed the performance of five topographic corrections: (i C correction (C, (ii Minnaert, (iii Sun Canopy Sensor (SCS, (iv SCS + C and (v the Processing Scheme for Standardised Surface Reflectance (PSSSR on the Landsat-5 Thematic Mapper (TM reflectance in the context of prediction of Foliage Projective Cover (FPC in hilly landscapes in north-eastern Australia. The performance of topographic corrections on the TM reflectance was assessed by (i visual comparison and (ii statistically comparing TM predicted FPC with ground measured FPC and LiDAR (Light Detection and Ranging-derived FPC estimates. In the majority of cases, the PSSSR method performed best in terms of eliminating topographic effects, providing the best relationship and lowest residual error when comparing ground measured FPC and LiDAR FPC with TM predicted FPC. The Minnaert, C and SCS + C showed the poorest performance. Finally, the use of TM surface reflectance, which includes atmospheric correction and broad Bidirectional Reflectance Distribution Function (BRDF effects, seemed to account for most topographic variation when predicting biophysical variables, such as FPC.

  5. Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model

    Science.gov (United States)

    Arumugam, S.; Libera, D.

    2017-12-01

    Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.

  6. Adaboost Ensemble with Simple Genetic Algorithm for Student Prediction Mode

    OpenAIRE

    AhmedSharaf ElDen; ElDen1Malaka A. Moustafa2Hany; M. Harb; AbdelH.Emara

    2013-01-01

    Predicting the student performance is a great concern to the higher education managements.Thisprediction helps to identify and to improve students' performance.Several factors may improve thisperformance.In the present study, we employ the data mining processes, particularly classification, toenhance the quality of the higher educational system. Recently, a new direction is used for the improvementof the classification accuracy by combining classifiers.In thispaper, we design and evaluate a f...

  7. Prediction of d^0 magnetism in self-interaction corrected density functional theory

    Science.gov (United States)

    Das Pemmaraju, Chaitanya

    2010-03-01

    Over the past couple of years, the phenomenon of ``d^0 magnetism'' has greatly intrigued the magnetism community [1]. Unlike conventional magnetic materials, ``d^0 magnets'' lack any magnetic ions with open d or f shells but surprisingly, exhibit signatures of ferromagnetism often with a Curie temperature exceeding 300 K. Current research in the field is geared towards trying to understand the mechanism underlying this observed ferromagnetism which is difficult to explain within the conventional m-J paradigm [1]. The most widely studied class of d^0 materials are un-doped and light element doped wide gap Oxides such as HfO2, MgO, ZnO, TiO2 all of which have been put forward as possible d0 ferromagnets. General experimental trends suggest that the magnetism is a feature of highly defective samples leading to the expectation that the phenomenon must be defect related. In particular, based on density functional theory (DFT) calculations acceptor defects formed from the O-2p states in these Oxides have been proposed as being responsible for the ferromagnetism [2,3]. However. predicting magnetism originating from 2p orbitals is a delicate problem, which depends on the subtle interplay between covalency and Hund's coupling. DFT calculations based on semi-local functionals such as the local spin-density approximation (LSDA) can lead to qualitative failures on several fronts. On one hand the excessive delocalization of spin-polarized holes leads to half-metallic ground states and the expectation of room-temperature ferromagnetism. On the other hand, in some cases a magnetic ground state may not be predicted at all as the Hund's coupling might be under estimated. Furthermore, polaronic distortions which are often a feature of acceptor defects in Oxides are not predicted [4,5]. In this presentation, we argue that the self interaction error (SIE) inherent to semi-local functionals is responsible for the failures of LSDA and demonstrate through various examples that beyond

  8. Predictive factors for perioperative blood transfusion in surgeries for correction of idiopathic, neuromuscular or congenital scoliosis

    Directory of Open Access Journals (Sweden)

    Alexandre Fogaça Cristante

    2014-12-01

    Full Text Available OBJECTIVE: To evaluate the association of clinical and demographic variables in patients requiring blood transfusion during elective surgery to treat scoliosis with the aim of identifying markers predictive of the need for blood transfusion. METHODS: Based on the review of medical charts at a public university hospital, this retrospective study evaluated whether the following variables were associated with the need for red blood cell transfusion (measured by the number of packs used during scoliosis surgery: scoliotic angle, extent of arthrodesis (number of fused levels, sex of the patient, surgery duration and type of scoliosis (neuromuscular, congenital or idiopathic. RESULTS: Of the 94 patients evaluated in a 55-month period, none required a massive blood transfusion (most patients needed less than two red blood cell packs. The number of packs was not significantly associated with sex or type of scoliosis. The extent of arthrodesis (r = 0.103, surgery duration (r = 0.144 and scoliotic angle (r = 0.004 were weakly correlated with the need for blood transfusion. Linear regression analysis showed an association between the number of spine levels submitted to arthrodesis and the volume of blood used in transfusions (p = 0.001. CONCLUSION: This study did not reveal any evidence of a significant association between the need for red blood cell transfusion and scoliotic angle, sex or surgery duration in scoliosis correction surgery. Submission of more spinal levels to arthrodesis was associated with the use of a greater number of blood packs.

  9. Predicting Academic Performance Based on Students' Blog and Microblog Posts

    NARCIS (Netherlands)

    Dascalu, Mihai; Popescu, Elvira; Becheru, Alexandru; Crossley, Scott; Trausan-Matu, Stefan

    2016-01-01

    This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal analysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in

  10. Predicting Student Success from the "LASSI for Learning Online" (LLO)

    Science.gov (United States)

    Carson, Andrew D.

    2011-01-01

    This study tested the degree to which subscales of the "LASSI for Learning Online" (LLO) (Weinstein & Palmer, 2006), a measure of learning strategies and study skills, predict student success in the form of passing grades, using a combination of large training (N = 4,409) and cross-validation (N = 3,203) samples. Discriminant function analysis…

  11. Predicting Student Performance in a Collaborative Learning Environment

    Science.gov (United States)

    Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

    2015-01-01

    Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

  12. Predicting Undergraduate Leadership Student Goal Orientation Using Personality Traits

    Science.gov (United States)

    Lamm, Kevan W.; Sheikh, Emana; Carter, Hannah S.; Lamm, Alexa J.

    2017-01-01

    Finding strategies to increase the motivation of students, their connection with the material, and retention of the content, has been very important within leadership education. Previous research studies have shown that personality traits can predict desired outcomes, including goal orientation or motivational disposition. However, there have not…

  13. Predicting Student Success in College: What Does the Research Say?

    Science.gov (United States)

    Merante, Joseph A.

    1983-01-01

    Reviews various methods for predicting college success: correlation of students' high school grades, achievement test scores, and class rank with characteristics of the institution to be attended; examination of demographic variables such as age, sex, birth order, income, parents' education, religious and ethnic background, and geographic factors;…

  14. Improving student success using predictive models and data visualisations

    Directory of Open Access Journals (Sweden)

    Hanan Ayad

    2012-08-01

    Full Text Available The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50–60%. At the college level in the US only 30% of students graduate from 2-year colleges in 3 years or less and approximately 50% graduate from 4-year colleges in 5 years or less. A basic challenge in delivering global education, therefore, is improving student success. By student success we mean improving retention, completion and graduation rates. In this paper we describe a Student Success System (S3 that provides a holistic, analytical view of student academic progress.1 The core of S3 is a flexible predictive modelling engine that uses machine intelligence and statistical techniques to identify at-risk students pre-emptively. S3 also provides a set of advanced data visualisations for reaching diagnostic insights and a case management tool for managing interventions. S3's open modular architecture will also allow integration and plug-ins with both open and proprietary software. Powered by learning analytics, S3 is intended as an end-to-end solution for identifying at-risk students, understanding why they are at risk, designing interventions to mitigate that risk and finally closing the feedback look by tracking the efficacy of the applied intervention.

  15. Predicting students' intention to use stimulants for academic performance enhancement.

    Science.gov (United States)

    Ponnet, Koen; Wouters, Edwin; Walrave, Michel; Heirman, Wannes; Van Hal, Guido

    2015-02-01

    The non-medical use of stimulants for academic performance enhancement is becoming a more common practice among college and university students. The objective of this study is to gain a better understanding of students' intention to use stimulant medication for the purpose of enhancing their academic performance. Based on an extended model of Ajzen's theory of planned behavior, we examined the predictive value of attitude, subjective norm, perceived behavioral control, psychological distress, procrastination, substance use, and alcohol use on students' intention to use stimulants to improve their academic performance. The sample consisted of 3,589 Flemish university and college students (mean age: 21.59, SD: 4.09), who participated anonymously in an online survey conducted in March and April 2013. Structural equation modeling was used to investigate the relationships among the study variables. Our results indicate that subjective norm is the strongest predictor of students' intention to use stimulant medication, followed by attitude and perceived behavioral control. To a lesser extent, procrastinating tendencies, psychological distress, and substance abuse contribute to students' intention. Conclusions/ Importance: Based on these findings, we provide several recommendations on how to curtail students' intention to use stimulant medication for the purpose of improving their academic performance. In addition, we urge researchers to identify other psychological variables that might be related to students' intention.

  16. Megavoltage photon beam attenuation by carbon fiber couch tops and its prediction using correction factors

    International Nuclear Information System (INIS)

    Hayashi, Naoki; Shibamoto, Yuta; Obata, Yasunori; Kimura, Takashi; Nakazawa, Hisato; Hagiwara, Masahiro; Hashizume, Chisa I.; Mori, Yoshimasa; Kobayashi, Tatsuya

    2010-01-01

    The purpose of this study was to evaluate the effect of megavoltage photon beam attenuation (PBA) by couch tops and to propose a method for correction of PBA. Four series of phantom measurements were carried out. First, PBA by the exact couch top (ECT, Varian) and Imaging Couch Top (ICT, BrainLAB) was evaluated using a water-equivalent phantom. Second, PBA by Type-S system (Med-Tec), ECT and ICT was compared with a spherical phantom. Third, percentage depth dose (PDD) after passing through ICT was measured to compare with control data of PDD. Forth, the gantry angle dependency of PBA by ICT was evaluated. Then, an equation for PBA correction was elaborated and correction factors for PBA at isocenter were obtained. Finally, this method was applied to a patient with hepatoma. PBA of perpendicular beams by ICT was 4.7% on average. With the increase in field size, the measured values became higher. PBA by ICT was greater than that by Type-S system and ECT. PBA increased significantly as the angle of incidence increased, ranging from 4.3% at 180 deg to 11.2% at 120 deg. Calculated doses obtained by the equation and correction factors agreed quite well with the measured doses between 120 deg and 180 deg of angles of incidence. Also in the patient, PBA by ICT was corrected quite well by the equation and correction factors. In conclusion, PBA and its gantry angle dependency by ICT were observed. This simple method using the equation and correction factors appeared useful to correct the isocenter dose when the PBA effect cannot be corrected by a treatment planning system. (author)

  17. Precise predictions of higgs boson decays including the full one-loop corrections in supersymmetry

    International Nuclear Information System (INIS)

    Frisch, W.

    2011-01-01

    The Standard Model of elementary particle physics is a highly successful theory, describing the electromagnetic, strong and weak interaction of matter particles up to energy scales to a few hundred giga electronvolt. Despite its great success in explaining experimental results correctly, there is hardly no doubt that the SM is an effective theory, which means that the theory loses its predictability at higher energies. Therefore, the Standard Model has to be extended in a proper way to describe physics at higher energies. A most promising concept for the extension of the SM is those of Supersymmetry, where for each particle of the SM one or more superpartner particles are introduced. The simplest and most attractive extension of the SM is called Minimal Supersymmetric Standard Model (MSSM). Minimal refers to the additional field content, which is kept as low as possible. In fact the MSSM consists of the fields of the SM and their corresponding supersymmetric partner fields, as well as one additional Higgs doublet. The presence of this additional Higgs doublet leads to the existence of five physical Higgs bosons in the MSSM. The search for supersymmetric particles and Higgs bosons is one of the primary goals of the Large Hadron Collider (LHC) at the CERN laboratory, producing collisions at sufficiently high energies to detect these particles. For the discovery of these new particles, precise pre- dictions of the corresponding decay widths and branching rations are utmost mandatory. To contribute with the precision of the LHC and the future ILC, Feynman amplitudes should be calculated at least to one-loop order. Since these calculations lead to so called UV- and IR- divergences, it is essential to perform a renormalization procedure, where the divergences are subtracted by a proper definition of counterterms. The goal of this work was to develop a program package, which calculates all MSSM two- body Higgs decay widths and corresponding branching ratios at full one

  18. BANKRUPTCY PREDICTION MODEL WITH ZETAc OPTIMAL CUT-OFF SCORE TO CORRECT TYPE I ERRORS

    Directory of Open Access Journals (Sweden)

    Mohamad Iwan

    2005-06-01

    This research has successfully attained the following results: (1 type I error is in fact 59,83 times more costly compared to type II error, (2 22 ratios distinguish between bankrupt and non-bankrupt groups, (3 2 financial ratios proved to be effective in predicting bankruptcy, (4 prediction using ZETAc optimal cut-off score predicts more companies filing for bankruptcy within one year compared to prediction using Hair et al. optimum cutting score, (5 Although prediction using Hair et al. optimum cutting score is more accurate, prediction using ZETAc optimal cut-off score proved to be able to minimize cost incurred from classification errors.

  19. Predicting stress in pre-registration nursing students.

    Science.gov (United States)

    Pryjmachuk, Steven; Richards, David A

    2007-02-01

    To determine which variables from a pool of potential predictors predict General Health Questionnaire 'caseness' in pre-registration nursing students. Cross-sectional survey, utilizing self-report measures of sources of stress, stress (psychological distress) and coping, together with pertinent demographic measures such as sex, ethnicity, educational programme and nursing specialty being pursued, and age, social class and highest qualifications on entry to the programme. Questionnaire packs were distributed to all pre-registration nursing students (N=1,362) in a large English university. Completed packs were coded, entered into statistical software and subjected to a series of logistic regression analyses. Of the questionnaire packs 1,005 (74%) were returned, of which up to 973 were available for the regression analyses undertaken. Four logistic regression models were considered and, on the principle of parsimony, a single model was chosen for discussion. This model suggested that the key predictors of caseness in the population studied were self-report of pressure, whether or not respondents had children (specifically, whether these children were pre-school or school-age), scores on a 'personal problems' scale and the type of coping employed. The overall caseness rate among the population was around one-third. Since self-report and personal, rather than academic, concerns predict stress, personal teachers need to play a key role in supporting students through 'active listening', especially when students self-report high levels of stress and where personal/social problems are evident. The work-life balance of students, especially those with child-care responsibilities, should be a central tenet in curriculum design in nurse education (and, indeed, the education of other professional and occupational groups). There may be some benefit in offering stress management (coping skills) training to nursing students and, indeed, students of other disciplines.

  20. Precise predictions of H2O line shapes over a wide pressure range using simulations corrected by a single measurement

    Science.gov (United States)

    Ngo, N. H.; Nguyen, H. T.; Tran, H.

    2018-03-01

    In this work, we show that precise predictions of the shapes of H2O rovibrational lines broadened by N2, over a wide pressure range, can be made using simulations corrected by a single measurement. For that, we use the partially-correlated speed-dependent Keilson-Storer (pcsdKS) model whose parameters are deduced from molecular dynamics simulations and semi-classical calculations. This model takes into account the collision-induced velocity-changes effects, the speed dependences of the collisional line width and shift as well as the correlation between velocity and internal-state changes. For each considered transition, the model is corrected by using a parameter deduced from its broadening coefficient measured for a single pressure. The corrected-pcsdKS model is then used to simulate spectra for a wide pressure range. Direct comparisons of the corrected-pcsdKS calculated and measured spectra of 5 rovibrational lines of H2O for various pressures, from 0.1 to 1.2 atm, show very good agreements. Their maximum differences are in most cases well below 1%, much smaller than residuals obtained when fitting the measurements with the Voigt line shape. This shows that the present procedure can be used to predict H2O line shapes for various pressure conditions and thus the simulated spectra can be used to deduce the refined line-shape parameters to complete spectroscopic databases, in the absence of relevant experimental values.

  1. Prediction of e± elastic scattering cross-section ratio based on phenomenological two-photon exchange corrections

    Science.gov (United States)

    Qattan, I. A.

    2017-06-01

    I present a prediction of the e± elastic scattering cross-section ratio, Re+e-, as determined using a new parametrization of the two-photon exchange (TPE) corrections to electron-proton elastic scattering cross section σR. The extracted ratio is compared to several previous phenomenological extractions, TPE hadronic calculations, and direct measurements from the comparison of electron and positron scattering. The TPE corrections and the ratio Re+e- show a clear change of sign at low Q2, which is necessary to explain the high-Q2 form factors discrepancy while being consistent with the known Q2→0 limit. While my predictions are in generally good agreement with previous extractions, TPE hadronic calculations, and existing world data including the recent two measurements from the CLAS and VEPP-3 Novosibirsk experiments, they are larger than the new OLYMPUS measurements at larger Q2 values.

  2. Reducing overlay sampling for APC-based correction per exposure by replacing measured data with computational prediction

    Science.gov (United States)

    Noyes, Ben F.; Mokaberi, Babak; Oh, Jong Hun; Kim, Hyun Sik; Sung, Jun Ha; Kea, Marc

    2016-03-01

    One of the keys to successful mass production of sub-20nm nodes in the semiconductor industry is the development of an overlay correction strategy that can meet specifications, reduce the number of layers that require dedicated chuck overlay, and minimize measurement time. Three important aspects of this strategy are: correction per exposure (CPE), integrated metrology (IM), and the prioritization of automated correction over manual subrecipes. The first and third aspects are accomplished through an APC system that uses measurements from production lots to generate CPE corrections that are dynamically applied to future lots. The drawback of this method is that production overlay sampling must be extremely high in order to provide the system with enough data to generate CPE. That drawback makes IM particularly difficult because of the throughput impact that can be created on expensive bottleneck photolithography process tools. The goal is to realize the cycle time and feedback benefits of IM coupled with the enhanced overlay correction capability of automated CPE without impacting process tool throughput. This paper will discuss the development of a system that sends measured data with reduced sampling via an optimized layout to the exposure tool's computational modelling platform to predict and create "upsampled" overlay data in a customizable output layout that is compatible with the fab user CPE APC system. The result is dynamic CPE without the burden of extensive measurement time, which leads to increased utilization of IM.

  3. Predicting Intentions to Seek Psychological Help Among Botswana University Students

    Directory of Open Access Journals (Sweden)

    Mpho M. Pheko

    2013-07-01

    Full Text Available The current study had two main objectives. The first was to investigate Botswana’s university students’ intentions to seek psychological help. The second was to investigate whether (a Attitude Toward Seeking Professional Psychological Help (ATSPPH, (b Self-Stigma of Seeking Help (SSOSH, and (c Social Stigma of Receiving Psychological Help (SSRPH predicted the students’ intentions to seek psychological help. A total of N = 519 (283 females and 236 males students from the University of Botswana completed the survey. Results indicated that generally, the students had moderate intentions of seeking psychological help. Multiple regression analysis revealed that of the three predictors, only ATSPPH and SSRPH significantly predicted intentions to seek psychological help. The current study is important because while it has been established that university students are a high-risk population for mental health problems, there is close to nothing documented on university students in Botswana. Findings of the current study will undoubtedly increase knowledge relating to psychological help-seeking and its predictors in Botswana and may inform interventions that aim to encourage young people to seek psychological or counseling help.

  4. Predicting the mental health of college students with psychological capital.

    Science.gov (United States)

    Selvaraj, Priscilla Rose; Bhat, Christine Suniti

    2018-06-01

    Behavioral health treatment is grounded in the medical model with language of deficits and problems, rather than resources and strengths. With developments in the field of positive psychology, re-focusing on well-being rather than illness is possible. The primary purpose of this study was to examine relationships and predictions that exist between levels of mental health in college students, i.e., flourishing, moderate mental health, and languishing, and psychological capital (PsyCap). For this cross-sectional, exploratory study survey method was used for data collection and for analyses of results a series of descriptive, correlation, ANOVA, and multiple regression analyses were done. Results indicated that developing positive psychological strengths such as hope, efficacy, resilience, and optimism (acronym HERO) within college students significantly increased their positive mental health. Based on the predictive nature of PsyCap, mental health professionals may engage more in creating programs incorporating PsyCap development intervention for college students. Implications for counseling and programmatic services for college students are presented along with suggestions for future research.

  5. Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

    Science.gov (United States)

    Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

    2017-10-01

    Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

  6. Simple prediction method of lumbar lordosis for planning of lumbar corrective surgery: radiological analysis in a Korean population.

    Science.gov (United States)

    Lee, Chong Suh; Chung, Sung Soo; Park, Se Jun; Kim, Dong Min; Shin, Seong Kee

    2014-01-01

    This study aimed at deriving a lordosis predictive equation using the pelvic incidence and to establish a simple prediction method of lumbar lordosis for planning lumbar corrective surgery in Asians. Eighty-six asymptomatic volunteers were enrolled in the study. The maximal lumbar lordosis (MLL), lower lumbar lordosis (LLL), pelvic incidence (PI), and sacral slope (SS) were measured. The correlations between the parameters were analyzed using Pearson correlation analysis. Predictive equations of lumbar lordosis through simple regression analysis of the parameters and simple predictive values of lumbar lordosis using PI were derived. The PI strongly correlated with the SS (r = 0.78), and a strong correlation was found between the SS and LLL (r = 0.89), and between the SS and MLL (r = 0.83). Based on these correlations, the predictive equations of lumbar lordosis were found (SS = 0.80 + 0.74 PI (r = 0.78, R (2) = 0.61), LLL = 5.20 + 0.87 SS (r = 0.89, R (2) = 0.80), MLL = 17.41 + 0.96 SS (r = 0.83, R (2) = 0.68). When PI was between 30° to 35°, 40° to 50° and 55° to 60°, the equations predicted that MLL would be PI + 10°, PI + 5° and PI, and LLL would be PI - 5°, PI - 10° and PI - 15°, respectively. This simple calculation method can provide a more appropriate and simpler prediction of lumbar lordosis for Asian populations. The prediction of lumbar lordosis should be used as a reference for surgeons planning to restore the lumbar lordosis in lumbar corrective surgery.

  7. An Integrated Loop Model of Corrective Feedback and Oral English Learning: A Case of International Students in the United States

    Science.gov (United States)

    Lee, Eun Jeong

    2017-01-01

    The author in this study introduces an integrated corrective feedback (CF) loop to schematize the interplay between CF and independent practice in L2 oral English learning among advanced-level adult ESL students. The CF loop integrates insights from the Interaction, Output, and Noticing Hypotheses to show how CF can help or harm L2 learners'…

  8. Correction Notice: Tools for Citizen-Science Recruitment and Student Engagement in Your Research and in Your Classroom

    Directory of Open Access Journals (Sweden)

    JMBE Production Editor

    2016-05-01

    Full Text Available Correction for Sarah E. Council and Julie E. Horvath, “Tools for Citizen-Science Recruitment and Student Engagement in Your Research and in Your Classroom,” which appeared in the Journal of Microbiology & Biology Education, volume 17, number 1, March 2016, pages 38–40.

  9. Psychometric Properties of the Satisfaction with Life Scale among Turkish University Students, Correctional Officers, and Elderly Adults

    Science.gov (United States)

    Durak, Mithat; Senol-Durak, Emre; Gencoz, Tulin

    2010-01-01

    This study aims to extensively examine the psychometric properties of adapted version of the Satisfaction with Life Scale (SWLS) in different Turkish samples. In order to test the psychometric properties of the SWLS three separate and independent samples are utilized in this study, namely university students (n = 547), correctional officers (n =…

  10. Predicting approach to homework in Primary school students.

    Science.gov (United States)

    Valle, Antonio; Pan, Irene; Regueiro, Bibiana; Suárez, Natalia; Tuero, Ellián; Nunes, Ana R

    2015-01-01

    The goal of this research was to study the weight of student variables related to homework (intrinsic homework motivation, perceived homework instrumentality, homework attitude, time spent on homework, and homework time management) and context (teacher feedback on homework and parental homework support) in the prediction of approaches to homework. 535 students of the last three courses of primary education participated in the study. Data were analyzed with hierarchical regression models and path analysis. The results obtained suggest that students’ homework engagement (high or low) is related to students´ level of intrinsic motivation and positive attitude towards homework. Furthermore, it was also observed that students who manage their homework time well (and not necessarily those who spend more time) are more likely to show the deepest approach to homework. Parental support and teacher feedback on homework affect student homework engagement through their effect on the levels of intrinsic homework motivation (directly), and on homework attitude, homework time management, and perceived homework instrumentality (indirectly). Data also indicated a strong and significant relationship between parental and teacher involvement.

  11. Physiotherapy students' perceptions and experiences of clinical prediction rules.

    Science.gov (United States)

    Knox, Grahame M; Snodgrass, Suzanne J; Stanton, Tasha R; Kelly, David H; Vicenzino, Bill; Wand, Benedict M; Rivett, Darren A

    2017-09-01

    Clinical reasoning can be difficult to teach to pre-professional physiotherapy students due to their lack of clinical experience. It may be that tools such as clinical prediction rules (CPRs) could aid the process, but there has been little investigation into their use in physiotherapy clinical education. This study aimed to determine the perceptions and experiences of physiotherapy students regarding CPRs, and whether they are learning about CPRs on clinical placement. Cross-sectional survey using a paper-based questionnaire. Final year pre-professional physiotherapy students (n=371, response rate 77%) from five universities across five states of Australia. Sixty percent of respondents had not heard of CPRs, and a further 19% had not clinically used CPRs. Only 21% reported using CPRs, and of these nearly three-quarters were rarely, if ever, learning about CPRs in the clinical setting. However most of those who used CPRs (78%) believed CPRs assisted in the development of clinical reasoning skills and none (0%) was opposed to the teaching of CPRs to students. The CPRs most commonly recognised and used by students were those for determining the need for an X-ray following injuries to the ankle and foot (67%), and for identifying deep venous thrombosis (63%). The large majority of students in this sample knew little, if anything, about CPRs and few had learned about, experienced or practiced them on clinical placement. However, students who were aware of CPRs found them helpful for their clinical reasoning and were in favour of learning more about them. Copyright © 2016 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  12. Real time prediction and correction of ADCS problems in LEO satellites using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Yassin Mounir Yassin

    2017-06-01

    Full Text Available This approach is concerned with adapting the operations of attitude determination and control subsystem (ADCS of low earth orbit LEO satellites through analyzing the telemetry readings received by mission control center, and then responding to ADCS off-nominal situations. This can be achieved by sending corrective operational Tele-commands within real time. Our approach is related to the fuzzy membership of off-nominal telemetry readings of corrective actions through a set of fuzzy rules based on understanding the ADCS modes resulted from the satellite telemetry readings. Response in real time gives us a chance to avoid risky situations. The approach is tested on the EgyptSat-1 engineering model, which is our method to simulate the results.

  13. Accurate density functional prediction of molecular electron affinity with the scaling corrected Kohn–Sham frontier orbital energies

    Science.gov (United States)

    Zhang, DaDi; Yang, Xiaolong; Zheng, Xiao; Yang, Weitao

    2018-04-01

    Electron affinity (EA) is the energy released when an additional electron is attached to an atom or a molecule. EA is a fundamental thermochemical property, and it is closely pertinent to other important properties such as electronegativity and hardness. However, accurate prediction of EA is difficult with density functional theory methods. The somewhat large error of the calculated EAs originates mainly from the intrinsic delocalisation error associated with the approximate exchange-correlation functional. In this work, we employ a previously developed non-empirical global scaling correction approach, which explicitly imposes the Perdew-Parr-Levy-Balduz condition to the approximate functional, and achieve a substantially improved accuracy for the calculated EAs. In our approach, the EA is given by the scaling corrected Kohn-Sham lowest unoccupied molecular orbital energy of the neutral molecule, without the need to carry out the self-consistent-field calculation for the anion.

  14. A national prediction model for PM2.5 component exposures and measurement error-corrected health effect inference.

    Science.gov (United States)

    Bergen, Silas; Sheppard, Lianne; Sampson, Paul D; Kim, Sun-Young; Richards, Mark; Vedal, Sverre; Kaufman, Joel D; Szpiro, Adam A

    2013-09-01

    Studies estimating health effects of long-term air pollution exposure often use a two-stage approach: building exposure models to assign individual-level exposures, which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error. To illustrate the importance of accounting for exposure model characteristics in two-stage air pollution studies, we considered a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA). We built national spatial exposure models that used partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), silicon (Si), and sulfur (S). We predicted PM2.5 component exposures for the MESA cohort and estimated cross-sectional associations with carotid intima-media thickness (CIMT), adjusting for subject-specific covariates. We corrected for measurement error using recently developed methods that account for the spatial structure of predicted exposures. Our models performed well, with cross-validated R2 values ranging from 0.62 to 0.95. Naïve analyses that did not account for measurement error indicated statistically significant associations between CIMT and exposure to OC, Si, and S. EC and OC exhibited little spatial correlation, and the corrected inference was unchanged from the naïve analysis. The Si and S exposure surfaces displayed notable spatial correlation, resulting in corrected confidence intervals (CIs) that were 50% wider than the naïve CIs, but that were still statistically significant. The impact of correcting for measurement error on health effect inference is concordant with the degree of spatial correlation in the exposure surfaces. Exposure model characteristics must be considered when performing two-stage air pollution epidemiologic analyses because naïve health effect inference may be inappropriate.

  15. Real-time axial motion detection and correction for single photon emission computed tomography using a linear prediction filter

    International Nuclear Information System (INIS)

    Saba, V.; Setayeshi, S.; Ghannadi-Maragheh, M.

    2011-01-01

    We have developed an algorithm for real-time detection and complete correction of the patient motion effects during single photon emission computed tomography. The algorithm is based on a linear prediction filter (LPC). The new prediction of projection data algorithm (PPDA) detects most motions-such as those of the head, legs, and hands-using comparison of the predicted and measured frame data. When the data acquisition for a specific frame is completed, the accuracy of the acquired data is evaluated by the PPDA. If patient motion is detected, the scanning procedure is stopped. After the patient rests in his or her true position, data acquisition is repeated only for the corrupted frame and the scanning procedure is continued. Various experimental data were used to validate the motion detection algorithm; on the whole, the proposed method was tested with approximately 100 test cases. The PPDA shows promising results. Using the PPDA enables us to prevent the scanner from collecting disturbed data during the scan and replaces them with motion-free data by real-time rescanning for the corrupted frames. As a result, the effects of patient motion is corrected in real time. (author)

  16. A Model to Predict Student Failure in the First Year of the Undergraduate Medical Curriculum

    Directory of Open Access Journals (Sweden)

    Gerard J.A. Baars

    2017-06-01

    Discussion: The earliest moment with the highest specificity to predict student failure in the first-year curriculum seems to be at 6 months. However, additional factors are needed to improve this prediction or to bring forward the predictive moment.

  17. Happy classes make happy students: Classmates' well-being predicts individual student well-being.

    Science.gov (United States)

    King, Ronnel B; Datu, Jesus Alfonso

    2017-12-01

    Student well-being has mostly been studied as an individual phenomenon with little research investigating how the well-being of one's classmates could influence a student's well-being. The aim of the current study was to examine how the aggregate well-being of students who comprise a class could predict students' subsequent well-being (Time 2 well-being) after controlling for the effects of prior well-being (Time 1 well-being) as well as key demographic variables such as gender and age. Two studies among Filipino secondary school students were conducted. In Study 1, 788 students from 21 classes participated; in Study 2, 404 students from 10 classes participated. For Study 1, questionnaires assessing students' life satisfaction, positive affect and negative affect were administered twice seven months apart. For Study 2, the well-being questionnaires were administered twice, three months apart. Hierarchical linear modeling was used with level 1 (Time 1 individual well-being, gender, and age) and level 2 (class well-being) predictors. Results across the two studies provided converging lines of evidence: students who were in classes with higher levels of life satisfaction and positive affect were also more likely to have higher life satisfaction and positive affect at Time 2. The study indicated that the well-being of a student partly depends on the well-being of their classmates providing evidence for the social contagion of well-being in the classroom context. Copyright © 2017 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  18. DEFINITION OF TYPOS IN ANSWER OF STUDENT IN KNOWN CORRECT ANSWER

    Directory of Open Access Journals (Sweden)

    Maria V. Biryukova

    2015-01-01

    Full Text Available The paper describes method of typo detection in the answers for the questions with open answers. In such questions we know one or several correct answers defining relatively small dictionary of correct words contrasting the usual case of looking for typos in arbitrary text. This fact allows using more complex analysis methods and finding more possible typos, such as extra or missing separators. A typo correction module for the Correct Writing question type (for Moodle LMS was developed using proposed methods. 

  19. Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected].

    Science.gov (United States)

    Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna; Tramontano, Anna

    2014-12-01

    Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

  20. An Analysis of College Students' Attitudes towards Error Correction in EFL Context

    Science.gov (United States)

    Zhu, Honglin

    2010-01-01

    This article is based on a survey on the attitudes towards the error correction by their teachers in the process of teaching and learning and it is intended to improve the language teachers' understanding of the nature of error correction. Based on the analysis, the article expounds some principles and techniques that can be applied in the process…

  1. Impact of Self-Correction on Extrovert and Introvert Students in EFL Writing Progress

    Science.gov (United States)

    Hajimohammadi, Reza; Makundan, Jayakaran

    2011-01-01

    To investigate the impact of self-correction method as an alternative to the traditional teacher-correction method, on the one side, and to evaluate the impact of personality traits of Extroversion/Introversion, on the other side, on the writing progress of the pre-intermediate learners three null-hypotheses were proposed. In spite of students…

  2. Preservice music teachers' predictions, perceptions, and assessment of students with special needs: the need for training in student assessment.

    Science.gov (United States)

    VanWeelden, Kimberly; Whipple, Jennifer

    2007-01-01

    The purpose of the current study was to examine preservice teachers' predictions and perceptions of students with special needs' levels of mastery of specific music education concepts and actual grades achieved by these students using alternative assessments and testing accommodations within two subpopulations: students with emotional and/or behavior disorders (EDBD) and students with acute cognitive delays (ACD). The preservice teachers predicted students within the EDBD class would achieve a significantly higher level of mastery of the music concepts than students within the ACD classroom. After the field experience, however, the preservice teachers' perceptions of all students' levels of mastery increased from prediction scores overall. Additionally, preservice teachers were able to execute testing accommodations and implement successful alternative assessments which gave empirical data on the students' levels of mastery of the music education concepts within the curriculum. Implications for music therapists, as consultants in special education, are discussed.

  3. Neither Basic Life Support knowledge nor self-efficacy are predictive of skills among dental students.

    Science.gov (United States)

    Mac Giolla Phadraig, C; Ho, J D; Guerin, S; Yeoh, Y L; Mohamed Medhat, M; Doody, K; Hwang, S; Hania, M; Boggs, S; Nolan, A; Nunn, J

    2017-08-01

    Basic life support (BLS) is considered a core competence for the graduating dentist. This study aimed to measure BLS knowledge, self-efficacy and skills of undergraduate dental students in Dublin. This study consisted of a cross-sectional survey measuring BLS knowledge and self-efficacy, accompanied by a directly observed BLS skills assessment in a subsample of respondents. Data were collected in January 2014. Bivariate correlations between descriptive and outcome variables (knowledge, self-efficacy and skills) were tested using Pearson's chi-square. We included knowledge and self-efficacy as predictor variables, along with other variables showing association, into a binary logistic regression model with BLS skills as the outcome measure. One hundred and thirty-five students participated. Almost all (n = 133, 98.5%) participants had BLS training within the last 2 years. One hundred and four (77%) felt that they were capable of providing effective BLS (self-efficacy), whilst only 46 (34.1%) scored >80% of knowledge items correct. Amongst the skills (n = 85) subsample, 38.8% (n = 33) were found to pass the BLS skills assessment. Controlling for gender, age and skills assessor, the regression model did not identify a predictive relationship between knowledge or self-efficacy and BLS skills. Neither knowledge nor self-efficacy was predictive of BLS skills. Dental students had low levels of knowledge and skills in BLS. Despite this, their confidence in their ability to perform BLS was high and did not predict actual competence. There is a need for additional hands-on training, focusing on self-efficacy and BLS skills, particularly the use of AED. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. Calibration between Undergraduate Students' Prediction of and Actual Performance: The Role of Gender and Performance Attributions

    Science.gov (United States)

    Gutierrez, Antonio P.; Price, Addison F.

    2017-01-01

    This study investigated changes in male and female students' prediction and postdiction calibration accuracy and bias scores, and the predictive effects of explanatory styles on these variables beyond gender. Seventy undergraduate students rated their confidence in performance before and after a 40-item exam. There was an improvement in students'…

  5. Scaling Student Success with Predictive Analytics: Reflections after Four Years in the Data Trenches

    Science.gov (United States)

    Wagner, Ellen; Longanecker, David

    2016-01-01

    The metrics used in the US to track students do not include adults and part-time students. This has led to the development of a massive data initiative--the Predictive Analytics Reporting (PAR) framework--that uses predictive analytics to trace the progress of all types of students in the system. This development has allowed actionable,…

  6. Iranian EFL Students' Writing Strategies for Error Correction: An MI Approach

    Science.gov (United States)

    Ansari, Dariush Nejad; Varnosfadrani, Azizollah Dabaghi

    2010-01-01

    This study tries to shed some light on the Iranian EFL students' writing strategies at the revision stage of the process of writing in relation to students' interpersonal or intrapersonal intelligences. A total of 73 students majoring in English participated in this investigation. The results indicated that there was a significant relationship…

  7. Immediate postoperative outcome of orthognathic surgical planning, and prediction of positional changes in hard and soft tissue, independently of the extent and direction of the surgical corrections required

    DEFF Research Database (Denmark)

    Donatsky, Ole; Bjørn-Jørgensen, Jens; Hermund, Niels Ulrich

    2011-01-01

    orthognathic correction using the computerised, cephalometric, orthognathic, surgical planning system (TIOPS). Preoperative cephalograms were analysed and treatment plans and prediction tracings produced by computerised interactive simulation. The planned changes were transferred to models and finally...... with the presently included soft tissue algorithms, the current study shows relatively high mean predictability of the immediately postoperative hard and soft tissue outcome, independent of the extent and direction of required orthognathic correction. Because of the relatively high individual variability, caution...

  8. Prediction of CT Substitutes from MR Images Based on Local Diffeomorphic Mapping for Brain PET Attenuation Correction.

    Science.gov (United States)

    Wu, Yao; Yang, Wei; Lu, Lijun; Lu, Zhentai; Zhong, Liming; Huang, Meiyan; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

    2016-10-01

    Attenuation correction is important for PET reconstruction. In PET/MR, MR intensities are not directly related to attenuation coefficients that are needed in PET imaging. The attenuation coefficient map can be derived from CT images. Therefore, prediction of CT substitutes from MR images is desired for attenuation correction in PET/MR. This study presents a patch-based method for CT prediction from MR images, generating attenuation maps for PET reconstruction. Because no global relation exists between MR and CT intensities, we propose local diffeomorphic mapping (LDM) for CT prediction. In LDM, we assume that MR and CT patches are located on 2 nonlinear manifolds, and the mapping from the MR manifold to the CT manifold approximates a diffeomorphism under a local constraint. Locality is important in LDM and is constrained by the following techniques. The first is local dictionary construction, wherein, for each patch in the testing MR image, a local search window is used to extract patches from training MR/CT pairs to construct MR and CT dictionaries. The k-nearest neighbors and an outlier detection strategy are then used to constrain the locality in MR and CT dictionaries. Second is local linear representation, wherein, local anchor embedding is used to solve MR dictionary coefficients when representing the MR testing sample. Under these local constraints, dictionary coefficients are linearly transferred from the MR manifold to the CT manifold and used to combine CT training samples to generate CT predictions. Our dataset contains 13 healthy subjects, each with T1- and T2-weighted MR and CT brain images. This method provides CT predictions with a mean absolute error of 110.1 Hounsfield units, Pearson linear correlation of 0.82, peak signal-to-noise ratio of 24.81 dB, and Dice in bone regions of 0.84 as compared with real CTs. CT substitute-based PET reconstruction has a regression slope of 1.0084 and R 2 of 0.9903 compared with real CT-based PET. In this method, no

  9. Iris-fixated phakic intraocular lens implantation to correct myopia and a predictive model of endothelial cell loss.

    Science.gov (United States)

    Bouheraoua, Nacim; Bonnet, Clemence; Labbé, Antoine; Sandali, Otman; Lecuen, Nicolas; Ameline, Barbara; Borderie, Vincent; Laroche, Laurent

    2015-11-01

    To report long-term results of Artisan phakic intraocular lens (pIOL) to correct myopia and to propose a model predicting endothelial cell loss after pIOL implantation. Quinze-Vingts National Ophthalmology Hospital, Paris, France. Retrospective, interventional case series. Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), and central endothelial cell count (ECC) were determined before and at yearly intervals up to 5 years after pIOL implantation. Linear model analysis was performed to present a model that describes endothelial cell loss as a linear decrease and an additional decrease depending on postoperative loss. A total of 49 patients (68 eyes) implanted with pIOLs from January 2000 to January 2009 were evaluated. The mean preoperative and final spherical equivalent (SE) were -13 ± 4.10 and -0.75 ± 0.74 diopters (D), respectively. The mean preoperative and final central ECC were 2629 ± 366 and 2250 ± 454 cells/mm(2), respectively. There were no intraoperative complications for any of the eyes. One eye required surgery for repositioning the pIOL, and 1 eye required pIOL exchange for postoperative refractive error. The model predicted that for patients with preoperative ECC of 3000, 2500, and 2000 cells/mm(2), a critical ECC of 1500 cells/mm(2) will be reached at 39, 28, and 15 years after implantation, respectively. Implantation of the pIOL was an effective and stable procedure after 5 years of follow-up. The presented model predicted EC loss after pIOL implantation, which can assist ophthalmologists in patient selection and follow-up. The authors report no conflict of interest. Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

  10. A Model for Predicting Student Performance on High-Stakes Assessment

    Science.gov (United States)

    Dammann, Matthew Walter

    2010-01-01

    This research study examined the use of student achievement on reading and math state assessments to predict success on the science state assessment. Multiple regression analysis was utilized to test the prediction for all students in grades 5 and 8 in a mid-Atlantic state. The prediction model developed from the analysis explored the combined…

  11. The effectiveness of the pilot program of differentiated correction of psycho-physical condition of students in physical education

    Directory of Open Access Journals (Sweden)

    A.V. Lukavenko

    2013-05-01

    Full Text Available Defined and justified the designing an algorithm for the formation and operation of the content of physical education students. The algorithm is aimed at correcting the mental and physical condition of students in the relevant classes in high school. In the experiment involved a group of boys and girls of 20 people 17-18 years of age.The program provides theoretical and methodological, practical training, and certain types of control. The basis of the program is a differentiated approach to students with the features of display, speakers, self-determination, the relationship between the change in indicators of mental and physical state in the first year of study. Project operations are focused on meeting the requirements of the principles of physical education, the provisions of the public education on maintaining a physically active lifestyle. It is recommended for theoretical and methodological training of the use of modern information tools. Showing the direction of correction of psycho-physical condition of students.

  12. Social problem solving ability predicts mental health among undergraduate students.

    Science.gov (United States)

    Ranjbar, Mansour; Bayani, Ali Asghar; Bayani, Ali

    2013-11-01

    The main objective of this study was predicting student's mental health using social problem solving- ability. In this correlational. descriptive study, 369 (208 female and 161 male) from, Mazandaran University of Medical Science were selected through stratified random sampling method. In order to collect the data, the social problem solving inventory-revised and general health questionnaire were used. Data were analyzed through SPSS-19, Pearson's correlation, t test, and stepwise regression analysis. Data analysis showed significant relationship between social problem solving ability and mental health (P Social problem solving ability was significantly associated with the somatic symptoms, anxiety and insomnia, social dysfunction and severe depression (P social problem solving ability and mental health.

  13. The Prediction of College Student Academic Performance and Retention: Application of Expectancy and Goal Setting Theories

    Science.gov (United States)

    Friedman, Barry A.; Mandel, Rhonda G.

    2010-01-01

    Student retention and performance in higher education are important issues for educators, students, and the nation facing critical professional labor shortages. Expectancy and goal setting theories were used to predict academic performance and college student retention. Students' academic expectancy motivation at the start of the college…

  14. SU-F-J-219: Predicting Ventilation Change Due to Radiation Therapy: Dependency On Pre-RT Ventilation and Effort Correction

    Energy Technology Data Exchange (ETDEWEB)

    Patton, T; Du, K; Bayouth, J [University of Wisconsin, Madison, WI (United States); Christensen, G; Reinhardt, J [University of Iowa, Iowa City, IA (United States)

    2016-06-15

    Purpose: Ventilation change caused by radiation therapy (RT) can be predicted using four-dimensional computed tomography (4DCT) and image registration. This study tested the dependency of predicted post-RT ventilation on effort correction and pre-RT lung function. Methods: Pre-RT and 3 month post-RT 4DCT images were obtained for 13 patients. The 4DCT images were used to create ventilation maps using a deformable image registration based Jacobian expansion calculation. The post-RT ventilation maps were predicted in four different ways using the dose delivered, pre-RT ventilation, and effort correction. The pre-RT ventilation and effort correction were toggled to determine dependency. The four different predicted ventilation maps were compared to the post-RT ventilation map calculated from image registration to establish the best prediction method. Gamma pass rates were used to compare the different maps with the criteria of 2mm distance-to-agreement and 6% ventilation difference. Paired t-tests of gamma pass rates were used to determine significant differences between the maps. Additional gamma pass rates were calculated using only voxels receiving over 20 Gy. Results: The predicted post-RT ventilation maps were in agreement with the actual post-RT maps in the following percentage of voxels averaged over all subjects: 71% with pre-RT ventilation and effort correction, 69% with no pre-RT ventilation and effort correction, 60% with pre-RT ventilation and no effort correction, and 58% with no pre-RT ventilation and no effort correction. When analyzing only voxels receiving over 20 Gy, the gamma pass rates were respectively 74%, 69%, 65%, and 55%. The prediction including both pre- RT ventilation and effort correction was the only prediction with significant improvement over using no prediction (p<0.02). Conclusion: Post-RT ventilation is best predicted using both pre-RT ventilation and effort correction. This is the only prediction that provided a significant

  15. Analysis of Student Misbehavior Patterns: Corrective Guidelines for Administrators and Teachers in Alternative Education Programs.

    Science.gov (United States)

    Dix, Jerry Edward; Karr-Kidwell, PJ

    This paper presents an analysis of adolescent violent behavior in schools. The paper offers an overview that includes student violence and discipline issues, school law, special services for at-risk students, and programs to enhance the opportunities for successful interventions. The paper is also a vehicle for a new discipline-management…

  16. Seasonal predictions of equatorial Atlantic SST in a low-resolution CGCM with surface heat flux correction

    Science.gov (United States)

    Dippe, Tina; Greatbatch, Richard; Ding, Hui

    2016-04-01

    The dominant mode of interannual variability in tropical Atlantic sea surface temperatures (SSTs) is the Atlantic Niño or Zonal Mode. Akin to the El Niño-Southern Oscillation in the Pacific sector, it is able to impact the climate both of the adjacent equatorial African continent and remote regions. Due to heavy biases in the mean state climate of the equatorial-to-subtropical Atlantic, however, most state-of-the-art coupled global climate models (CGCMs) are unable to realistically simulate equatorial Atlantic variability. In this study, the Kiel Climate Model (KCM) is used to investigate the impact of a simple bias alleviation technique on the predictability of equatorial Atlantic SSTs. Two sets of seasonal forecasting experiments are performed: An experiment using the standard KCM (STD), and an experiment with additional surface heat flux correction (FLX) that efficiently removes the SST bias from simulations. Initial conditions for both experiments are generated by the KCM run in partially coupled mode, a simple assimilation technique that forces the KCM with observed wind stress anomalies and preserves SST as a fully prognostic variable. Seasonal predictions for both sets of experiments are run four times yearly for 1981-2012. Results: Heat flux correction substantially improves the simulated variability in the initialization runs for boreal summer and fall (June-October). In boreal spring (March-May), however, neither the initialization runs of the STD or FLX-experiments are able to capture the observed variability. FLX-predictions show no consistent enhancement of skill relative to the predictions of the STD experiment over the course of the year. The skill of persistence forecasts is hardly beat by either of the two experiments in any season, limiting the usefulness of the few forecasts that show significant skill. However, FLX-forecasts initialized in May recover skill in July and August, the peak season of the Atlantic Niño (anomaly correlation

  17. Assessment of a non-uniform heat flux correction model to predicting CHF in PWR rod bundles

    International Nuclear Information System (INIS)

    Dae-Hyun, Hwang; Sung-Quun, Zee

    2001-01-01

    The full text follows. The prediction of CHF (critical heat flux) has been, in most cases, based on the empirical correlation. For PWR fuel assemblies the local parameter correlation requires the local thermal-hydraulic conditions usually calculated by a subchannel analysis code. The cross-sectional averaged fluid conditions of the subchannel, however, are not sufficient for determining CHF, especially for the cases of non-uniform axial heat flux distributions. Many investigators have studied the effect of the upstream heat flux on the CHF. In terms of the upstream memory effect, two different approaches have been considered as the limiting cases. The 'local conditions' hypothesis assumes that there is a unique relationship between the CHF and the local thermal-hydraulic conditions, and consequently there is no memory effect. In the 'overall power' hypothesis, on the other hand, it is assumed that the total power which can be fed into the tube with nonuniform heating will be the same as that for a uniformly heated tube of the same heated length with the same inlet conditions. Thus the CHF is totally influenced by the upstream heat flux distribution. In view of some experimental investigations such as the DeBortoli's test, it revealed that the two approaches are inadequate in general. It means that the local critical heat flux may be affected to some extent by the heat flux distribution upstream of the CHF location. Some correction-factor models have been suggested to take into account the upstream memory effect. Typically, Tong devised a correction factor on the basis of the heat balance of the superheated liquid layer that is spread underneath a highly viscous bubbly layer along the heated surface. His physical model suggested that the fluid enthalpy obtained from an energy balance of the superheated liquid layer is a representative quantity for the onset of DNB (departure nucleate boiling). A theoretically based correction factor model has been proposed by the

  18. Spatial measurement error and correction by spatial SIMEX in linear regression models when using predicted air pollution exposures.

    Science.gov (United States)

    Alexeeff, Stacey E; Carroll, Raymond J; Coull, Brent

    2016-04-01

    Spatial modeling of air pollution exposures is widespread in air pollution epidemiology research as a way to improve exposure assessment. However, there are key sources of exposure model uncertainty when air pollution is modeled, including estimation error and model misspecification. We examine the use of predicted air pollution levels in linear health effect models under a measurement error framework. For the prediction of air pollution exposures, we consider a universal Kriging framework, which may include land-use regression terms in the mean function and a spatial covariance structure for the residuals. We derive the bias induced by estimation error and by model misspecification in the exposure model, and we find that a misspecified exposure model can induce asymptotic bias in the effect estimate of air pollution on health. We propose a new spatial simulation extrapolation (SIMEX) procedure, and we demonstrate that the procedure has good performance in correcting this asymptotic bias. We illustrate spatial SIMEX in a study of air pollution and birthweight in Massachusetts. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. Lifting scheme-based method for joint coding 3D stereo digital cinema with luminace correction and optimized prediction

    Science.gov (United States)

    Darazi, R.; Gouze, A.; Macq, B.

    2009-01-01

    Reproducing a natural and real scene as we see in the real world everyday is becoming more and more popular. Stereoscopic and multi-view techniques are used for this end. However due to the fact that more information are displayed requires supporting technologies such as digital compression to ensure the storage and transmission of the sequences. In this paper, a new scheme for stereo image coding is proposed. The original left and right images are jointly coded. The main idea is to optimally exploit the existing correlation between the two images. This is done by the design of an efficient transform that reduces the existing redundancy in the stereo image pair. This approach was inspired by Lifting Scheme (LS). The novelty in our work is that the prediction step is been replaced by an hybrid step that consists in disparity compensation followed by luminance correction and an optimized prediction step. The proposed scheme can be used for lossless and for lossy coding. Experimental results show improvement in terms of performance and complexity compared to recently proposed methods.

  20. Impact of correcting visual impairment and low vision in deaf-mute students in Pune, India.

    Science.gov (United States)

    Gogate, Parikshit; Bhusan, Shashi; Ray, Shantanu; Shinde, Amit

    2016-12-01

    The aim of this study was to evaluate visual acuity and vision function before and after providing spectacles and low vision devices (LVDs) in deaf-mute students. Schools for deaf-mute in West Maharashtra. Hearing-impaired children in all special schools in Pune district underwent detailed visual acuity testing (with teachers' help), refraction, external ocular examination, and fundoscopy. Students with refractive errors and low vision were provided with spectacles and LVD. The LV Prasad-Functional Vision Questionnaire consisting of twenty items was administered to each subject before and after providing spectacles, LVDs. Wilcoxon matched-pairs signed-ranks test. 252/929 (27.1%) students had a refractive error. 794 (85.5%) were profound deaf. Two-hundred and fifty students were dispensed spectacles and LVDs. Mean LogMAR visual acuity before introduction of spectacles and LVDs were 0.33 ± 0.36 which improved to 0.058 (P vision pre- and post-intervention was statistically significant (P vision was much worse than their friend's vision, which was reduced to 17.6% after dispensing spectacles and LVDs. Spectacle and LVD reduced visual impairment and improved vision function in deaf-mute students, augmenting their ability to negotiate in and out of school.

  1. Building Models to Predict Hint-or-Attempt Actions of Students

    Science.gov (United States)

    Castro, Francisco Enrique Vicente; Adjei, Seth; Colombo, Tyler; Heffernan, Neil

    2015-01-01

    A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…

  2. Predicting Academic Success from Academic Motivation and Learning Approaches in Classroom Teaching Students

    Science.gov (United States)

    Çetin, Baris

    2015-01-01

    Our aim was to determine whether learning approaches and academic motivation together predict academic success of classroom teaching students. The sample of the study included 536 students (386 female, 150 male) studying at the Classroom Teaching Division of Canakkale 18 Mart University. Our research was designed as a prediction study. Data was…

  3. Predicting Persistence and Withdrawal of Open Admissions Students at Virginia State University.

    Science.gov (United States)

    Tambe, Joseph T.

    1984-01-01

    A study of persistence/dropout among open admissions college students found: (1) accurate predictions cannot be made for individual students at the time of matriculation; and (2) it is possible to predict that about 80 percent of future groups will fall in the persist category after two semesters, 51 percent after four semesters. (CMG)

  4. Predicting Eight Grade Students' Equation Solving Performances via Concepts of Variable and Equality

    Science.gov (United States)

    Ertekin, Erhan

    2017-01-01

    This study focused on how two algebraic concepts- equality and variable- predicted 8th grade students' equation solving performance. In this study, predictive design as a correlational research design was used. Randomly selected 407 eight-grade students who were from the central districts of a city in the central region of Turkey participated in…

  5. Predicting the Risk of Attrition for Undergraduate Students with Time Based Modelling

    Science.gov (United States)

    Chai, Kevin E. K.; Gibson, David

    2015-01-01

    Improving student retention is an important and challenging problem for universities. This paper reports on the development of a student attrition model for predicting which first year students are most at-risk of leaving at various points in time during their first semester of study. The objective of developing such a model is to assist…

  6. Predicting Successful Completion Using Student Delay Indicators in Undergraduate Self-Paced Online Courses

    Science.gov (United States)

    Lim, Janine M.

    2016-01-01

    Self-paced online courses meet flexibility and learning needs of many students, but skepticism persists regarding the quality and the tendency for students to procrastinate in self-paced courses. Research is needed to understand procrastination and delay patterns of students in online self-paced courses to predict successful completion and…

  7. Getting the Most out of Audience Response Systems: Predicting Student Reactions

    Science.gov (United States)

    Trew, Jennifer L.; Nelsen, Jacqueline L.

    2012-01-01

    Audience response systems (ARS) are effective tools for improving learning outcomes and student engagement in large undergraduate classes. However, if students do not accept ARS and do not find them to be useful, ARS may be less effective. Predicting and improving student perceptions of ARS may help to ensure positive outcomes. The present study…

  8. Using intervention-oriented evaluation to diagnose and correct students' persistent climate change misconceptions: A Singapore case study.

    Science.gov (United States)

    Pascua, Liberty; Chang, Chew-Hung

    2015-10-01

    The evaluation of classroom-based educational interventions is fraught with tensions, the most critical of which is choosing between focusing the inquiry on measuring the effects of treatment or in proximately utilizing the data to improve practice. This paper attempted to achieve both goals through the use of intervention-oriented evaluation of a professional development program intended to diagnose and correct students' misconceptions of climate change. Data was gathered, monitored and analyzed in three stages of a time-series design: the baseline, treatment and follow-up stages. The evaluation itself was the 'intervention' such that the data was allowed to 'contaminate' the treatment. This was achieved through giving the teacher unimpeded access to the collected information and to introduce midcourse corrections as she saw fit to her instruction. Results showed a significant development in students' conceptual understanding only after the teacher's decision to use direct and explicit refutation of misconceptions. Due to the accessibility of feedback, it was possible to locate specifically at which point in the process that the intervention was most effective. The efficacy of the intervention was then measured through comparing the scores across the three research stages. The inclusion of a comparison group to the design is recommended for future studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. No Exit: Predicting Student Persistence. AIR 1990 Annual Forum Paper.

    Science.gov (United States)

    Beil, Cheryl; Shope, Janet H.

    A longitudinal study was conducted to determine the factors influencing college student persistence in remaining in school. Persistence was examined at two points: after the first year and 4 years after enrollment. The study was conducted at an urban university using the American College Testing's Entering Student Survey and Student Opinion…

  10. Students' Metacomprehension Knowledge: Components That Predict Comprehension Performance

    Science.gov (United States)

    Zabrucky, Karen M.; Moore, DeWayne; Agler, Lin-Miao Lin; Cummings, Andrea M.

    2015-01-01

    In the present study, we assessed students' metacomprehension knowledge and examined the components of knowledge most related to comprehension of expository texts. We used the Revised Metacomprehension Scale (RMCS) to investigate the relations between students' metacomprehension knowledge and comprehension performance. Students who evaluated and…

  11. Digital Game's Impacts on Students' Learning Effectiveness of Correct Medication

    Science.gov (United States)

    Shiue, Ya-Ming; Hsu, Yu-Chiung

    2017-01-01

    In recent years, considerable concern has arisen over the use of digital games as instructional tools in educational research. However, game-based learning not only enhances students' learning motivation and effectiveness, but also fosters knowledge transfer. Taiwanese people living in rural areas often receive health-related information through…

  12. Students-as-Customers' Satisfaction, Predictive Retention with Marketing Implications: The Case of Malaysian Higher Education Business Students

    Science.gov (United States)

    Carter, Stephen; Yeo, Amy Chu-May

    2016-01-01

    Purpose: The purpose of this paper is to investigate two areas of interest: first, to determine business student customer satisfiers that could be contributors to students' current and predicted retention in a higher educational institution (HEI) and second, to use these satisfiers to inform HEI marketing planning. Design/Methodology/Approach: The…

  13. A Predictive Study of Student Satisfaction in Online Education Programs

    Directory of Open Access Journals (Sweden)

    Yu-Chun Kuo

    2013-03-01

    Full Text Available This paper is intended to investigate the degree to which interaction and other predictors contribute to student satisfaction in online learning settings. This was a preliminary study towards a dissertation work which involved the establishment of interaction and satisfaction scales through a content validity survey. Regression analysis was performed to determine the contribution of predictor variables to student satisfaction. The effects of student background variables on predictors were explored. The results showed that learner-instructor interaction, learner-content interaction, and Internet self-efficacy were good predictors of student satisfaction while interactions among students and self-regulated learning did not contribute to student satisfaction. Learner-content interaction explained the largest unique variance in student satisfaction. Additionally, gender, class level, and time spent online per week seemed to have influence on learner-learner interaction, Internet self-efficacy, and self-regulation.

  14. Robust Inference of Population Structure for Ancestry Prediction and Correction of Stratification in the Presence of Relatedness

    Science.gov (United States)

    Conomos, Matthew P.; Miller, Mike; Thornton, Timothy

    2016-01-01

    Population structure inference with genetic data has been motivated by a variety of applications in population genetics and genetic association studies. Several approaches have been proposed for the identification of genetic ancestry differences in samples where study participants are assumed to be unrelated, including principal components analysis (PCA), multi-dimensional scaling (MDS), and model-based methods for proportional ancestry estimation. Many genetic studies, however, include individuals with some degree of relatedness, and existing methods for inferring genetic ancestry fail in related samples. We present a method, PC-AiR, for robust population structure inference in the presence of known or cryptic relatedness. PC-AiR utilizes genome-screen data and an efficient algorithm to identify a diverse subset of unrelated individuals that is representative of all ancestries in the sample. The PC-AiR method directly performs PCA on the identified ancestry representative subset and then predicts components of variation for all remaining individuals based on genetic similarities. In simulation studies and in applications to real data from Phase III of the HapMap Project, we demonstrate that PC-AiR provides a substantial improvement over existing approaches for population structure inference in related samples. We also demonstrate significant efficiency gains, where a single axis of variation from PC-AiR provides better prediction of ancestry in a variety of structure settings than using ten (or more) components of variation from widely used PCA and MDS approaches. Finally, we illustrate that PC-AiR can provide improved population stratification correction over existing methods in genetic association studies with population structure and relatedness. PMID:25810074

  15. Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density

    Science.gov (United States)

    Nooruddin, Hasan A.; Anifowose, Fatai; Abdulraheem, Abdulazeez

    2014-03-01

    Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results.

  16. Three-dimensional transport coefficient model and prediction-correction numerical method for thermal margin analysis of PWR cores

    International Nuclear Information System (INIS)

    Chiu, C.

    1981-01-01

    Combustion Engineering Inc. designs its modern PWR reactor cores using open-core thermal-hydraulic methods where the mass, momentum and energy equations are solved in three dimensions (one axial and two lateral directions). The resultant fluid properties are used to compute the minimum Departure from Nuclear Boiling Ratio (DNBR) which ultimately sets the power capability of the core. The on-line digital monitoring and protection systems require a small fast-running algorithm of the design code. This paper presents two techniques used in the development of the on-line DNB algorithm. First, a three-dimensional transport coefficient model is introduced to radially group the flow subchannel into channels for the thermal-hydraulic fluid properties calculation. Conservation equations of mass, momentum and energy for this channels are derived using transport coefficients to modify the calculation of the radial transport of enthalpy and momentum. Second, a simplified, non-iterative numerical method, called the prediction-correction method, is applied together with the transport coefficient model to reduce the computer execution time in the determination of fluid properties. Comparison of the algorithm and the design thermal-hydraulic code shows agreement to within 0.65% equivalent power at a 95/95 confidence/probability level for all normal operating conditions of the PWR core. This algorithm accuracy is achieved with 1/800th of the computer processing time of its parent design code. (orig.)

  17. Predicting Alcohol Misuse Among College Students in the US and South Korea.

    Science.gov (United States)

    Kim, Sang-Yeon; Ahn, Seokhoon; Lim, Tae-Seop

    2015-01-01

    This study examines contributing factors of alcohol misuse among college students in South Korea and the U.S. Exploratory factor analyses (EFA) on measurements of alcohol expectancy, alcohol efficacy, and accommodation resulted in social and personal causes for alcohol misuse. Social causes alone predicted alcohol misuse for both countries. Social factors constituted a much stronger predictor of alcohol misuse among South Korean students than among American students. Practical implications for effective deterrence of student binge drinking are discussed.

  18. On predicting student performance using low-rank matrix factorization techniques

    DEFF Research Database (Denmark)

    Lorenzen, Stephan Sloth; Pham, Dang Ninh; Alstrup, Stephen

    2017-01-01

    Predicting the score of a student is one of the important problems in educational data mining. The scores given by an individual student reflect how a student understands and applies the knowledge conveyed in class. A reliable performance prediction enables teachers to identify weak students...... that require remedial support, generate adaptive hints, and improve the learning of students. This work focuses on predicting the score of students in the quiz system of the Clio Online learning platform, the largest Danish supplier of online learning materials, covering 90% of Danish elementary schools...... and the current version of the data set is very sparse, the very low-rank approximation can capture enough information. This means that the simple baseline approach achieves similar performance compared to other advanced methods. In future work, we will restrict the quiz data set, e.g. only including quizzes...

  19. Specific attitudes which predict psychology students' intentions to seek help for psychological distress.

    Science.gov (United States)

    Thomas, Susan J; Caputi, Peter; Wilson, Coralie J

    2014-03-01

    Although many postgraduate psychology programs address students' mental health, there are compelling indications that earlier, undergraduate, interventions may be optimal. We investigated specific attitudes that predict students' intentions to seek treatment for psychological distress to inform targeted interventions. Psychology students (N = 289; mean age = 19.75 years) were surveyed about attitudes and intentions to seek treatment for stress, anxiety, or depression. Less than one quarter of students reported that they would be likely to seek treatment should they develop psychological distress. Attitudes that predicted help-seeking intentions related to recognition of symptoms and the benefits of professional help, and openness to treatment for emotional problems. The current study identified specific attitudes which predict help-seeking intentions in psychology students. These attitudes could be strengthened in undergraduate educational interventions promoting well-being and appropriate treatment uptake among psychology students. © 2013 Wiley Periodicals, Inc.

  20. Z-LASIK and Trans-PRK for correction of high-grade myopia: safety, efficacy, predictability and clinical outcomes.

    Science.gov (United States)

    Gershoni, Assaf; Mimouni, Michael; Livny, Eitan; Bahar, Irit

    2018-03-12

    The aim of the study was to examine the outcomes of transepithelial photorefractive keratectomy (Trans-PRK) and Femtosecond Laser-assisted in situ keratomileusis (Z-LASIK) for the correction of high myopia. A retrospective cohort study design was used. The study group included 792 eyes with high-grade myopia (- 6.0 diopters or higher) or high-grade myopia with astigmatism that were treated with Z-LASIK or Trans-PRK in 2013 through 2014 in an optical outpatient clinic of a large private medical service. The Trans-PRK group comprised of 674 eyes with a spherical equivalent (SE) of - 7.87 ± 1.46 and the Z-LASIK group comprised of 118 eyes with a SE of - 7.19 ± 0.81 (P PRK group was - 0.06 and - 0.02 in the Z-LASIK group (P = 0.545). Efficacy index values were 0.92 in the Trans-PRK group and 0.95 in the Z-LASIK group (P = 0.083), and corresponding safety index values were 0.95 and 0.97 (P = 0.056). An UCVA of 20/40 or better was achieved in 94.20% of eyes in the Trans-PRK group, and 98.31% in the Z-LASIK group (P = 0.063). The majority of eyes in both the Trans-PRK and Z-LASIK groups were within ± 0.5D of attempted correction: 59.35 and 64.71%, respectively (P = 0.271). Both Trans-PRK and Z-LASIK demonstrated excellent efficacy, safety and predictability profiles, with results comparable and in some cases superior to the current literature. Results of Z-LASIK were slightly better than those of Trans-PRK, though the preoperative SE of the latter was higher.

  1. Predicting Student Success from Non-Cognitive Variables.

    Science.gov (United States)

    Blumberg, Phyllis

    In order to identify the relationship among social support networks, depression, life events, and student progress in medical school, 96 students completed a questionnaire. The results indicated good social support, a high number of recent life events, slight depression and a continuum of not quite passing to doing extremely well in medical…

  2. Designing a Predictive Model of Student Satisfaction in Online Learning

    Science.gov (United States)

    Parahoo, Sanjai K; Santally, Mohammad Issack; Rajabalee, Yousra; Harvey, Heather Lea

    2016-01-01

    Higher education institutions consider student satisfaction to be one of the major elements in determining the quality of their programs. The objective of the study was to develop a model of student satisfaction to identify the influencers that emerged in online higher education settings. The study adopted a mixed method approach to identify…

  3. Improving Student Success Using Predictive Models and Data Visualisations

    Science.gov (United States)

    Essa, Alfred; Ayad, Hanan

    2012-01-01

    The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50-60%. At the college level in the US only 30% of students graduate from…

  4. Predicting College Student Success: A Historical and Predictive Examination of High School Activities and Accomplishments

    Science.gov (United States)

    Davey, Carla Mae

    2010-01-01

    According to generational theorists, the interests and experiences of incoming students have fluctuated over time, with Millennial students being more engaged and accomplished than their predecessors. This project explored data from 1974-2007 to determine the actual trends in engagement and accomplishments for three generations of students. Over…

  5. [Study on correction of data bias caused by different missing mechanisms in survey of medical expenditure among students enrolling in Urban Resident Basic Medical Insurance].

    Science.gov (United States)

    Zhang, Haixia; Zhao, Junkang; Gu, Caijiao; Cui, Yan; Rong, Huiying; Meng, Fanlong; Wang, Tong

    2015-05-01

    The study of the medical expenditure and its influencing factors among the students enrolling in Urban Resident Basic Medical Insurance (URBMI) in Taiyuan indicated that non response bias and selection bias coexist in dependent variable of the survey data. Unlike previous studies only focused on one missing mechanism, a two-stage method to deal with two missing mechanisms simultaneously was suggested in this study, combining multiple imputation with sample selection model. A total of 1 190 questionnaires were returned by the students (or their parents) selected in child care settings, schools and universities in Taiyuan by stratified cluster random sampling in 2012. In the returned questionnaires, 2.52% existed not missing at random (NMAR) of dependent variable and 7.14% existed missing at random (MAR) of dependent variable. First, multiple imputation was conducted for MAR by using completed data, then sample selection model was used to correct NMAR in multiple imputation, and a multi influencing factor analysis model was established. Based on 1 000 times resampling, the best scheme of filling the random missing values is the predictive mean matching (PMM) method under the missing proportion. With this optimal scheme, a two stage survey was conducted. Finally, it was found that the influencing factors on annual medical expenditure among the students enrolling in URBMI in Taiyuan included population group, annual household gross income, affordability of medical insurance expenditure, chronic disease, seeking medical care in hospital, seeking medical care in community health center or private clinic, hospitalization, hospitalization canceled due to certain reason, self medication and acceptable proportion of self-paid medical expenditure. The two-stage method combining multiple imputation with sample selection model can deal with non response bias and selection bias effectively in dependent variable of the survey data.

  6. Predicting erectile dysfunction following surgical correction of Peyronie's disease without inflatable penile prosthesis placement: vascular assessment and preoperative risk factors.

    Science.gov (United States)

    Taylor, Frederick L; Abern, Michael R; Levine, Laurence A

    2012-01-01

    Surgical therapy remains the gold standard treatment for Peyronie's Disease (PD). Surgical options include plication, grafting, and placement of inflatable penile prosthesis (IPP). Postoperative erectile dysfunction (ED) is a potential complication for PD surgery without IPP. We present our large series follow-up to evaluate preoperative risk factors for postoperative ED. The aim of this study is to evaluate preoperative risk factors for the development of ED following surgical correction of PD taking into account the degree of curvature, graft size, surgical approach, hypertension, hyperlipidemia, diabetes, smoking history, preoperative use of phosphodiesterase 5 inhibitors (PDE5), and preoperative duplex ultrasound findings including peak systolic and end diastolic velocities and resistive index. We identified 218 men undergoing either tunica albuginea plication (TAP) or partial plaque excision with pericardial grafting for PD following a previously published algorithm between November 1992 and April 2007. Preoperative and postoperative erectile function, curvature characteristics, presence of vascular risk factors, and duplex ultrasound findings were available on 109 patients. Our primary outcome measure is the development of ED after surgery for PD. Ten percent of TAP and 21% of plaque excision with grafting patients developed postoperative ED. Neither curve direction (P = 0.76), graft area (P = 0.78), surgical approach (P = 0.12), chronic hypertension (P = 0.51), hyperlipidemia (P = 0.87), diabetes (P = 0.69), nor smoking history (P = 0.99) were significant predictors of postoperative ED. No combination of risk factors was found to be predictive of postoperative ED. Preoperative use of PDE5 was not a significant predictor of postoperative ED (P = 0.33). Neither peak systolic, end diastolic, nor resistive index were significant predictors of ED (P = 0.28, 0.28, and 0.25, respectively). This long-term follow-up of a large published series suggests that neither

  7. How learning analytics can early predict under-achieving students in a blended medical education course.

    Science.gov (United States)

    Saqr, Mohammed; Fors, Uno; Tedre, Matti

    2017-07-01

    Learning analytics (LA) is an emerging discipline that aims at analyzing students' online data in order to improve the learning process and optimize learning environments. It has yet un-explored potential in the field of medical education, which can be particularly helpful in the early prediction and identification of under-achieving students. The aim of this study was to identify quantitative markers collected from students' online activities that may correlate with students' final performance and to investigate the possibility of predicting the potential risk of a student failing or dropping out of a course. This study included 133 students enrolled in a blended medical course where they were free to use the learning management system at their will. We extracted their online activity data using database queries and Moodle plugins. Data included logins, views, forums, time, formative assessment, and communications at different points of time. Five engagement indicators were also calculated which would reflect self-regulation and engagement. Students who scored below 5% over the passing mark were considered to be potentially at risk of under-achieving. At the end of the course, we were able to predict the final grade with 63.5% accuracy, and identify 53.9% of at-risk students. Using a binary logistic model improved prediction to 80.8%. Using data recorded until the mid-course, prediction accuracy was 42.3%. The most important predictors were factors reflecting engagement of the students and the consistency of using the online resources. The analysis of students' online activities in a blended medical education course by means of LA techniques can help early predict underachieving students, and can be used as an early warning sign for timely intervention.

  8. Improving students' meaningful learning on the predictive nature of quantum mechanics

    Directory of Open Access Journals (Sweden)

    Rodolfo Alves de Carvalho Neto

    2009-03-01

    Full Text Available This paper deals with research about teaching quantum mechanics to 3rd year high school students and their meaningful learning of its predictive aspect; it is based on the Master’s dissertation of one of the authors (CARVALHO NETO, 2006. While teaching quantum mechanics, we emphasized its predictive and essentially probabilistic nature, based on Niels Bohr’s complementarity interpretation (BOHR, 1958. In this context, we have discussed the possibility of predicting measurement results in well-defined experimental contexts, even for individual events. Interviews with students reveal that they have used quantum mechanical ideas, suggesting their meaningful learning of the essentially probabilistic predictions of quantum mechanics.

  9. Predicting multicultural effectiveness of international students : the Multicultural Personality Questionnaire

    NARCIS (Netherlands)

    Van Oudenhoven, J.P.; Van der Zee, K.I.

    The present study considered the reliability and validity of the 78-item revised version of the Multicultural Personality Questionnaire, a multidimensional instrument aimed at measuring multicultural effectiveness of expatriate employees and students. The questionnaire includes scales for cultural

  10. Predicting multicultural effectiveness of international students : The Multicultural Personality Questionnaire

    NARCIS (Netherlands)

    Van Oudenhoven, Jan Pieter; Van der Zee, K.I.

    2002-01-01

    The present study considered the reliability and validity of the 78-item revised version of the Multicultural Personality Questionnaire, a multidimensional instrument aimed at measuring multicultural effectiveness of expatriate employees and students. The questionnaire includes scales for cultural

  11. Effect of heart rate correction on pre- and post-exercise heart rate variability to predict risk of mortality – an experimental study on the FINCAVAS cohort

    Directory of Open Access Journals (Sweden)

    Paruthi ePradhapan

    2014-06-01

    Full Text Available The non-linear inverse relationship between RR-intervals and heart rate (HR contributes significantly to the heart rate variability (HRV parameters and their performance in mortality prediction. To determine the level of influence HR exerts over HRV parameters’ prognostic power, we studied the predictive performance for different HR levels by applying eight correction procedures, multiplying or dividing HRV parameters by the mean RR-interval (RRavg to the power 0.5-16. Data collected from 1288 patients in The Finnish Cardiovascular Study (FINCAVAS, who satisfied the inclusion criteria, was used for the analyses. HRV parameters (RMSSD, VLF Power and LF Power were calculated from 2-minute segment in the rest phase before exercise and 2-minute recovery period immediately after peak exercise. Area under the receiver operating characteristic curve (AUC was used to determine the predictive performance for each parameter with and without HR corrections in rest and recovery phases. The division of HRV parameters by segment’s RRavg to the power 2 (HRVDIV-2 showed the highest predictive performance under the rest phase (RMSSD: 0.67/0.66; VLF Power: 0.70/0.62; LF Power: 0.79/0.65; cardiac mortality/non-cardiac mortality with minimum correlation to HR (r = -0.15 to 0.15. In the recovery phase, Kaplan-Meier (KM survival analysis revealed good risk stratification capacity at HRVDIV-2 in both groups (cardiac and non-cardiac mortality. Although higher powers of correction (HRVDIV-4 and HRVDIV-8 improved predictive performance during recovery, they induced an increased positive correlation to HR. Thus, we inferred that predictive capacity of HRV during rest and recovery is augmented when its dependence on HR is weakened by applying appropriate correction procedures.

  12. Seeing Eye to Eye: Predicting Teacher-Student Agreement on Classroom Social Networks

    Science.gov (United States)

    Neal, Jennifer Watling; Cappella, Elise; Wagner, Caroline; Atkins, Marc S.

    2010-01-01

    This study examines the association between classroom characteristics and teacher-student agreement in perceptions of students’ classroom peer networks. Social network, peer nomination, and observational data were collected from a sample of second through fourth grade teachers (N=33) and students (N=669) in 33 classrooms across five high poverty urban schools. Results demonstrate that variation in teacher-student agreement on the structure of students’ peer networks can be explained, in part, by developmental factors and classroom characteristics. Developmental increases in network density partially mediated the positive relationship between grade level and teacher-student agreement. Larger class sizes and higher levels of normative aggressive behavior resulted in lower levels of teacher-student agreement. Teachers’ levels of classroom organization had mixed influences, with behavior management negatively predicting agreement, and productivity positively predicting agreement. These results underscore the importance of the classroom context in shaping teacher and student perceptions of peer networks. PMID:21666768

  13. Mental health predicts better academic outcomes: a longitudinal study of elementary school students in Chile.

    Science.gov (United States)

    Murphy, J Michael; Guzmán, Javier; McCarthy, Alyssa E; Squicciarini, Ana María; George, Myriam; Canenguez, Katia M; Dunn, Erin C; Baer, Lee; Simonsohn, Ariela; Smoller, Jordan W; Jellinek, Michael S

    2015-04-01

    The world's largest school-based mental health program, Habilidades para la Vida [Skills for Life (SFL)], has been operating on a national scale in Chile for 15 years. SFL's activities include using standardized measures to screen elementary school students and providing preventive workshops to students at risk for mental health problems. This paper used SFL's data on 37,397 students who were in first grade in 2009 and third grade in 2011 to ascertain whether first grade mental health predicted subsequent academic achievement and whether remission of mental health problems predicted improved academic outcomes. Results showed that mental health was a significant predictor of future academic performance and that, overall, students whose mental health improved between first and third grade made better academic progress than students whose mental health did not improve or worsened. Our findings suggest that school-based mental health programs like SFL may help improve students' academic outcomes.

  14. Effects of energy drink consumption on corrected QT interval and heart rate variability in young obese Saudi male university students.

    Science.gov (United States)

    Alsunni, Ahmed; Majeed, Farrukh; Yar, Talay; AlRahim, Ahmed; Alhawaj, Ali Fouad; Alzaki, Muneer

    2015-01-01

    Consumption of energy drinks has adverse effects on the heart that might be potentiated in obese individuals. Since the incidence of obesity and use of energy drinks is high among Saudi youth, we used non-invasive tests to study hemodynamic changes produced by altered autonomic cardiac activ.ity following consumption of energy drinks in obese male students. This cross-sectional study was carried out at Department of Physiology, College of Medicine, University of Dammam, Saudi Arabia, over a one-year period from December 2013 to December 2014. In Saudi male university students we measured continuous ECG recordings and a one-minute deep breathing maneuver to measure the expiratory-to-inspiratory ratio, the mean heart rate range (MHRR), the mean percentage variability. (M%VHR) and the corrected QT interval (QTc) at 0, 30 and 60 minutes after consumption of energy drink. We enrolled 31 students (18 overweight/obese and 13 normal weights. QTc was significantly in.creased at 60 min as compared with the resting state in overweight/obese subjects (P=.006). Heart rate variability was significantly less in obese as compared with normal weight subjects at 60 minutes as indicated by E:I ratio, (P=.037), MHRR (P=.012), M%VHR (P=.040) after energy drink consumption. Significant increases in diastolic (P=.020) and mean arterial blood pressure (P=.024) were observed at 30 minutes in the obese group. Hemodynamic changes after intake of energy drinks in obese subjects indicate that obesity and energy drinks could synergistically induce harmful effects. This finding warrants efforts to caution the obese on intake of energy drinks and timely intervention to motivate changes in lifestyle.

  15. A 3D correction method for predicting the readings of a PinPoint chamber on the CyberKnife® M6™ machine

    Science.gov (United States)

    Zhang, Yongqian; Brandner, Edward; Ozhasoglu, Cihat; Lalonde, Ron; Heron, Dwight E.; Saiful Huq, M.

    2018-02-01

    The use of small fields in radiation therapy techniques has increased substantially in particular in stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT). However, as field size reduces further still, the response of the detector changes more rapidly with field size, and the effects of measurement uncertainties become increasingly significant due to the lack of lateral charged particle equilibrium, spectral changes as a function of field size, detector choice, and subsequent perturbations of the charged particle fluence. This work presents a novel 3D dose volume-to-point correction method to predict the readings of a 0.015 cc PinPoint chamber (PTW 31014) for both small static-fields and composite-field dosimetry formed by fixed cones on the CyberKnife® M6™ machine. A 3D correction matrix is introduced to link the 3D dose distribution to the response of the PinPoint chamber in water. The parameters of the correction matrix are determined by modeling its 3D dose response in circular fields created using the 12 fixed cones (5 mm-60 mm) on a CyberKnife® M6™ machine. A penalized least-square optimization problem is defined by fitting the calculated detector reading to the experimental measurement data to generate the optimal correction matrix; the simulated annealing algorithm is used to solve the inverse optimization problem. All the experimental measurements are acquired for every 2 mm chamber shift in the horizontal planes for each field size. The 3D dose distributions for the measurements are calculated using the Monte Carlo calculation with the MultiPlan® treatment planning system (Accuray Inc., Sunnyvale, CA, USA). The performance evaluation of the 3D conversion matrix is carried out by comparing the predictions of the output factors (OFs), off-axis ratios (OARs) and percentage depth dose (PDD) data to the experimental measurement data. The discrepancy of the measurement and the prediction data for composite fields is also

  16. Predictive validity of the comprehensive basic science examination mean score for assessment of medical students' performance

    Directory of Open Access Journals (Sweden)

    Firouz Behboudi

    2002-04-01

    Full Text Available Background Medical education curriculum improvements can be achieved bye valuating students performance. Medical students have to pass two undergraduate comprehensive examinations, basic science and preinternship, in Iran. Purpose To measure validity of the students' mean score in comprehensive basic science exam (CBSE for predicting their performance in later curriculum phases. Methods This descriptive cross-sectional study was conducted on 95 (38 women and 55 men Guilan medical university students. Their admission to the university was 81% by regional quota and 12% by shaheed and other organizations' share. They first enrolled in 1994 and were able to pass CBS£ at first try. Data on gender, regional quota, and average grades of CBS£, PC, and CPIE were collected by a questionnaire. The calculations were done by SPSS package. Results The correlation coefficient between CBS£ and CPIE mean scores (0.65 was higher than correlation coefficient between CBS£ and PC mean scores (0.49. The predictive validity of CBS£ average grade was significant for students' performance in CPIE; however, the predictive validity of CBSE mean scores for students I pe1jormance in PC was lower. Conclusion he students' mean score in CBSE can be a good denominator for their further admission. We recommend further research to assess the predictive validity for each one of the basic courses. Keywords predictive validity, comprehensive basic exam

  17. Beyond Engagement Analytics: Which Online Mixed-Data Factors Predict Student Learning Outcomes?

    Science.gov (United States)

    Strang, Kenneth David

    2017-01-01

    This mixed-method study focuses on online learning analytics, a research area of importance. Several important student attributes and their online activities are examined to identify what seems to work best to predict higher grades. The purpose is to explore the relationships between student grade and key learning engagement factors using a large…

  18. Predicting Pre-Service Teachers' Intention of Implementing Peer Assessment for Low-Achieving Students

    Science.gov (United States)

    Yim, Su Yon; Cho, Young Hoan

    2016-01-01

    Despite the benefits of peer assessment, many teachers are not willing to implement it, particularly for low-achieving students. This study used the theory of planned behaviour to predict pre-service teachers' intention to use peer assessment for low-achieving students. A total of 229 pre-service teachers in Singapore participated in the survey…

  19. The Role of Goal Importance in Predicting University Students' High Academic Performance

    Science.gov (United States)

    Kyle, Vanessa A.; White, Katherine M.; Hyde, Melissa K.; Occhipinti, Stefano

    2014-01-01

    We examined goal importance, focusing on high, but not exclusive priority goals, in the theory of planned behaviour (TPB) to predict students' academic performance. At the beginning of semester, students in a psychology subject (N = 197) completed TPB and goal importance items for achieving a high grade. Regression analyses revealed partial…

  20. A "Uses and Gratification Expectancy Model" to Predict Students' "Perceived e-Learning Experience"

    Science.gov (United States)

    Mondi, Makingu; Woods, Peter; Rafi, Ahmad

    2008-01-01

    This study investigates "how and why" students' "Uses and Gratification Expectancy" (UGE) for e-learning resources influences their "Perceived e-Learning Experience." A "Uses and Gratification Expectancy Model" (UGEM) framework is proposed to predict students' "Perceived e-Learning Experience," and…

  1. The Predictive Validity of CBM Writing Indices for Eighth-Grade Students

    Science.gov (United States)

    Amato, Janelle M.; Watkins, Marley W.

    2011-01-01

    Curriculum-based measurement (CBM) is an alternative to traditional assessment techniques. Technical work has begun to identify CBM writing indices that are psychometrically sound for monitoring older students' writing proficiency. This study examined the predictive validity of CBM writing indices in a sample of 447 eighth-grade students.…

  2. The Role of Life Satisfaction and Parenting Styles in Predicting Delinquent Behaviors among High School Students

    Science.gov (United States)

    Onder, Fulya Cenkseven; Yilmaz, Yasin

    2012-01-01

    The purpose of this study is to determine whether the parenting styles and life satisfaction predict delinquent behaviors frequently or not. Firstly the data were collected from 471 girls and 410 boys, a total of 881 high school students. Then the research was carried out with 502 students showing low (n = 262, 52.2%) and high level of delinquent…

  3. Do Materialism, Intrinsic Aspirations, and Meaning in Life Predict Students' Meanings of Education?

    Science.gov (United States)

    Henderson-King, Donna; Mitchell, Amanda M.

    2011-01-01

    Though there is a deep literature on factors that predict college attendance and on the effects of college attendance on students' development, there has been little research on what education actually means to students themselves. This study was conducted to examine whether materialism, intrinsic aspirations, and the search for meaning in life…

  4. A Parsimonious Instrument for Predicting Students' Intent to Pursue a Sales Career: Scale Development and Validation

    Science.gov (United States)

    Peltier, James W.; Cummins, Shannon; Pomirleanu, Nadia; Cross, James; Simon, Rob

    2014-01-01

    Students' desire and intention to pursue a career in sales continue to lag behind industry demand for sales professionals. This article develops and validates a reliable and parsimonious scale for measuring and predicting student intention to pursue a selling career. The instrument advances previous scales in three ways. The instrument is…

  5. Noncognitive Variables to Predict Academic Success among Junior Year Baccalaureate Nursing Students

    Science.gov (United States)

    Smith, Ellen M. T.

    2017-01-01

    An equitable predictor of academic success is needed as nursing education strives toward comprehensive preparation of diverse nursing students. The purpose of this study was to discover how Sedlacek's (2004a) Noncognitive Questionnaire (NCQ) and Duckworth & Quinn's (2009) Grit-S predicted baccalaureate nursing student academic performance and…

  6. Using Hierarchical Linear Modelling to Examine Factors Predicting English Language Students' Reading Achievement

    Science.gov (United States)

    Fung, Karen; ElAtia, Samira

    2015-01-01

    Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…

  7. Developing a Model and Applications for Probabilities of Student Success: A Case Study of Predictive Analytics

    Science.gov (United States)

    Calvert, Carol Elaine

    2014-01-01

    This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at…

  8. Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

    Science.gov (United States)

    Lee, Diane Sookyoung; Padilla, Amado M.

    2016-01-01

    This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

  9. Predicting Binge Drinking in College Students: Rational Beliefs, Stress, or Loneliness?

    Science.gov (United States)

    Chen, Yixin; Feeley, Thomas Hugh

    2015-01-01

    We proposed a conceptual model to predict binge-drinking behavior among college students, based on the theory of planned behavior and the stress-coping hypothesis. A two-wave online survey was conducted with predictors and drinking behavior measured separately over 2 weeks' time. In the Wave 1 survey, 279 students at a public university in the…

  10. Predicting College Students' Intention to Graduate: A Test of the Theory of Planned Behavior

    Science.gov (United States)

    Sutter, Nate; Paulson, Sharon

    2016-01-01

    The current study examined whether it is possible to increase college students' intention to earn a four-year degree with the Theory of Planned Behavior (TPB). Three research questions were examined: (1) Can the TPB predict traditional undergraduates' graduation intention? (2) Does graduation intention differ by traditional students' year of…

  11. The Role of Basic Needs Fulfillment in Prediction of Subjective Well-Being among University Students

    Science.gov (United States)

    Turkdogan, Turgut; Duru, Erdinc

    2012-01-01

    The aim of this study is to examine the role of fulfillment level of university students' basic needs in predicting the level of their subjective well being. The participants were 627 students (56% female, 44% male) attending different faculties of Pamukkale University. In this study, subjective well being was measured with Life Satisfaction Scale…

  12. A Comparison of Logistic Regression, Neural Networks, and Classification Trees Predicting Success of Actuarial Students

    Science.gov (United States)

    Schumacher, Phyllis; Olinsky, Alan; Quinn, John; Smith, Richard

    2010-01-01

    The authors extended previous research by 2 of the authors who conducted a study designed to predict the successful completion of students enrolled in an actuarial program. They used logistic regression to determine the probability of an actuarial student graduating in the major or dropping out. They compared the results of this study with those…

  13. Collegiate Student-Athletes' Academic Success: Academic Communication Apprehension's Impact on Prediction Models

    Science.gov (United States)

    James, Kai'Iah A.

    2010-01-01

    This dissertation study examines the impact of traditional and non-cognitive variables on the academic prediction model for a sample of collegiate student-athletes. Three hundred and fifty-nine NCAA Division IA male and female student-athletes, representing 13 sports, including football and Men's and Women's Basketball provided demographic…

  14. Engagement vs Performance: Using Electronic Portfolios to Predict First Semester Engineering Student Persistence

    Science.gov (United States)

    Aguiar, Everaldo; Ambrose, G. Alex; Chawla, Nitesh V.; Goodrich, Victoria; Brockman, Jay

    2014-01-01

    As providers of higher education begin to harness the power of big data analytics, one very fitting application for these new techniques is that of predicting student attrition. The ability to pinpoint students who might soon decide to drop out, or who may be following a suboptimal path to success, allows those in charge not only to understand the…

  15. Specific Disgust Sensitivities Differentially Predict Interest in Careers of Varying Procedural-Intensity among Medical Students

    Science.gov (United States)

    Consedine, Nathan S.; Windsor, John A.

    2014-01-01

    Mismatches between the needs of public health systems and student interests have led to renewed study on the factors predicting career specializations among medical students. While most work examines career and lifestyle values, emotional proclivities may be important; disgust sensitivity may help explain preferences for careers with greater and…

  16. Factors That Predict Marijuana Use and Grade Point Average among Undergraduate College Students

    Science.gov (United States)

    Coco, Marlena B.

    2017-01-01

    The purpose of this study was to analyze factors that predict marijuana use and grade point average among undergraduate college students using the Core Institute national database. The Core Alcohol and Drug Survey was used to collect data on students' attitudes, beliefs, and experiences related to substance use in college. The sample used in this…

  17. Predicting Success: How Predictive Analytics Are Transforming Student Support and Success Programs

    Science.gov (United States)

    Boerner, Heather

    2015-01-01

    Every year, Lone Star College in Texas hosts a "Men of Honor" program to provide assistance and programming to male students, but particularly those who are Hispanic and black, in hopes their academic performance will improve. Lone Star might have kept directing its limited resources toward these students--and totally missed the subset…

  18. Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students

    Directory of Open Access Journals (Sweden)

    Mahbobeh Faramarzi

    2017-01-01

    Full Text Available Objective. Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design. In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20, College Academic Self-Efficacy Scale (CASES, and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ. Results. Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students (B=-0.512, P<0.001. The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother’s education, father’s education, and doctoral level did not accurately predict alexithymia in college students. Conclusion. As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities.

  19. Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students

    Science.gov (United States)

    2017-01-01

    Objective. Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design. In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results. Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students (B = −0.512, P students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion. As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities. PMID:28154839

  20. Discrimination-Aware Classifiers for Student Performance Prediction

    Science.gov (United States)

    Luo, Ling; Koprinska, Irena; Liu, Wei

    2015-01-01

    In this paper we consider discrimination-aware classification of educational data. Mining and using rules that distinguish groups of students based on sensitive attributes such as gender and nationality may lead to discrimination. It is desirable to keep the sensitive attributes during the training of a classifier to avoid information loss but…

  1. A Decision Support System for Predicting Students' Performance

    Science.gov (United States)

    Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis

    2016-01-01

    Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…

  2. Entitlement Attitudes Predict Students' Poor Performance in Challenging Academic Conditions

    Science.gov (United States)

    Anderson, Donna; Halberstadt, Jamin; Aitken, Robert

    2013-01-01

    Excessive entitlement--an exaggerated or unrealistic belief about what one deserves--has been associated with a variety of maladaptive behaviors, including a decline in motivation and effort. In the context of tertiary education, we reasoned that if students expend less effort to obtain positive outcomes to which they feel entitled, this should…

  3. Internship Quality Predicts Career Exploration of High School Students

    Science.gov (United States)

    Gamboa, Vitor; Paixao, Maria Paula; Neves de Jesus, Saul

    2013-01-01

    The provision of workplace-based experiences (internship/placement) is an important component of the training program of students attending vocational education courses. Regarding the impact of such experiences on vocational development, research results are not conclusive enough, mainly, if we consider the theoretical expectation that work…

  4. Beyond Host Language Proficiency: Coping Resources Predicting International Students' Satisfaction

    Science.gov (United States)

    Mak, Anita S.; Bodycott, Peter; Ramburuth, Prem

    2015-01-01

    As international students navigate in a foreign educational environment, having higher levels of coping or stress-resistance resources--both internal and external--could be related to increased satisfaction with personal and university life. The internal coping resources examined in this study were host language proficiency, self-esteem,…

  5. Predicting Success for Actuarial Students in Undergraduate Mathematics Courses

    Science.gov (United States)

    Smith, Richard Manning; Schumacher, Phyllis A.

    2005-01-01

    A study of undergraduate actuarial graduates found that math SAT scores, verbal SAT scores, percentile rank in high school graduating class, and percentage score on a college mathematics placement exam had some relevance to forecasting the students' grade point averages in their major. For both males and females, percentile rank in high school…

  6. A Multilevel Latent Growth Curve Approach to Predicting Student Proficiency

    Science.gov (United States)

    Choi, Kilchan; Goldschmidt, Pete

    2012-01-01

    Value-added models and growth-based accountability aim to evaluate school's performance based on student growth in learning. The current focus is on linking the results from value-added models to the ones from growth-based accountability systems including Adequate Yearly Progress decisions mandated by No Child Left Behind. We present a new…

  7. The Role of Teachers' Support in Predicting Students' Motivation and Achievement Outcomes in Physical Education

    Science.gov (United States)

    Zhang, Tao; Solmon, Melinda A.; Gu, Xiangli

    2012-01-01

    Examining how teachers' beliefs and behaviors predict students' motivation and achievement outcomes in physical education is an area of increasing research interest. Guided by the expectancy-value model and self-determination theory, the major purpose of this study was to examine the predictive strength of teachers' autonomy, competence, and…

  8. On predicting student performance using low-rank matrix factorization techniques

    DEFF Research Database (Denmark)

    Lorenzen, Stephan Sloth; Pham, Dang Ninh; Alstrup, Stephen

    2017-01-01

    that require remedial support, generate adaptive hints, and improve the learning of students. This work focuses on predicting the score of students in the quiz system of the Clio Online learning platform, the largest Danish supplier of online learning materials, covering 90% of Danish elementary schools....... Experimental results in the Clio Online data set confirm that the proposed initialization methods lead to very fast convergence. Regarding the prediction accuracy, surprisingly, the advanced EM method is just slightly better than the baseline approach based on the global mean score and student/quiz bias...

  9. Increasing Prediction the Original Final Year Project of Student Using Genetic Algorithm

    Science.gov (United States)

    Saragih, Rijois Iboy Erwin; Turnip, Mardi; Sitanggang, Delima; Aritonang, Mendarissan; Harianja, Eva

    2018-04-01

    Final year project is very important forgraduation study of a student. Unfortunately, many students are not seriouslydidtheir final projects. Many of studentsask for someone to do it for them. In this paper, an application of genetic algorithms to predict the original final year project of a studentis proposed. In the simulation, the data of the final project for the last 5 years is collected. The genetic algorithm has several operators namely population, selection, crossover, and mutation. The result suggest that genetic algorithm can do better prediction than other comparable model. Experimental results of predicting showed that 70% was more accurate than the previous researched.

  10. Predicting students' happiness from physiology, phone, mobility, and behavioral data.

    Science.gov (United States)

    Jaques, Natasha; Taylor, Sara; Azaria, Asaph; Ghandeharioun, Asma; Sano, Akane; Picard, Rosalind

    2015-09-01

    In order to model students' happiness, we apply machine learning methods to data collected from undergrad students monitored over the course of one month each. The data collected include physiological signals, location, smartphone logs, and survey responses to behavioral questions. Each day, participants reported their wellbeing on measures including stress, health, and happiness. Because of the relationship between happiness and depression, modeling happiness may help us to detect individuals who are at risk of depression and guide interventions to help them. We are also interested in how behavioral factors (such as sleep and social activity) affect happiness positively and negatively. A variety of machine learning and feature selection techniques are compared, including Gaussian Mixture Models and ensemble classification. We achieve 70% classification accuracy of self-reported happiness on held-out test data.

  11. Prediction and Analysis of students Behavior using BARC Algorithm

    OpenAIRE

    M.Sindhuja; Dr.S.Rajalakshmi; S.M.Nandagopal

    2013-01-01

    Educational Data mining is a recent trends where data mining methods are experimented for the improvement of student performance in academics. The work describes the mining of higher education students’ related attributes such as behavior, attitude and relationship. The data were collected from a higher education institution in terms of the mentioned attributes. The proposed work explored Behavior Attitude Relationship Clustering (BARC) Algorithm, which showed the improvement in students’ per...

  12. Looking for students'personal characteristics predicting study outcome

    NARCIS (Netherlands)

    Bergen, T.C.M.; Bragt, van C.A.C.; Bakx, A.W.E.A.; Croon, M.A.

    2011-01-01

    Abstract The central goal of this study is to clarify to what degree former education and students’ personal characteristics (the ‘Big Five personality characteristics’, personal orientations on learning and students’ study approach) may predict study outcome (required credits and study

  13. Social Problem Solving Ability Predicts Mental Health Among Undergraduate Students

    OpenAIRE

    Ranjbar, Mansour; Bayani, Ali Asghar; Bayani, Ali

    2013-01-01

    Background : The main objective of this study was predicting student′s mental health using social problem solving- ability . Methods : In this correlational- descriptive study, 369 (208 female and 161 male) from, Mazandaran University of Medical Science were selected through stratified random sampling method. In order to collect the data, the social problem solving inventory-revised and general health questionnaire were used. Data were analyzed through SPSS-19, Pearson′s correlation, t tes...

  14. A Geometrical-based Vertical Gain Correction for Signal Strength Prediction of Downtilted Base Station Antennas in Urban Areas

    DEFF Research Database (Denmark)

    Rodriguez, Ignacio; Nguyen, Huan Cong; Sørensen, Troels Bundgaard

    2012-01-01

    -based extension to standard empirical path loss prediction models can give quite reasonable accuracy in predicting the signal strength from tilted base station antennas in small urban macro-cells. Our evaluation is based on measurements on several sectors in a 2.6 GHz Long Term Evolution (LTE) cellular network......, with electrical antenna downtilt in the range from 0 to 10 degrees, as well as predictions based on ray-tracing and 3D building databases covering the measurement area. Although the calibrated ray-tracing predictions are highly accurate compared with the measured data, the combined LOS/NLOS COST-WI model...

  15. Predictive validity of pre-admission assessments on medical student performance.

    Science.gov (United States)

    Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef; Mohamed, Ayman

    2017-11-24

    To examine the predictive validity of pre-admission variables on students' performance in a medical school in Saudi Arabia. In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students' progress test performance (p<0.001 and B=19.02). Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years.

  16. Cross-cultural validity of the theory of planned behavior for predicting healthy food choice in secondary school students of Inner Mongolia.

    Science.gov (United States)

    Shimazaki, Takashi; Bao, Hugejiletu; Deli, Geer; Uechi, Hiroaki; Lee, Ying-Hua; Miura, Kayo; Takenaka, Koji

    2017-11-01

    Unhealthy eating behavior is a serious health concern among secondary school students in Inner Mongolia. To predict their healthy food choices and devise methods of correcting unhealthy choices, we sought to confirm the cross-cultural validity of the theory of planned behavior among Inner Mongolian students. A cross-sectional study, conducted between November and December 2014. Overall, 3047 students were enrolled. We devised a questionnaire based on the theory of planned behavior to measure its components (intentions, attitudes, subjective norms, and perceived behavioral control) in relation to healthy food choices; we also assessed their current engagement in healthy food choices. A principal component analysis revealed high contribution rates for the components (69.32%-88.77%). A confirmatory factor analysis indicated that the components of the questionnaire had adequate model fit (goodness of fit index=0.997, adjusted goodness of fit index=0.984, comparative fit index=0.998, and root mean square error of approximation=0.049). Notably, data from participants within the suburbs did not support the theory of planned behavior construction. Several paths did not predict the hypothesis variables. However, attitudes toward healthy food choices strongly predicted behavioral intention (path coefficients 0.49-0.77, ptheory of planned behavior can apply to secondary school students in urban areas. Furthermore, attitudes towards healthy food choices were the best predictor of behavioral intentions to engage in such choices in Inner Mongolian students. Copyright © 2017 Diabetes India. Published by Elsevier Ltd. All rights reserved.

  17. Intermittently-visual Tracking Experiments Reveal the Roles of Error-correction and Predictive Mechanisms in the Human Visual-motor Control System

    Science.gov (United States)

    Hayashi, Yoshikatsu; Tamura, Yurie; Sase, Kazuya; Sugawara, Ken; Sawada, Yasuji

    Prediction mechanism is necessary for human visual motion to compensate a delay of sensory-motor system. In a previous study, “proactive control” was discussed as one example of predictive function of human beings, in which motion of hands preceded the virtual moving target in visual tracking experiments. To study the roles of the positional-error correction mechanism and the prediction mechanism, we carried out an intermittently-visual tracking experiment where a circular orbit is segmented into the target-visible regions and the target-invisible regions. Main results found in this research were following. A rhythmic component appeared in the tracer velocity when the target velocity was relatively high. The period of the rhythm in the brain obtained from environmental stimuli is shortened more than 10%. The shortening of the period of rhythm in the brain accelerates the hand motion as soon as the visual information is cut-off, and causes the precedence of hand motion to the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand motion precedes the target in average when the predictive mechanism dominates the error-corrective mechanism.

  18. Approaches to studying predict academic performance in undergraduate occupational therapy students: a cross-cultural study.

    Science.gov (United States)

    Bonsaksen, Tore; Brown, Ted; Lim, Hua Beng; Fong, Kenneth

    2017-05-02

    Learning outcomes may be a result of several factors including the learning environment, students' predispositions, study efforts, cultural factors and approaches towards studying. This study examined the influence of demographic variables, education-related factors, and approaches to studying on occupational therapy students' Grade Point Average (GPA). Undergraduate occupational therapy students (n = 712) from four countries completed the Approaches and Study Skills Inventory for Students (ASSIST). Demographic background, education-related factors, and ASSIST scores were used in a hierarchical linear regression analysis to predict the students' GPA. Being older, female and more time engaged in self-study activities were associated with higher GPA among the students. In addition, five ASSIST subscales predicted higher GPA: higher scores on 'seeking meaning', 'achieving', and 'lack of purpose', and lower scores on 'time management' and 'fear of failure'. The full model accounted for 9.6% of the variance related to the occupational therapy students' GPA. To improve academic performance among occupational therapy students, it appears important to increase their personal search for meaning and motivation for achievement, and to reduce their fear of failure. The results should be interpreted with caution due to small effect sizes and a modest amount of variance explained by the regression model, and further research on predictors of academic performance is required.

  19. Predicting the academic performance of Asian, black, and Hispanic optometry students.

    Science.gov (United States)

    Kegel-Flom, P

    1990-03-01

    As optometry schools receive increasing numbers of Asian, Black, and Hispanic applications, it is appropriate for us to ask whether minority students differ in meaningful ways from nonminority students in measures used in admissions, and whether these variables have differential validity in predicting their achievement in optometry school. This study compares Asian, Black, Hispanic, and nonminority students at entry to the University of Houston College of Optometry (UHCO) from 1981 through 1986 and tests the validity of admissions indices to predict optometry grades, academic dropout, and high-level achievement for these ethnic groups. Although preoptometry grade point average (GPA) was the best predictor of optometry grades for all students, measures of verbal ability were additional predictors for Asian students and, for Black and Hispanic students, ability in study/reading and math were predictors. In addition, personality inventory measures and ratings of the competitiveness of the undergraduate institution were important in differentiating minority academic dropouts from retained students. Suggestions are made for optometry college programs which will enhance the probability of success for minority students.

  20. A hybrid solution using computational prediction and measured data to accurately determine process corrections with reduced overlay sampling

    Science.gov (United States)

    Noyes, Ben F.; Mokaberi, Babak; Mandoy, Ram; Pate, Alex; Huijgen, Ralph; McBurney, Mike; Chen, Owen

    2017-03-01

    Reducing overlay error via an accurate APC feedback system is one of the main challenges in high volume production of the current and future nodes in the semiconductor industry. The overlay feedback system directly affects the number of dies meeting overlay specification and the number of layers requiring dedicated exposure tools through the fabrication flow. Increasing the former number and reducing the latter number is beneficial for the overall efficiency and yield of the fabrication process. An overlay feedback system requires accurate determination of the overlay error, or fingerprint, on exposed wafers in order to determine corrections to be automatically and dynamically applied to the exposure of future wafers. Since current and future nodes require correction per exposure (CPE), the resolution of the overlay fingerprint must be high enough to accommodate CPE in the overlay feedback system, or overlay control module (OCM). Determining a high resolution fingerprint from measured data requires extremely dense overlay sampling that takes a significant amount of measurement time. For static corrections this is acceptable, but in an automated dynamic correction system this method creates extreme bottlenecks for the throughput of said system as new lots have to wait until the previous lot is measured. One solution is using a less dense overlay sampling scheme and employing computationally up-sampled data to a dense fingerprint. That method uses a global fingerprint model over the entire wafer; measured localized overlay errors are therefore not always represented in its up-sampled output. This paper will discuss a hybrid system shown in Fig. 1 that combines a computationally up-sampled fingerprint with the measured data to more accurately capture the actual fingerprint, including local overlay errors. Such a hybrid system is shown to result in reduced modelled residuals while determining the fingerprint, and better on-product overlay performance.

  1. Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method

    Directory of Open Access Journals (Sweden)

    Mingjie Tan

    2015-02-01

    Full Text Available The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN, Decision Tree (DT and Bayesian Networks (BNs. A large sample of 62375 students was utilized in the procedures of model training and testing. The results of each model were presented in confusion matrix, and analyzed by calculating the rates of accuracy, precision, recall, and F-measure. The results suggested all of the three machine learning methods were effective in student dropout prediction, and DT presented a better performance. Finally, some suggestions were made for considerable future research.

  2. Depression Vulnerability Predicts Cigarette Smoking among College Students: Gender and Negative Reinforcement Expectancies as Contributing Factors

    OpenAIRE

    Morrell, Holly E. R.; Cohen, Lee M.; McChargue, Dennis E.

    2010-01-01

    This study examined the association between vulnerability to depression and smoking behavior in college students in 1214 college students (54% female), and evaluated gender and expectancies of negative affect reduction as moderators or mediators of this relationship. Depression vulnerability predicted smoking in females, but not males. The relationship between depression vulnerability and smoking status was mediated by expectancies of negative affect reduction in females only. Female college ...

  3. Using an admissions exam to predict student success in an ADN program.

    Science.gov (United States)

    Gallagher, P A; Bomba, C; Crane, L R

    2001-01-01

    Nursing faculty strive to admit students who are likely to successfully complete the nursing curriculum and pass NCLEX-RN. The high cost of academic preparation and the nursing shortage make this selection process even more critical. The authors discuss how one community college nursing program examined academic achievement measures to determine how well they predicted student success. Results provided faculty with useful data to improve the success and retention of nursing.

  4. ENHANCED PREDICTION OF STUDENT DROPOUTS USING FUZZY INFERENCE SYSTEM AND LOGISTIC REGRESSION

    OpenAIRE

    A. Saranya; J. Rajeswari

    2016-01-01

    Predicting college and school dropouts is a major problem in educational system and has complicated challenge due to data imbalance and multi dimensionality, which can affect the low performance of students. In this paper, we have collected different database from various colleges, among these 500 best real attributes are identified in order to identify the factor that affecting dropout students using neural based classification algorithm and different mining technique are implemented for dat...

  5. Correction to: CASPer, an online pre-interview screen for personal/professional characteristics: prediction of national licensure scores.

    Science.gov (United States)

    Dore, Kelly L; Reiter, Harold I; Kreuger, Sharyn; Norman, Geoffrey R

    2017-12-01

    In re-examining the paper "CASPer, an online pre-interview screen for personal/professional characteristics: prediction of national licensure scores" published in AHSE (22(2), 327-336), we recognized two errors of interpretation.

  6. ENHANCED PREDICTION OF STUDENT DROPOUTS USING FUZZY INFERENCE SYSTEM AND LOGISTIC REGRESSION

    Directory of Open Access Journals (Sweden)

    A. Saranya

    2016-01-01

    Full Text Available Predicting college and school dropouts is a major problem in educational system and has complicated challenge due to data imbalance and multi dimensionality, which can affect the low performance of students. In this paper, we have collected different database from various colleges, among these 500 best real attributes are identified in order to identify the factor that affecting dropout students using neural based classification algorithm and different mining technique are implemented for data processing. We also propose a Dropout Prediction Algorithm (DPA using fuzzy logic and Logistic Regression based inference system because the weighted average will improve the performance of whole system. We are experimented our proposed work with all other classification systems and documented as the best outcomes. The aggregated data is given to the decision trees for better dropout prediction. The accuracy of overall system 98.6% it shows the proposed work depicts efficient prediction.

  7. Application Of Data Mining Techniques For Student Success And Failure Prediction The Case Of DebreMarkos University

    OpenAIRE

    Muluken Alemu Yehuala

    2015-01-01

    Abstract This research work has investigated the potential applicability of data mining technology to predict student success and failure cases on University students datasets. CRISP-DM Cross Industry Standard Process for Data mining is a data mining methodology to be used by the research. Classification and prediction data mining functionalities are used to extract hidden patterns from students data. These patterns can be seen in relation to different variables in the students records. The ...

  8. Finding "safe" campuses: predicting the presence of LGBT student groups at North Carolina colleges and universities.

    Science.gov (United States)

    Kane, Melinda D

    2013-01-01

    A key indicator of a supportive campus climate for lesbian, gay, bisexual, and transgender (LGBT) college students is the existence of an LGBT student organization. This article integrates the research on high school LGBT policies and programs with social movement studies of campus activism to examine the characteristics associated with the existence of university-approved LGBT groups on North Carolina campuses. Drawing on data from the National Center for Education Statistics, campus Web sites, and other sources, logistic regression is used to examine the importance of public opinion, campus and community resources, and the institutional context in predicting the location of these student groups.

  9. Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method

    OpenAIRE

    Mingjie Tan; Peiji Shao

    2015-01-01

    The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN), Decision Tree (DT) and Bayesian Ne...

  10. Predicting performance at medical school: can we identify at-risk students?

    Directory of Open Access Journals (Sweden)

    Shaban S

    2011-05-01

    Full Text Available Sami Shaban, Michelle McLeanDepartment of Medical Education, Faculty of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab EmiratesBackground: The purpose of this study was to examine the predictive potential of multiple indicators (eg, preadmission scores, unit, module and clerkship grades, course and examination scores on academic performance at medical school, with a view to identifying students at risk.Methods: An analysis was undertaken of medical student grades in a 6-year medical school program at the Faculty of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates, over the past 14 years.Results: While high school scores were significantly (P < 0.001 correlated with the final integrated examination, predictability was only 6.8%. Scores for the United Arab Emirates university placement assessment (Common Educational Proficiency Assessment were only slightly more promising as predictors with 14.9% predictability for the final integrated examination. Each unit or module in the first four years was highly correlated with the next unit or module, with 25%–60% predictability. Course examination scores (end of years 2, 4, and 6 were significantly correlated (P < 0.001 with the average scores in that 2-year period (59.3%, 64.8%, and 55.8% predictability, respectively. Final integrated examination scores were significantly correlated (P < 0.001 with National Board of Medical Examiners scores (35% predictability. Multivariate linear regression identified key grades with the greatest predictability of the final integrated examination score at three stages in the program.Conclusion: This study has demonstrated that it may be possible to identify “at-risk” students relatively early in their studies through continuous data archiving and regular analysis. The data analysis techniques used in this study are not unique to this institution.Keywords: at-risk students, grade

  11. Determination of Multiphase Flow Meter Reliability and Development of Correction Charts for the Prediction of Oilfield Fluid Flow Rates

    Directory of Open Access Journals (Sweden)

    Samuel S. MOFUNLEWI

    2008-06-01

    Full Text Available The aim of field testing of Multiphase Flow Meter (MPFM is to show whether its accuracy compares favourably with that of the Test Separator in accurately measuring the three production phases (oil, gas and water as well as determining meter reliability in field environment. This study evaluates field test results of the MPFM as compared to reference conventional test separators. Generally, results show that MPFM compares favourably with Test Separator within the specified range of accuracy.At the moment, there is no legislation for meter proving technique for MPFM. However, this study has developed calibration charts that can be used to correct and improve meter accuracy.

  12. Balancing of a rigid rotor using artificial neural network to predict the correction masses - DOI: 10.4025/actascitechnol.v31i2.3912

    Directory of Open Access Journals (Sweden)

    Fábio Lúcio Santos

    2009-06-01

    Full Text Available This paper deals with an analytical model of a rigid rotor supported by hydrodynamic journal bearings where the plane separation technique together with the Artificial Neural Network (ANN is used to predict the location and magnitude of the correction masses for balancing the rotor bearing system. The rotating system is modeled by applying the rigid shaft Stodola-Green model, in which the shaft gyroscopic moments and rotatory inertia are accounted for, in conjunction with the hydrodynamic cylindrical journal bearing model based on the classical Reynolds equation. A linearized perturbation procedure is employed to render the lubrication equations from the Reynolds equation, which allows predicting the eight linear force coefficients associated with the bearing direct and cross-coupled stiffness and damping coefficients. The results show that the methodology presented is efficient for balancing rotor systems. This paper gives a step further in the monitoring process, since Artificial Neural Network is normally used to predict, not to correct the mass unbalance. The procedure presented can be used in turbo machinery industry to balance rotating machinery that require continuous inspections. Some simulated results will be used in order to clarify the methodology presented.

  13. How to Make Correct Predictions in False Belief Tasks without Attributing False Beliefs: An Analysis of Alternative Inferences and How to Avoid Them

    Directory of Open Access Journals (Sweden)

    Ricardo Augusto Perera

    2018-04-01

    Full Text Available The use of new paradigms of false belief tasks (FBT allowed to reduce the age of children who pass the test from the previous 4 years in the standard version to only 15 months or even a striking 6 months in the nonverbal modification. These results are often taken as evidence that infants already possess an—at least implicit—theory of mind (ToM. We criticize this inferential leap on the grounds that inferring a ToM from the predictive success on a false belief task requires to assume as premise that a belief reasoning is a necessary condition for correct action prediction. It is argued that the FBT does not satisfactorily constrain the predictive means, leaving room for the use of belief-independent inferences (that can rely on the attribution of non-representational mental states or the consideration of behavioral patterns that dispense any reference to other minds. These heuristics, when applied to the FBT, can achieve the same predictive success of a belief-based inference because information provided by the test stimulus allows the recognition of particular situations that can be subsumed by their ‘laws’. Instead of solving this issue by designing a single experimentum crucis that would render unfeasible the use of non-representational inferences, we suggest the application of a set of tests in which, although individually they can support inferences dissociated from a ToM, only an inference that makes use of false beliefs is able to correctly predict all the outcomes.

  14. Collective school-type identity: predicting students' motivation beyond academic self-concept.

    Science.gov (United States)

    Knigge, Michel; Hannover, Bettina

    2011-06-01

    In Germany, according to their prior achievement students are tracked into different types of secondary school that provide profoundly different options for their future educational careers. In this paper we suggest that as a result, school tracks clearly differ in their social status or reputation. This should translate into different collective school-type identities for their students, irrespective of the students' personal academic self-concepts. We examine the extent to which collective school-type identity systematically varies as a function of the school track students are enrolled in, and the extent to which students' collective school-type identity makes a unique contribution beyond academic self-concept and school track in predicting scholastic motivation. In two cross-sectional studies a measure of collective school-type identity is established and applied to explain motivational differences between two school tracks in Berlin. In Study 1 (N = 39 students) the content of the collective school-type identity is explored by means of an open format questionnaire. Based on these findings a structured instrument (semantic differential) to measure collective school-type identity is developed. In Study 2 (N = 1278 students) the assumed structure with four subscales (Stereotype Achievement, Stereotype Motivation, Stereotype Social, and Compensation) is proved with confirmatory factor analysis. This measure is used to compare the collective school-type identity across school tracks and predict motivational outcomes. Results show large differences in collective school-type identity between students of different school tracks. Furthermore, these differences can explain motivational differences between school tracks. Collective school-type identity has incremental predictive power for scholastic motivation, over and above the effects of academic self-concept and school track.

  15. A predictive model of suitability for minimally invasive parathyroid surgery in the treatment of primary hyperparathyroidism [corrected].

    LENUS (Irish Health Repository)

    Kavanagh, Dara O

    2012-05-01

    Improved preoperative localizing studies have facilitated minimally invasive approaches in the treatment of primary hyperparathyroidism (PHPT). Success depends on the ability to reliably select patients who have PHPT due to single-gland disease. We propose a model encompassing preoperative clinical, biochemical, and imaging studies to predict a patient\\'s suitability for minimally invasive surgery.

  16. RNA secondary structure prediction by using discrete mathematics: an interdisciplinary research experience for undergraduate students.

    Science.gov (United States)

    Ellington, Roni; Wachira, James; Nkwanta, Asamoah

    2010-01-01

    The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems.

  17. RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

    Science.gov (United States)

    Ellington, Roni; Wachira, James

    2010-01-01

    The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems. PMID:20810968

  18. Factors Predicting Turkish and Korean Students' Science and Mathematics Achievement in TIMSS 2011

    Science.gov (United States)

    Topçu, Mustafa Sami; Erbilgin, Evrim; Arikan, Serkan

    2016-01-01

    This study makes an important contribution to an expanding body of international comparative studies by exploring factors predicting differences in science and mathematics achievement by students in Turkey and the Republic of Korea on the 2011 TIMSS assessment. While these countries are similar with regards to population size, cultural beliefs…

  19. Classification via Clustering for Predicting Final Marks Based on Student Participation in Forums

    Science.gov (United States)

    Lopez, M. I.; Luna, J. M.; Romero, C.; Ventura, S.

    2012-01-01

    This paper proposes a classification via clustering approach to predict the final marks in a university course on the basis of forum data. The objective is twofold: to determine if student participation in the course forum can be a good predictor of the final marks for the course and to examine whether the proposed classification via clustering…

  20. Loneliness among University Students: Predictive Power of Sex Roles and Attachment Styles on Loneliness

    Science.gov (United States)

    Ilhan, Tahsin

    2012-01-01

    This study examined the predictive power of sex roles and attachment styles on loneliness. A total of 188 undergraduate students (114 female, and 74 male) from Gazi University completed the Bem Sex Role Inventory, UCLA Loneliness Scale, and Relationship Scales Questionnaire. Hierarchic Multiple Regression analysis and t-test were used to test…

  1. Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program

    Science.gov (United States)

    Yukselturk, Erman; Ozekes, Serhat; Turel, Yalin Kilic

    2014-01-01

    This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographic Survey, Online Technologies…

  2. Data pre-processing: a case study in predicting student's retention in ...

    African Journals Online (AJOL)

    dataset with features that are ready for data mining task. The study also proposed a process model and suggestions, which can be applied to support more comprehensible tools for educational domain who is the end user. Subsequently, the data pre-processing become more efficient for predicting student's retention in ...

  3. Using Predictive Modelling to Identify Students at Risk of Poor University Outcomes

    Science.gov (United States)

    Jia, Pengfei; Maloney, Tim

    2015-01-01

    Predictive modelling is used to identify students at risk of failing their first-year courses and not returning to university in the second year. Our aim is twofold. Firstly, we want to understand the factors that lead to poor first-year experiences at university. Secondly, we want to develop simple, low-cost tools that would allow universities to…

  4. Predicting Change over Time in Career Planning and Career Exploration for High School Students

    Science.gov (United States)

    Creed, Peter A.; Patton, Wendy; Prideaux, Lee-Ann

    2007-01-01

    This study assessed 166 high school students in Grade 8 and again in Grade 10. Four models were tested: (a) whether the T1 predictor variables (career knowledge, indecision, decision-making selfefficacy, self-esteem, demographics) predicted the outcome variable (career planning/exploration) at T1; (b) whether the T1 predictor variables predicted…

  5. Correlation and Predictive Relationship between Self-Determination Instruction and Academic Performance of Students with Disabilities

    Science.gov (United States)

    Chao, Pen-Chiang; Chou, Yu-Chi

    2017-01-01

    The purpose of this study was to investigate the correlation and probable predictive relationship between self-determination skills taught by special education teachers and the academic performance of students with disabilities from junior high schools in Taiwan. The subjects included teachers from resource rooms and self-contained classrooms (n =…

  6. Comparison of Self-Beliefs for Predicting Student Motivation and Achievement

    Science.gov (United States)

    Bong, Mimi; Cho, Catherine; Ahn, Hyun Seon; Kim, Hye Jin

    2012-01-01

    The authors examined whether self-concept, self-efficacy, and self-esteem show differential predictive utility for academic achievement across age groups and domains. More specifically, the relationships of 3 self-constructs with achievement were examined in mathematics for elementary school students and mathematics and language arts for middle…

  7. Ideal Teacher Behaviors: Student Motivation and Self-Efficacy Predict Preferences

    Science.gov (United States)

    Komarraju, Meera

    2013-01-01

    Differences in students' academic self-efficacy and motivation were examined in predicting preferred teacher traits. Undergraduates (261) completed the Teaching Behavior Checklist, Academic Self-Concept scale, and Academic Motivation scale. Hierarchical regression analyses indicated that academic self-efficacy and extrinsic motivation explained…

  8. Decision-Tree Analysis for Predicting First-Time Pass/Fail Rates for the NCLEX-RN® in Associate Degree Nursing Students.

    Science.gov (United States)

    Chen, Hsiu-Chin; Bennett, Sean

    2016-08-01

    Little evidence shows the use of decision-tree algorithms in identifying predictors and analyzing their associations with pass rates for the NCLEX-RN(®) in associate degree nursing students. This longitudinal and retrospective cohort study investigated whether a decision-tree algorithm could be used to develop an accurate prediction model for the students' passing or failing the NCLEX-RN. This study used archived data from 453 associate degree nursing students in a selected program. The chi-squared automatic interaction detection analysis of the decision trees module was used to examine the effect of the collected predictors on passing/failing the NCLEX-RN. The actual percentage scores of Assessment Technologies Institute®'s RN Comprehensive Predictor(®) accurately identified students at risk of failing. The classification model correctly classified 92.7% of the students for passing. This study applied the decision-tree model to analyze a sequence database for developing a prediction model for early remediation in preparation for the NCLEXRN. [J Nurs Educ. 2016;55(8):454-457.]. Copyright 2016, SLACK Incorporated.

  9. Predictive Method for Correct Identification of Archaeological Charred Grape Seeds: Support for Advances in Knowledge of Grape Domestication Process

    Science.gov (United States)

    Ucchesu, Mariano; Orrù, Martino; Grillo, Oscar; Venora, Gianfranco; Paglietti, Giacomo; Ardu, Andrea; Bacchetta, Gianluigi

    2016-01-01

    The identification of archaeological charred grape seeds is a difficult task due to the alteration of the morphological seeds shape. In archaeobotanical studies, for the correct discrimination between Vitis vinifera subsp. sylvestris and Vitis vinifera subsp. vinifera grape seeds it is very important to understand the history and origin of the domesticated grapevine. In this work, different carbonisation experiments were carried out using a hearth to reproduce the same burning conditions that occurred in archaeological contexts. In addition, several carbonisation trials on modern wild and cultivated grape seeds were performed using a muffle furnace. For comparison with archaeological materials, modern grape seed samples were obtained using seven different temperatures of carbonisation ranging between 180 and 340ºC for 120 min. Analysing the grape seed size and shape by computer vision techniques, and applying the stepwise linear discriminant analysis (LDA) method, discrimination of the wild from the cultivated charred grape seeds was possible. An overall correct classification of 93.3% was achieved. Applying the same statistical procedure to compare modern charred with archaeological grape seeds, found in Sardinia and dating back to the Early Bronze Age (2017–1751 2σ cal. BC), allowed 75.0% of the cases to be identified as wild grape. The proposed method proved to be a useful and effective procedure in identifying, with high accuracy, the charred grape seeds found in archaeological sites. Moreover, it may be considered valid support for advances in the knowledge and comprehension of viticulture adoption and the grape domestication process. The same methodology may also be successful when applied to other plant remains, and provide important information about the history of domesticated plants. PMID:26901361

  10. The Role of Depression and Attachment Styles in Predicting Students' Addiction to Cell Phones.

    Science.gov (United States)

    Ghasempour, Abdollah; Mahmoodi-Aghdam, Mansour

    2015-01-01

    The present study aimed at investigating the role of depression and attachment styles in predicting cell phone addiction. In this descriptive correlational study, a sample including 100 students of Payame Noor University (PNU), Reyneh Center, Iran, in the academic year of 2013-2014 was selected using volunteer sampling. Participants were asked to complete the adult attachment inventory (AAI), Beck depression inventory-13 (BDI-13) and the cell phone overuse scale (COS). Results of the stepwise multiple regression analysis showed that depression and avoidant attachment style were the best predictors of students' cell phone addiction (R(2) = 0.23). The results of this study highlighted the predictive value of depression and avoidant attachment style concerning students' cell phone addiction.

  11. Perceived Medical School stress of undergraduate medical students predicts academic performance: an observational study.

    Science.gov (United States)

    Kötter, Thomas; Wagner, Josefin; Brüheim, Linda; Voltmer, Edgar

    2017-12-16

    Medical students are exposed to high amounts of stress. Stress and poor academic performance can become part of a vicious circle. In order to counteract this circularity, it seems important to better understand the relationship between stress and performance during medical education. The most widespread stress questionnaire designed for use in Medical School is the "Perceived Medical School Stress Instrument" (PMSS). It addresses a wide range of stressors, including workload, competition, social isolation and financial worries. Our aim was to examine the relation between the perceived Medical School stress of undergraduate medical students and academic performance. We measured Medical School stress using the PMSS at two different time points (at the end of freshman year and at the end of sophomore year) and matched stress scores together with age and gender to the first medical examination (M1) grade of the students (n = 456). PMSS scores from 2 and 14 months before M1 proved to be significant predictors for medical students' M1 grade. Age and gender also predict academic performance, making older female students with high stress scores a potential risk group for entering the vicious circle of stress and poor academic performance. PMSS sum scores 2 and 14 months before the M1 exam seem to have an independent predictive validity for medical students' M1 grade. More research is needed to identify potential confounders.

  12. Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students.

    Science.gov (United States)

    Faramarzi, Mahbobeh; Khafri, Soraya

    2017-01-01

    Objective . Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design . In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results . Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students ( B = -0.512, P academic functioning, we suggest it should be routinely evaluated by mental physicians at universities.

  13. Does teacher evaluation based on student performance predict motivation, well-being, and ill-being?

    Science.gov (United States)

    Cuevas, Ricardo; Ntoumanis, Nikos; Fernandez-Bustos, Juan G; Bartholomew, Kimberley

    2018-06-01

    This study tests an explanatory model based on self-determination theory, which posits that pressure experienced by teachers when they are evaluated based on their students' academic performance will differentially predict teacher adaptive and maladaptive motivation, well-being, and ill-being. A total of 360 Spanish physical education teachers completed a multi-scale inventory. We found support for a structural equation model that showed that perceived pressure predicted teacher autonomous motivation negatively, predicted amotivation positively, and was unrelated to controlled motivation. In addition, autonomous motivation predicted vitality positively and exhaustion negatively, whereas controlled motivation and amotivation predicted vitality negatively and exhaustion positively. Amotivation significantly mediated the relation between pressure and vitality and between pressure and exhaustion. The results underline the potential negative impact of pressure felt by teachers due to this type of evaluation on teacher motivation and psychological health. Copyright © 2018 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  14. Attachment and personality predicts engagement in sexual harassment by male and female college students.

    Science.gov (United States)

    Mènard, Kim S; Shoss, Naomi E; Pincus, Aaron L

    2010-01-01

    The purpose of this study was to examine a trait model of personality (Five-Factor Model) as a mediator of the relationship between attachment styles and sexually harassing behavior in a sample of male (N = 148) and female (N = 278) college students. We found that gender (male) and low Agreeableness predicted engaging in sexual harassment and all three of its subtypes; gender harassment, unwanted sexual attention, and sexual coercion. Further, low Conscientiousness predicted overall sexual harassment, gender harassment, and unwanted sexual attention. Personality traits mediated the relationship between insecure attachment styles (Preoccupation with Relationships and Relationships as Secondary) and sexually harassing behaviors. Thus, factors beyond gender can help predict students' propensity to sexually harass others.

  15. Prediction of Addiction Potential on the Basis of Aggression and Assertiveness in University Students

    Directory of Open Access Journals (Sweden)

    Mehrdad Hajihasani

    2012-02-01

    Full Text Available Introduction: The aim of present research was the prediction of addiction potential on the basis of aggression and assertiveness in Allameh Tabbatabaei girl students. Method: The research method was correlational design and population of research was girl students of Allameh Tabatabaei university. By available sampling 150 girls were selected and Ahvaz Aggression Questionnaire, Gambril & Rigy Assertiveness questionnaire and Zargari Addiction Potential Questionnaire administered among selected sample. Findings: the results of the Pearson correlation showed that the relationship between aggression, assertiveness, and addiction potential was significant. Also, the results of multivariate regression analysis showed that aggression, assertiveness and depression can predict the Addiction Potential. Conclusion: Addiction potential can be predicted by aggression and assertiveness.

  16. Exclusionary Discipline of Students with Disabilities: Student and School Characteristics Predicting Suspension

    Science.gov (United States)

    Sullivan, Amanda L.; Van Norman, Ethan R.; Klingbeil, David A.

    2014-01-01

    Given the negative outcomes associated with suspension, scholars and practitioners are concerned with discipline disparities. This study explored patterns and predictors of suspension in a sample of 2,750 students with disabilities in 39 schools in a Midwestern district. Hierarchical generalized linear modeling demonstrated that disability type,…

  17. Safety, Efficacy, Predictability and Stability Indices of Photorefractive Keratectomy for Correction of Myopic Astigmatism with Plano-Scan and Tissue-Saving Algorithms

    Directory of Open Access Journals (Sweden)

    Mehrdad Mohammadpour

    2013-10-01

    Full Text Available Purpose: To assess the safety, efficacy and predictability of photorefractive keratectomy (PRK [Tissue-saving (TS versus Plano-scan (PS ablation algorithms] of Technolas 217z excimer laser for correction of myopic astigmatismMethods: In this retrospective study one hundred and seventy eyes of 85 patients (107 eyes (62.9% with PS and 63 eyes (37.1% with TS algorithm were included. TS algorithm was applied for those with central corneal thickness less than 500 µm or estimated residual stromal thickness less than 420 µm. Mitomycin C (MMC was applied for 120 eyes (70.6%; in case of an ablation depth more than 60 μm and/or astigmatic correction more than one diopter (D. Mean sphere, cylinder, spherical equivalent (SE refraction, uncorrected visual acuity (UCVA, best corrected visual acuity (BCVA were measured preoperatively, and 4 weeks,12 weeks and 24 weeks postoperatively.Results: One, three and six months postoperatively, 60%, 92.9%, 97.5% of eyes had UCVA of 20/20 or better, respectively. Mean preoperative and 1, 3, 6 months postoperative SE were -3.48±1.28 D (-1.00 to -8.75, -0.08±0.62D, -0.02±0.57 and -0.004± 0.29, respectively. And also, 87.6%, 94.1% and 100% were within ±1.0 D of emmetropia and 68.2, 75.3, 95% were within ±0.5 of emmetropia. The safety and efficacy indices were 0.99 and 0.99 at 12 weeks and 1.009 and 0.99 at 24 weeks, respectively. There was no clinically or statistically significant difference between the outcomes of PS or TS algorithms or between those with or without MMC in either group in terms of safety, efficacy, predictability or stability. Dividing the eyes with subjective SE≤4 D and SE≥4 D postoperatively, there was no significant difference between the predictability of the two groups. There was no intra- or postoperative complication.Conclusion: Outcomes of PRK for correction of myopic astigmatism showed great promise with both PS and TS algorithms.

  18. INCREASE PRESSURE IN CONTAINER WITH BALLOONS INSIDE: PREDICTIONS AND STUDENT EXPLANATIONS

    Directory of Open Access Journals (Sweden)

    Ladislao Romero-Bojórquez

    2014-07-01

    Full Text Available From a Predict, Observe, Explain (POE strategy, students’ existing ideas are explored to promote a conceptual change as a process of meaningful learning. The study population included 140 students from the 2nd common term of College, at the Faculty of Chemical and Biological Sciences of the Autonomous University of Sinaloa, Mexico. A mixed questionnaire with open–ended and multiple choice questions was used; asking students to justify their answers, with the alternative to support them with drawings. Students responded while attended an experimental demonstration. The questionnaire involves activities of metacognition and cognitive conflict, managing to make students aware of scientific misconceptions, and to adopt attitudes that facilitate their understanding, influencing a significant conceptual change in this study population.

  19. Performance assessment of the commercial CFD software for the prediction of the PWR internal flow - Corrected version

    International Nuclear Information System (INIS)

    Lee, Gong Hee; Bang, Young Seok; Woo, Sweng Woong; Cheong, Ae Ju; Kim, Do Hyeong; Kang, Min Ku

    2013-01-01

    As the computer hardware technology develops the license applicants for nuclear power plant use the commercial CFD software with the aim of reducing the excessive conservatism associated with using simplified and conservative analysis tools. Even if some of CFD software developers and its users think that a state of the art CFD software can be used to solve reasonably at least the single-phase nuclear reactor safety problems there is still the limitations and the uncertainties in the calculation result. From a regulatory perspective, Korea Institute of Nuclear Safety (KINS) has been presently conducting the performance assessment of the commercial CFD software for the nuclear reactor safety problems. In this study, in order to examine the prediction performance of the commercial CFD software with the porous model in the analysis of the scale-down APR+ (Advanced Power Reactor Plus) internal flow, simulation was conducted with the on-board numerical models in ANSYS CFX R.14 and FLUENT R.14. It was concluded that depending on the CFD software the internal flow distribution of the scale-down APR+ was locally some-what different. Although there was a limitation in estimating the prediction performance of the commercial CFD software due to the limited number of the measured data, CFXR.14 showed the more reasonable predicted results in comparison with FLUENT R.14. Meanwhile, due to the difference of discretization methodology, FLUENT R.14 required more computational memory than CFX R.14 for the same grid system. Therefore the CFD software suitable to the available computational resource should be selected for the massive parallel computation. (authors)

  20. Characteristics predicting laparoscopic skill in medical students: nine years' experience in a single center.

    Science.gov (United States)

    Nomura, Tsutomu; Matsutani, Takeshi; Hagiwara, Nobutoshi; Fujita, Itsuo; Nakamura, Yoshiharu; Kanazawa, Yoshikazu; Makino, Hiroshi; Mamada, Yasuhiro; Fujikura, Terumichi; Miyashita, Masao; Uchida, Eiji

    2018-01-01

    We introduced laparoscopic simulator training for medical students in 2007. This study was designed to identify factors that predict the laparoscopic skill of medical students, to identify intergenerational differences in abilities, and to estimate the variability of results in each training group. Our ultimate goal was to determine the optimal educational program for teaching laparoscopic surgery to medical students. Between 2007 and 2015, a total of 270 fifth-year medical students were enrolled in this observational study. Before training, the participants were asked questions about their interest in laparoscopic surgery, experience with playing video games, confidence about driving, and manual dexterity. After the training, aspects of their competence (execution time, instrument path length, and economy of instrument movement) were assessed. Multiple regression analysis identified significant effects of manual dexterity, gender, and confidence about driving on the results of the training. The training results have significantly improved over recent years. The variability among the results in each training group was relatively small. We identified the characteristics of medical students with excellent laparoscopic skills. We observed educational benefits from interactions between medical students within each training group. Our study suggests that selection and grouping are important to the success of modern programs designed to train medical students in laparoscopic surgery.

  1. Predicting Relationship of Smoking Behavior Among Male Saudi Arabian College Students Related to Their Religious Practice.

    Science.gov (United States)

    Almutairi, Khalid M

    2016-04-01

    This study describes the relationships of smoking behavior among a sample of male college students in Kingdom of Saudi Arabia (KSA) to their religious practice, parents' smoking behaviors and attitudes, peers' smoking behaviors and attitudes, and knowledge about the dangers of smoking. A 49-item questionnaire was developed and pilot tested in KSA. This questionnaire was completed during the academic year 2013 by 715 undergraduate male students at the King Saud University in Riyadh. 29.8% of the students were smokers (13.8% cigarette smokers, 7.3% sheesha smokers, and 27% cigarette and sheesha smokers). Students in the College of Education were much more likely to be smokers than the students in the College of Science. The differences between the College of Education and the College of Science was statistically significant (χ (2) = 16.864. df = 1, p = .001). Logistic regression analysis suggested that students who were more faithful in their practice of Islam were 15% less likely to smoke. Students who were more knowledgeable about the dangers of smoking were 8% less likely to smoke. The logistic analysis identified peers (friends) as the most powerful factor in predicting smoking. The four-factor model had an overall classification accuracy of 78%. The need to understand more fully the dynamics of peer relations among Saudi Arabian males as a basis for developing tobacco education/prevention programs. Prevention programs will need to include education and changes in the college level or earlier in KSA.

  2. Examining and Predicting College Students' Reading Intentions and Behaviors: An Application of the Theory of Reasoned Action

    Science.gov (United States)

    Burak, Lydia

    2004-01-01

    This study examined the recreational reading attitudes, intentions, and behaviors of college students. The theory of reasoned action provided the framework for the investigation and prediction of the students' intentions and behaviors. Two hundred and one students completed questionnaires developed according to the guidelines for the construction…

  3. How Well Does the Theory of Planned Behavior Predict Graduation among College and University Students with Disabilities?

    Science.gov (United States)

    Fichten, Catherine S.; Nguyen, Mai Nhu; Amsel, Rhonda; Jorgensen, Shirley; Budd, Jillian; Jorgensen, Mary; Asuncion, Jennison; Barile, Maria

    2014-01-01

    The goal of this research was to develop a model to predict which students with disabilities will drop out before graduation and to investigate the drop out pattern of students with disabilities. To accomplish this we evaluated potential predictors of persistence and drop-out among 611 college and university students with various disabilities and…

  4. Prolonged corrected QT interval is predictive of future stroke events even in subjects without ECG-diagnosed left ventricular hypertrophy.

    Science.gov (United States)

    Ishikawa, Joji; Ishikawa, Shizukiyo; Kario, Kazuomi

    2015-03-01

    We attempted to evaluate whether subjects who exhibit prolonged corrected QT (QTc) interval (≥440 ms in men and ≥460 ms in women) on ECG, with and without ECG-diagnosed left ventricular hypertrophy (ECG-LVH; Cornell product, ≥244 mV×ms), are at increased risk of stroke. Among the 10 643 subjects, there were a total of 375 stroke events during the follow-up period (128.7±28.1 months; 114 142 person-years). The subjects with prolonged QTc interval (hazard ratio, 2.13; 95% confidence interval, 1.22-3.73) had an increased risk of stroke even after adjustment for ECG-LVH (hazard ratio, 1.71; 95% confidence interval, 1.22-2.40). When we stratified the subjects into those with neither a prolonged QTc interval nor ECG-LVH, those with a prolonged QTc interval but without ECG-LVH, and those with ECG-LVH, multivariate-adjusted Cox proportional hazards analysis demonstrated that the subjects with prolonged QTc intervals but not ECG-LVH (1.2% of all subjects; incidence, 10.7%; hazard ratio, 2.70, 95% confidence interval, 1.48-4.94) and those with ECG-LVH (incidence, 7.9%; hazard ratio, 1.83; 95% confidence interval, 1.31-2.57) had an increased risk of stroke events, compared with those with neither a prolonged QTc interval nor ECG-LVH. In conclusion, prolonged QTc interval was associated with stroke risk even among patients without ECG-LVH in the general population. © 2014 American Heart Association, Inc.

  5. Cation-exchanged SAPO-34 for adsorption-based hydrocarbon separations: predictions from dispersion-corrected DFT calculations.

    Science.gov (United States)

    Fischer, Michael; Bell, Robert G

    2014-10-21

    The influence of the nature of the cation on the interaction of the silicoaluminophosphate SAPO-34 with small hydrocarbons (ethane, ethylene, acetylene, propane, propylene) is investigated using periodic density-functional theory calculations including a semi-empirical dispersion correction (DFT-D). Initial calculations are used to evaluate which of the guest-accessible cation sites in the chabazite-type structure is energetically preferred for a set of ten cations, which comprises four alkali metals (Li(+), Na(+), K(+), Rb(+)), three alkaline earth metals (Mg(2+), Ca(2+), Sr(2+)), and three transition metals (Cu(+), Ag(+), Fe(2+)). All eight cations that are likely to be found at the SII site (centre of a six-ring) are then included in the following investigation, which studies the interaction with the hydrocarbon guest molecules. In addition to the interaction energies, some trends and peculiarities regarding the adsorption geometries are analysed, and electron density difference plots obtained from the calculations are used to gain insights into the dominant interaction types. In addition to dispersion interactions, electrostatic and polarisation effects dominate for the main group cations, whereas significant orbital interactions are observed for unsaturated hydrocarbons interacting with transition metal (TM) cations. The differences between the interaction energies obtained for pairs of hydrocarbons of interest (such as ethylene-ethane and propylene-propane) deliver some qualitative insights: if this energy difference is large, it can be expected that the material will exhibit a high selectivity in the adsorption-based separation of alkene-alkane mixtures, which constitutes a problem of considerable industrial relevance. While the calculations show that TM-exchanged SAPO-34 materials are likely to exhibit a very high preference for alkenes over alkanes, the strong interaction may render an application in industrial processes impractical due to the large amount

  6. Ensemble Kalman filter assimilation of temperature and altimeter data with bias correction and application to seasonal prediction

    Directory of Open Access Journals (Sweden)

    C. L. Keppenne

    2005-01-01

    Full Text Available To compensate for a poorly known geoid, satellite altimeter data is usually analyzed in terms of anomalies from the time mean record. When such anomalies are assimilated into an ocean model, the bias between the climatologies of the model and data is problematic. An ensemble Kalman filter (EnKF is modified to account for the presence of a forecast-model bias and applied to the assimilation of TOPEX/Poseidon (T/P altimeter data. The online bias correction (OBC algorithm uses the same ensemble of model state vectors to estimate biased-error and unbiased-error covariance matrices. Covariance localization is used but the bias covariances have different localization scales from the unbiased-error covariances, thereby accounting for the fact that the bias in a global ocean model could have much larger spatial scales than the random error.The method is applied to a 27-layer version of the Poseidon global ocean general circulation model with about 30-million state variables. Experiments in which T/P altimeter anomalies are assimilated show that the OBC reduces the RMS observation minus forecast difference for sea-surface height (SSH over a similar EnKF run in which OBC is not used. Independent in situ temperature observations show that the temperature field is also improved. When the T/P data and in situ temperature data are assimilated in the same run and the configuration of the ensemble at the end of the run is used to initialize the ocean component of the GMAO coupled forecast model, seasonal SSH hindcasts made with the coupled model are generally better than those initialized with optimal interpolation of temperature observations without altimeter data. The analysis of the corresponding sea-surface temperature hindcasts is not as conclusive.

  7. Predicting High-School Students' Bystander Behavior in Simulated Dating Violence Situations.

    Science.gov (United States)

    Jouriles, Ernest N; Rosenfield, David; Yule, Kristen; Sargent, Kelli S; McDonald, Renee

    2016-03-01

    Dating violence among adolescents is associated with a variety of negative health consequences for victims. Bystander programs are being developed and implemented with the intention of preventing such violence, but determinants of high-school students' responsive bystander behavior remain unclear. The present study examines hypothesized determinants of high-school students' bystander behavior in simulated situations of dating violence. Participants were 80 high-school students who completed self-reports of hypothesized determinants of bystander behavior (responsibility, efficacy, and perceived benefits for intervening) at a baseline assessment. A virtual-reality paradigm was used to observationally assess bystander behavior at 1-week and 6-month assessments after baseline. Efficacy for intervening was positively associated with observed bystander behavior at the 1-week and 6-month assessments. Moreover, efficacy predicted bystander behavior over and above feelings of responsibility and perceived benefits for intervening. Contrary to our predictions, neither responsibility nor perceived benefits for intervening were associated with observed bystander behavior. This research advances our understanding of determinants of bystander behavior for high-school students and can inform prevention programming for adolescents. The study also introduces an innovative way to assess high-school students' bystander behavior. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  8. Autonomous Motivation Predicts 7-Day Physical Activity in Hong Kong Students.

    Science.gov (United States)

    Ha, Amy S; Ng, Johan Y Y

    2015-07-01

    Autonomous motivation predicts positive health behaviors such as physical activity. However, few studies have examined the relation between motivational regulations and objectively measured physical activity and sedentary behaviors. Thus, we investigated whether different motivational regulations (autonomous motivation, controlled motivation, and amotivation) predicted 7-day physical activity, sedentary behaviors, and health-related quality of life (HRQoL) of students. A total of 115 students (mean age = 11.6 years, 55.7% female) self-reported their motivational regulations and health-related quality of life. Physical activity and sedentary behaviors were measured using accelerometers for seven days. Using multilevel modeling, we found that autonomous motivation predicted higher levels of moderate-to-vigorous physical activity, less sedentary behaviors, and better HRQoL. Controlled motivation and amotivation each only negatively predicted one facet of HRQoL. Results suggested that autonomous motivation could be an important predictor of physical activity behaviors in Hong Kong students. Promotion of this form of motivational regulation may also increase HRQoL. © 2015 The International Association of Applied Psychology.

  9. The Abdominal Aortic Aneurysm Statistically Corrected Operative Risk Evaluation (AAA SCORE) for predicting mortality after open and endovascular interventions.

    Science.gov (United States)

    Ambler, Graeme K; Gohel, Manjit S; Mitchell, David C; Loftus, Ian M; Boyle, Jonathan R

    2015-01-01

    Accurate adjustment of surgical outcome data for risk is vital in an era of surgeon-level reporting. Current risk prediction models for abdominal aortic aneurysm (AAA) repair are suboptimal. We aimed to develop a reliable risk model for in-hospital mortality after intervention for AAA, using rigorous contemporary statistical techniques to handle missing data. Using data collected during a 15-month period in the United Kingdom National Vascular Database, we applied multiple imputation methodology together with stepwise model selection to generate preoperative and perioperative models of in-hospital mortality after AAA repair, using two thirds of the available data. Model performance was then assessed on the remaining third of the data by receiver operating characteristic curve analysis and compared with existing risk prediction models. Model calibration was assessed by Hosmer-Lemeshow analysis. A total of 8088 AAA repair operations were recorded in the National Vascular Database during the study period, of which 5870 (72.6%) were elective procedures. Both preoperative and perioperative models showed excellent discrimination, with areas under the receiver operating characteristic curve of .89 and .92, respectively. This was significantly better than any of the existing models (area under the receiver operating characteristic curve for best comparator model, .84 and .88; P AAA repair. These models were carefully developed with rigorous statistical methodology and significantly outperform existing methods for both elective cases and overall AAA mortality. These models will be invaluable for both preoperative patient counseling and accurate risk adjustment of published outcome data. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

  10. Prediction of internet addiction based on information literacy among students of Iran University of Medical Sciences.

    Science.gov (United States)

    Langarizadeh, Mostafa; Naghipour, Majid; Tabatabaei, Seyed Mohsen; Mirzaei, Abbas; Vaghar, Mohammad Eslami

    2018-02-01

    A considerable group of internet users consists of university users; however, despite internet benefits and capabilities, internet overuse is a threat to societies especially to young people and students. The objective of this study was to determine the predictive role of information literacy in internet addiction among students of Iran University of Medical Sciences during 2016. This analytical cross-sectional study was conducted in Iran University of Medical Sciences in 2016. Using stratified random sampling method, 365 students from different disciplines were selected. Measuring tools included the Information Literacy Questionnaire, the Yang Online Drug Addiction Scale and the General Health Questionnaire. The collected data were analyzed by Pearson product-moment correlation, independent samples t-test and multiple linear regression using SPSS version 22. According to this study, 31.2% of students had internet addiction (29.9% were mildly addicted and 1.3% had severe addiction). There was a significant and inverse relationship between higher information literacy and internet addiction (R= -0.45) and (pInformation literacy" explained 20% of the variation in the outcome variable "Internet addiction". Students play a substantial role in promoting the cultural and scientific level of knowledge in society; the higher their information literacy, the lower the level of Internet addiction, and consequently the general health of society will improve. It seems that wise planning by authorities of Iran's universities to prevent internet addiction and to increase information literacy among students is needed.

  11. Emotions in the classroom: the role of teachers' emotional intelligence ability in predicting students' achievement.

    Science.gov (United States)

    Curci, Antonietta; Lanciano, Tiziana; Soleti, Emanuela

    2014-01-01

    School days can be a difficult time, especially when students are faced with subjects that require motivational investment along with cognitive effort, such as mathematics and sciences. In the present study, we investigated the effects of teachers' emotional intelligence (El) ability, self-efficacy, and emotional states and students' self-esteem, perceptions of ability, and metacognitive beliefs in predicting school achievement. We hypothesized that the level of teacher EI ability would moderate the impact of students' self-perceptions and beliefs about their achievements in mathematics and sciences. Students from Italian junior high schools (N = 338) and their math teachers (N = 12) were involved in the study, and a multilevel approach was used. Findings showed that teachers' EI has a positive role in promoting students' achievement, by enhancing the effects of students' self-perceptions of ability and self-esteem.These results have implications for the implementation of intervention programs on the emotional, motivational, and metacognitive correlates of studying and learning behavior.

  12. Diagnostic value of thallium-201 myocardial perfusion IQ-SPECT without and with computed tomography-based attenuation correction to predict clinically significant and insignificant fractional flow reserve

    Science.gov (United States)

    Tanaka, Haruki; Takahashi, Teruyuki; Ohashi, Norihiko; Tanaka, Koichi; Okada, Takenori; Kihara, Yasuki

    2017-01-01

    Abstract The aim of this study was to clarify the predictive value of fractional flow reserve (FFR) determined by myocardial perfusion imaging (MPI) using thallium (Tl)-201 IQ-SPECT without and with computed tomography-based attenuation correction (CT-AC) for patients with stable coronary artery disease (CAD). We assessed 212 angiographically identified diseased vessels using adenosine-stress Tl-201 MPI-IQ-SPECT/CT in 84 consecutive, prospectively identified patients with stable CAD. We compared the FFR in 136 of the 212 diseased vessels using visual semiquantitative interpretations of corresponding territories on MPI-IQ-SPECT images without and with CT-AC. FFR inversely correlated most accurately with regional summed difference scores (rSDS) in images without and with CT-AC (r = −0.584 and r = −0.568, respectively, both P system can predict FFR at an optimal cut-off of <0.80, and we propose a novel application of CT-AC to MPI-IQ-SPECT for predicting clinically significant and insignificant FFR even in nonobese patients. PMID:29390486

  13. Corrections to primordial nucleosynthesis

    International Nuclear Information System (INIS)

    Dicus, D.A.; Kolb, E.W.; Gleeson, A.M.; Sudarshan, E.C.G.; Teplitz, V.L.; Turner, M.S.

    1982-01-01

    The changes in primordial nucleosynthesis resulting from small corrections to rates for weak processes that connect neutrons and protons are discussed. The weak rates are corrected by improved treatment of Coulomb and radiative corrections, and by inclusion of plasma effects. The calculations lead to a systematic decrease in the predicted 4 He abundance of about ΔY = 0.0025. The relative changes in other primoridal abundances are also 1 to 2%

  14. The Role of Depression and Attachment Styles in Predicting Students? Addiction to Cell Phones

    OpenAIRE

    Ghasempour, Abdollah; Mahmoodi-Aghdam, Mansour

    2015-01-01

    Background The present study aimed at investigating the role of depression and attachment styles in predicting cell phone addiction. Methods In this descriptive correlational study, a sample including 100 students of Payame Noor University (PNU), Reyneh Center, Iran, in the academic year of 2013-2014 was selected using volunteer sampling. Participants were asked to complete the adult attachment inventory (AAI), Beck depression inventory-13 (BDI-13) and the cell phone overuse scale (COS). Find...

  15. Predicting Student Success on the Texas Chemistry STAAR Test: A Logistic Regression Analysis

    Science.gov (United States)

    Johnson, William L.; Johnson, Annabel M.; Johnson, Jared

    2012-01-01

    Background: The context is the new Texas STAAR end-of-course testing program. Purpose: The authors developed a logistic regression model to predict who would pass-or-fail the new Texas chemistry STAAR end-of-course exam. Setting: Robert E. Lee High School (5A) with an enrollment of 2700 students, Tyler, Texas. Date of the study was the 2011-2012…

  16. Safety, efficacy, and predictability of laser in situ keratomileusis to correct myopia or myopic astigmatism with a 750 Hz scanning-spot laser system.

    Science.gov (United States)

    Tomita, Minoru; Watabe, Miyuki; Yukawa, Satoshi; Nakamura, Nobuo; Nakamura, Tadayuki; Magnago, Thomas

    2014-02-01

    To evaluate the clinical outcomes of laser in situ keratomileusis (LASIK) to correct myopia or myopic astigmatism using the Amaris 750S 750 Hz excimer laser. Private LASIK center, Tokyo, Japan. Case series. Patients with myopia or myopic astigmatism (spherical equivalent -0.50 to -11.63 diopters [D]), a corrected distance visual acuity (CDVA) of 20/20 or better, and an estimated residual bed thickness of 300 μm or more had LASIK using the aspheric aberration-free ablation profile of the 750 Hz scanning-spot laser and the Femto LDV Crystal Line femtosecond laser for flap creation. Study parameters included uncorrected distance visual acuity (UDVA), CDVA, manifest refraction, astigmatism, and higher-order aberrations (HOAs). The study included 1280 eyes (685 patients). At 3 months, 96.6% of eyes had a UDVA of 20/20 or better and 99.1% had 20/32 or better; 94.1% of eyes were within ± 0.50 D of the intended correction and 98.9% were within ± 1.00 D; 89.7% of eyes had no residual cylinder and 96.0% had a postoperative astigmatism of less than 0.50 D. All eyes had a postoperative CDVA of 20/20 or better. The HOAs increased postoperatively (PLaser in situ keratomileusis with the 750 Hz scanning-spot laser was safe, effective, and predictable. No specific clinical side effects that might be associated with a high repetition rate occurred. Mr. Magnago is an employee of Schwind eye-tech-solutions GmbH. No other author has a financial or proprietary interest in any material or method mentioned. Copyright © 2013 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

  17. Energy Drinks and Binge Drinking Predict College Students' Sleep Quantity, Quality, and Tiredness.

    Science.gov (United States)

    Patrick, Megan E; Griffin, Jamie; Huntley, Edward D; Maggs, Jennifer L

    2018-01-01

    This study examines whether energy drink use and binge drinking predict sleep quantity, sleep quality, and next-day tiredness among college students. Web-based daily data on substance use and sleep were collected across four semesters in 2009 and 2010 from 667 individuals for up to 56 days each, yielding information on 25,616 person-days. Controlling for average levels of energy drink use and binge drinking (i.e., 4+ drinks for women, 5+ drinks for men), on days when students consumed energy drinks, they reported lower sleep quantity and quality that night, and greater next-day tiredness, compared to days they did not use energy drinks. Similarly, on days when students binge drank, they reported lower sleep quantity and quality that night, and greater next-day tiredness, compared to days they did not binge drink. There was no significant interaction effect between binge drinking and energy drink use on the outcomes.

  18. [Willingness of Students of Economics to Pay for Predictive Oncological Genetic Testing - An Empirical Analysis].

    Science.gov (United States)

    Siol, V; Lange, A; Prenzler, A; Neubauer, S; Frank, M

    2017-05-01

    Objectives: The present study aims to investigate the interest of young adults in predictive oncological genetic testing and their willingness to pay for such a test. Furthermore, major determinants of the 2 variables of interest were identified. Methods: 348 students of economics from the Leibniz University of Hanover were queried in July 2013 using an extensive questionnaire. Among other things, the participants were asked if they are interested in information about the probability to develop cancer in the future and their willingness to pay for such information. Data were analysed using descriptive statistics and ordinal probit regressions. Additionally marginal effects were calculated. Results: About 50% of the students were interested in predictive oncological genetic testing and were willing to pay for the test. Moreover, the participants who were willing to pay for the test partly attach high monetary values to the information that could so be obtained. The study shows that the interest of the students and their willingness to pay were primarily influenced by individual attitudes and perceptions. Conclusions: The study proves that young adults were interested in predictive genetic testing and appreciate information about their probability of develop cancer someday. © Georg Thieme Verlag KG Stuttgart · New York.

  19. Dark Triad Personality and Wisdom in Prediction of Students' Academic Self-Efficacy

    Directory of Open Access Journals (Sweden)

    Sajjad Saadat

    2018-01-01

    Full Text Available Introduction: A number of studies have argued that students' academic self-efficacy is affected by various factors. This study investigates the role of the dark triad personality and wisdom on the Iranian students' academic self-efficacy. Methods: In this correlational study, 177 (84 female and 93 male students of the University of Isfahan aged 18-54 years old (M = 23.1, SD = 4.9 were selected. Total academic mean range of the participants was 10 to 20 (M = 16.4, SD = 1.6. Participants completed the College Academic Self-Efficacy Scale, The Dark Triad Dirty Dozen, and Three-dimensional wisdom scales. Results: Results showed that there was a negative relationship between the variables of Machiavellianism and psychopathy and academic self-efficacy; inversely, there was a positive relationship between variables of cognitive and reflective wisdom and academic self-efficacy. Reflective wisdom, narcissism, and Machiavellianism predicted 0.17% of the self-efficacy. Conclusion: The results of the present study supported the importance of the dark triad personality and wisdom, as the variables, which were able to predict the academic self-efficacy of the students.

  20. School Maladjustment and External Locus of Control Predict the Daytime Sleepiness of College Students With ADHD.

    Science.gov (United States)

    Langberg, Joshua M; Dvorsky, Melissa R; Becker, Stephen P; Molitor, Stephen J

    2016-09-01

    The primary aim of this study was to evaluate whether school maladjustment longitudinally predicts the daytime sleepiness of college students with ADHD above and beyond symptoms of ADHD and to determine whether internalizing dimensions mediate the relationship between maladjustment and sleepiness. A prospective longitudinal study of 59 college students comprehensively diagnosed with ADHD who completed ratings at the beginning, middle, and end of the school year. School maladjustment at the beginning of the year significantly predicted daytime sleepiness at the end of the year above and beyond symptoms of ADHD. Locus of control mediated the relationship between maladjustment and daytime sleepiness. The significant school maladjustment difficulties that students with ADHD experience following the transition to college may lead to the development of problems with daytime sleepiness, particularly for those students with high external locus of control. This pattern is likely reciprocal, whereby sleep problems in turn result in greater school impairment, reinforcing the idea that life events are outside of one's control. © The Author(s) 2014.

  1. Predictive validity of the personal qualities assessment for selection of medical students in Scotland.

    Science.gov (United States)

    Dowell, Jon; Lumsden, Mary Ann; Powis, David; Munro, Don; Bore, Miles; Makubate, Boikanyo; Kumwenda, Ben

    2011-01-01

    The Personal Qualities Assessment (PQA) was developed to enhance medical student selection by measuring a range of non-cognitive attributes in the applicants to medical school. Applicants to the five Scottish medical schools were invited to pilot the test in 2001 and 2002. To evaluate the predictive validity of PQA for selecting medical students. A longitudinal cohort study was conducted in which PQA scores were compared with senior year medical school performance. Consent to access performance markers was obtained from 626 students (61.6% of 1017 entrants in 2002-2003). Linkable Foundation Year (4th) rankings were available for 411 (66%) students and objective structured clinical examination (OSCE) rankings for 335 (54%) of those consenting. Both samples were representative of the original cohort. No significant correlations were detected between separate elements of the PQA assessment and student performance. However, using the algorithm advocated by Powis et al. those defined as 'non-extreme' (libertarian-communitarian moral orientation scales were ranked higher in OSCEs (average of 7.5% or 25 out of 335, p = 0.049). This study was limited by high attrition and basic outcome markers which are insensitive to relevant non-cognitive characteristics. However, it is the largest currently available study of predictive validity for the PQA assessment. There was one finding of significance: that those students who were identified by PQA as 'not extreme' on the two personal characteristics scales performed better in an OSCE measure of professionalism. Futures studies are required since psychometric testing for both cognitive and non-cognitive attributes are increasingly used in admission process and these should include more and better measures of professionalism against which to correlate non-cognitive traits.

  2. Can learning style predict student satisfaction with different instruction methods and academic achievement in medical education?

    Science.gov (United States)

    Gurpinar, Erol; Alimoglu, Mustafa Kemal; Mamakli, Sumer; Aktekin, Mehmet

    2010-12-01

    The curriculum of our medical school has a hybrid structure including both traditional training (lectures) and problem-based learning (PBL) applications. The purpose of this study was to determine the learning styles of our medical students and investigate the relation of learning styles with each of satisfaction with different instruction methods and academic achievement in them. This study was carried out with the participation of 170 first-year medical students (the participation rate was 91.4%). The researchers prepared sociodemographic and satisfaction questionnaires to determine the characteristics of the participants and their satisfaction levels with traditional training and PBL. The Kolb learning styles inventory was used to explore the learning styles of the study group. The participants completed all forms at the end of the first year of medical education. Indicators of academic achievement were scores of five theoretical block exams and five PBL exams performed throughout the academic year of 2008-2009. The majority of the participants took part in the "diverging" (n = 84, 47.7%) and "assimilating" (n = 73, 41.5%) groups. Numbers of students in the "converging" and "accommodating" groups were 11 (6.3%) and 8 (4.5%), respectively. In all learning style groups, PBL satisfaction scores were significantly higher than those of traditional training. Exam scores for "PBL and traditional training" did not differ among the four learning styles. In logistic regression analysis, learning style (assimilating) predicted student satisfaction with traditional training and success in theoretical block exams. Nothing predicted PBL satisfaction and success. This is the first study conducted among medical students evaluating the relation of learning style with student satisfaction and academic achievement. More research with larger groups is needed to generalize our results. Some learning styles may relate to satisfaction with and achievement in some instruction methods.

  3. Sitting and standing postures are corrected by adjustable furniture with lowered muscle tension in high-school students.

    Science.gov (United States)

    Koskelo, R; Vuorikari, K; Hänninen, O

    2007-10-01

    This study compared the effect of 24 months of adjustable school desks and chairs usage (the intervention) and traditional non-adjustable usage (the control condition) on sitting and standing postures, muscle strength, classroom muscle tension, pain and learning in 15 (8 female and 7 male) high-school students and 15 anthropometrically and gender matched control students from neighbouring schools. It was assessed whether any responses took place after growth cessation. In comparison with controls, the intervention group of students' sitting postures standing kyphosis, scoliosis and lordosis became significantly better, both before and after growth cessation. Trunk muscle strength increased in the intervention students whose muscle tension during classes fell significantly in the trapezius and lumbar muscles, whereas in control students' lumbar tension increased. Headache and low-back pain correlated with neck-shoulder pain and trapezius muscle tension. Intervention students reported that they experienced benefits from the adjustable tables and chairs. They also received significantly better overall marks than the controls at the end of high school. It is concluded that the adjustable school desks and chairs promoted better sitting and standing postures, increased muscle strength, alleviated pain and appeared to be associated with better overall academic marks.

  4. Improved Fuzzy Modelling to Predict the Academic Performance of Distance Education Students

    Directory of Open Access Journals (Sweden)

    Osman Yildiz

    2013-12-01

    Full Text Available It is essential to predict distance education students’ year-end academic performance early during the course of the semester and to take precautions using such prediction-based information. This will, in particular, help enhance their academic performance and, therefore, improve the overall educational quality. The present study was on the development of a mathematical model intended to predict distance education students’ year-end academic performance using the first eight-week data on the learning management system. First, two fuzzy models were constructed, namely the classical fuzzy model and the expert fuzzy model, the latter being based on expert opinion. Afterwards, a gene-fuzzy model was developed optimizing membership functions through genetic algorithm. The data on distance education were collected through Moodle, an open source learning management system. The data were on a total of 218 students who enrolled in Basic Computer Sciences in 2012. The input data consisted of the following variables: When a student logged on to the system for the last time after the content of a lesson was uploaded, how often he/she logged on to the system, how long he/she stayed online in the last login, what score he/she got in the quiz taken in Week 4, and what score he/she got in the midterm exam taken in Week 8. A comparison was made among the predictions of the three models concerning the students’ year-end academic performance.

  5. TU-G-BRA-05: Predicting Volume Change of the Tumor and Critical Structures Throughout Radiation Therapy by CT-CBCT Registration with Local Intensity Correction

    Energy Technology Data Exchange (ETDEWEB)

    Park, S; Robinson, A; Kiess, A; Quon, H; Wong, J; Lee, J [Johns Hopkins University, Baltimore, MD (United States); Plishker, W [IGI Technologies Inc., College Park, MD (United States); Shekhar, R [IGI Technologies Inc., College Park, MD (United States); Children’s National Medical Center, Washington, D.C. (United States)

    2015-06-15

    Purpose: The purpose of this study is to develop an accurate and effective technique to predict and monitor volume changes of the tumor and organs at risk (OARs) from daily cone-beam CTs (CBCTs). Methods: While CBCT is typically used to minimize the patient setup error, its poor image quality impedes accurate monitoring of daily anatomical changes in radiotherapy. Reconstruction artifacts in CBCT often cause undesirable errors in registration-based contour propagation from the planning CT, a conventional way to estimate anatomical changes. To improve the registration and segmentation accuracy, we developed a new deformable image registration (DIR) that iteratively corrects CBCT intensities using slice-based histogram matching during the registration process. Three popular DIR algorithms (hierarchical B-spline, demons, optical flow) augmented by the intensity correction were implemented on a graphics processing unit for efficient computation, and their performances were evaluated on six head and neck (HN) cancer cases. Four trained scientists manually contoured nodal gross tumor volume (GTV) on the planning CT and every other fraction CBCTs for each case, to which the propagated GTV contours by DIR were compared. The performance was also compared with commercial software, VelocityAI (Varian Medical Systems Inc.). Results: Manual contouring showed significant variations, [-76, +141]% from the mean of all four sets of contours. The volume differences (mean±std in cc) between the average manual segmentation and four automatic segmentations are 3.70±2.30(B-spline), 1.25±1.78(demons), 0.93±1.14(optical flow), and 4.39±3.86 (VelocityAI). In comparison to the average volume of the manual segmentations, the proposed approach significantly reduced the estimation error by 9%(B-spline), 38%(demons), and 51%(optical flow) over the conventional mutual information based method (VelocityAI). Conclusion: The proposed CT-CBCT registration with local CBCT intensity correction

  6. Examination of factors predicting secondary students' interest in tertiary STEM education

    Science.gov (United States)

    Chachashvili-Bolotin, Svetlana; Milner-Bolotin, Marina; Lissitsa, Sabina

    2016-02-01

    Based on the Social Cognitive Career Theory (SCCT), the study aims to investigate factors that predict students' interest in pursuing science, technology, engineering, and mathematics (STEM) fields in tertiary education both in general and in relation to their gender and socio-economic background. The results of the analysis of survey responses of 2458 secondary public school students in the fifth-largest Israeli city indicate that STEM learning experience positively associates with students' interest in pursuing STEM fields in tertiary education as opposed to non-STEM fields. Moreover, studying advanced science courses at the secondary school level decreases (but does not eliminate) the gender gap and eliminates the effect of family background on students' interest in pursuing STEM fields in the future. Findings regarding outcome expectations and self-efficacy beliefs only partially support the SCCT model. Outcome expectations and self-efficacy beliefs positively correlate with students' entering tertiary education but did not differentiate between their interests in the fields of study.

  7. Predicting Students' Skills in the Context of Scientific Inquiry with Cognitive, Motivational, and Sociodemographic Variables

    Science.gov (United States)

    Nehring, Andreas; Nowak, Kathrin H.; Belzen, Annette Upmeier zu; Tiemann, Rüdiger

    2015-06-01

    Research on predictors of achievement in science is often targeted on more traditional content-based assessments and single student characteristics. At the same time, the development of skills in the field of scientific inquiry constitutes a focal point of interest for science education. Against this background, the purpose of this study was to investigate to which extent multiple student characteristics contribute to skills of scientific inquiry. Based on a theoretical framework describing nine epistemological acts, we constructed and administered a multiple-choice test that assesses these skills in lower and upper secondary school level (n = 780). The test items contained problem-solving situations that occur during chemical investigations in school and had to be solved by choosing an appropriate inquiry procedure. We collected further data on 12 cognitive, motivational, and sociodemographic variables such as conceptual knowledge, enjoyment of chemistry, or language spoken at home. Plausible values were drawn to quantify students' inquiry skills. The results show that students' characteristics predict their inquiry skills to a large extent (55%), whereas 9 out of 12 variables contribute significantly on a multivariate level. The influence of sociodemographic traits such as gender or the social background becomes non-significant after controlling for cognitive and motivational variables. Furthermore, the performance advance of students from upper secondary school level can be explained by controlling for cognitive covariates. We discuss our findings with regard to curricular aspects and raise the question whether the inquiry skills can be considered as an autonomous trait in science education research.

  8. Developing a study aptitude test for international distance education students of geoinformation science and earth observation

    NARCIS (Netherlands)

    Pasha Zadeh Monajjemi, P.; Augustijn-Beckers, Petronella; Verkroost, M.J.; Sarjakoski, Tapani; Santos, Maribel Yasmina; Sarjakoski, L. Tiina

    2016-01-01

    Online diagnostic study aptitude tests are a common means of helping students select the correct type of course, and the correct mode of education. However, universities often lack the data to predict critical student success factors correctly. In this paper we discuss the development of an online

  9. Exploring students' perceptions and performance on predict-observe-explain tasks in high school chemistry laboratory

    Science.gov (United States)

    Vadapally, Praveen

    This study sought to understand the impact of gender and reasoning level on students' perceptions and performances of Predict-Observe-Explain (POE) laboratory tasks in a high school chemistry laboratory. Several literature reviews have reported that students at all levels have not developed the specific knowledge and skills that were expected from their laboratory work. Studies conducted over the last several decades have found that boys tend to be more successful than girls in science and mathematics courses. However, some recent studies have suggested that girls may be reducing this gender gap. This gender difference is the focal point of this research study, which was conducted at a mid-western, rural high school. The participants were 24 boys and 25 girls enrolled in two physical science classes taught by the same teacher. In this mixed methods study, qualitative and quantitative methods were implemented simultaneously over the entire period of the study. MANOVA statistics revealed significant effects due to gender and level of reasoning on the outcome variables, which were POE performances and perceptions of the chemistry laboratory environment. There were no significant interactions between these effects. For the qualitative method, IRB-approved information was collected, coded, grouped, and analyzed. This method was used to derive themes from students' responses on questionnaires and semi-structured interviews. Students with different levels of reasoning and gender were interviewed, and many of them expressed positive themes, which was a clear indication that they had enjoyed participating in the POE learning tasks and they had developed positive perceptions towards POE inquiry laboratory learning environment. When students are capable of formal reasoning, they can use an abstract scientific concept effectively and then relate it to the ideas they generate in their minds. Thus, instructors should factor the nature of students' thinking abilities into their

  10. A Big Data Approach for Situation-Aware estimation, correction and prediction of aerosol effects, based on MODIS Joint Atmosphere product (collection 6) time series data

    Science.gov (United States)

    Singh, A. K.; Toshniwal, D.

    2017-12-01

    The MODIS Joint Atmosphere product, MODATML2 and MYDATML2 L2/3 provided by LAADS DAAC (Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center) re-sampled from medium resolution MODIS Terra /Aqua Satellites data at 5km scale, contains Cloud Reflectance, Cloud Top Temperature, Water Vapor, Aerosol Optical Depth/Thickness, Humidity data. These re-sampled data, when used for deriving climatic effects of aerosols (particularly in case of cooling effect) still exposes limitations in presence of uncertainty measures in atmospheric artifacts such as aerosol, cloud, cirrus cloud etc. The effect of uncertainty measures in these artifacts imposes an important challenge for estimation of aerosol effects, adequately affecting precise regional weather modeling and predictions: Forecasting and recommendation applications developed largely depend on these short-term local conditions (e.g. City/Locality based recommendations to citizens/farmers based on local weather models). Our approach inculcates artificial intelligence technique for representing heterogeneous data(satellite data along with air quality data from local weather stations (i.e. in situ data)) to learn, correct and predict aerosol effects in the presence of cloud and other atmospheric artifacts, defusing Spatio-temporal correlations and regressions. The Big Data process pipeline consisting correlation and regression techniques developed on Apache Spark platform can easily scale for large data sets including many tiles (scenes) and over widened time-scale. Keywords: Climatic Effects of Aerosols, Situation-Aware, Big Data, Apache Spark, MODIS Terra /Aqua, Time Series

  11. Student nurse selection and predictability of academic success: The Multiple Mini Interview project.

    Science.gov (United States)

    Gale, Julia; Ooms, Ann; Grant, Robert; Paget, Kris; Marks-Maran, Di

    2016-05-01

    With recent reports of public enquiries into failure to care, universities are under pressure to ensure that candidates selected for undergraduate nursing programmes demonstrate academic potential as well as characteristics and values such as compassion, empathy and integrity. The Multiple Mini Interview (MMI) was used in one university as a way of ensuring that candidates had the appropriate numeracy and literacy skills as well as a range of communication, empathy, decision-making and problem-solving skills as well as ethical insights and integrity, initiative and team-work. To ascertain whether there is evidence of bias in MMIs (gender, age, nationality and location of secondary education) and to determine the extent to which the MMI is predictive of academic success in nursing. A longitudinal retrospective analysis of student demographics, MMI data and the assessment marks for years 1, 2 and 3. One university in southwest London. One cohort of students who commenced their programme in September 2011, including students in all four fields of nursing (adult, child, mental health and learning disability). Inferential statistics and a Bayesian Multilevel Model. MMI in conjunction with MMI numeracy test and MMI literacy test shows little or no bias in terms of ages, gender, nationality or location of secondary school education. Although MMI in conjunction with numeracy and literacy testing is predictive of academic success, it is only weakly predictive. The MMI used in conjunction with literacy and numeracy testing appears to be a successful technique for selecting candidates for nursing. However, other selection methods such as psychological profiling or testing of emotional intelligence may add to the extent to which selection methods are predictive of academic success on nursing. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Perceived Academic Control and Academic Emotions Predict Undergraduate University Student Success: Examining Effects on Dropout Intention and Achievement.

    Science.gov (United States)

    Respondek, Lisa; Seufert, Tina; Stupnisky, Robert; Nett, Ulrike E

    2017-01-01

    The present study addressed concerns over the high risk of university students' academic failure. It examined how perceived academic control and academic emotions predict undergraduate students' academic success, conceptualized as both low dropout intention and high achievement (indicated by GPA). A cross-sectional survey was administered to 883 undergraduate students across all disciplines of a German STEM orientated university. The study additionally compared freshman students ( N = 597) vs. second-year students ( N = 286). Using structural equation modeling, for the overall sample of undergraduate students we found that perceived academic control positively predicted enjoyment and achievement, as well as negatively predicted boredom and anxiety. The prediction of dropout intention by perceived academic control was fully mediated via anxiety. When taking perceived academic control into account, we found no specific impact of enjoyment or boredom on the intention to dropout and no specific impact of all three academic emotions on achievement. The multi-group analysis showed, however, that perceived academic control, enjoyment, and boredom among second-year students had a direct relationship with dropout intention. A major contribution of the present study was demonstrating the important roles of perceived academic control and anxiety in undergraduate students' academic success. Concerning corresponding institutional support and future research, the results suggested distinguishing incoming from advanced undergraduate students.

  13. Pop Rocks! Engaging first-year geology students by deconstructing and correcting scientific misconceptions in popular culture. A Practice Report

    Directory of Open Access Journals (Sweden)

    Leslie Almberg

    2011-07-01

    Full Text Available Popular culture abounds with ill-conceived notions about Earth’s processes.  Movies, books, music, television and even video games frequently misrepresent fundamental scientific principles, warping viewers’ perceptions of the world around them.  First year geoscience students are not immune to pop culture’s portrayal of earth science and the misconceptions they bring to Geology 101 cloud their ability to differentiate between fact and fiction.  Working within an action research context, a semester-long assessment was designed with the intent to highlight and subsequently challenge students’ misconceptions using examples of “bad geoscience” from pop culture.  Students were required to practice and refine generic skills within this context.  This project succeeded in engaging students, but requires refinement to become more effective in enhancing their geoscience literacy. 

  14. Hope of Success and Fear of Failure Predicting Academic Procrastination Students Who Working on a Thesis

    Directory of Open Access Journals (Sweden)

    Sari Zakiah Akmal

    2017-08-01

    Full Text Available Students, who are working on the thesis, have some difficulties caused by internal and external factors. Those problems can disrupt the completion of their thesis, such as the tendency to do academic procrastination. Increasing achievement motivation can reduce academic procrastination. This study aims to look at the role of achievement motivation (hope of success and fear of failure in predicting academic procrastination. The study used a quantitative approach by distributing academic procrastination and achievement motivation questionnaires. The study involved 182 students who were working on a thesis as samples, which were obtained by using accidental sampling technique. Data were analyzed using multiple regressions. It showed that the hope of success and fear of failure have a significant role in predicting academic procrastination (R2 = 13.8%, F = 14,356, p <0.05. The hope of success can decrease academic procrastination, while fear of failure can improve it. Thus, interventions to reduce academic procrastination can be delivered by increasing students hope of success.

  15. Role of Personality Traits, Learning Styles and Metacognition in Predicting Critical Thinking of Undergraduate Students

    Directory of Open Access Journals (Sweden)

    Soliemanifar O

    2015-04-01

    The aim of this study was to investigate the role of personality traits, learning styles and metacognition in predicting critical thinking. Instrument & Methods: In this descriptive correlative study, 240 students (130 girls and 110 boys of Ahvaz Shahid Chamran University were selected by multi-stage random sampling method. The instruments for collecting data were NEO Five-Factor Inventory, learning style inventory of Kolb (LSI, metacognitive assessment inventory (MAI of Schraw & Dennison (1994 and California Critical Thinking Skills Test (CCTST. The data were analyzed using Pearson correlation coefficient, stepwise regression analysis and Canonical correlation analysis.  Findings: Openness to experiment (b=0.41, conscientiousness (b=0.28, abstract conceptualization (b=0.39, active experimentation (b=0.22, reflective observation (b=0.12, knowledge of cognition (b=0.47 and regulation of cognition (b=0.29 were effective in predicting critical thinking. Openness to experiment and conscientiousness (r2=0.25, active experimentation, abstract conceptualization and reflective observation learning styles (r2=0.21 and knowledge and regulation of cognition metacognitions (r2=0.3 had an important role in explaining critical thinking. The linear combination of critical thinking skills (evaluation, analysis, inference was predictable by a linear combination of dispositional-cognitive factors (openness, conscientiousness, abstract conceptualization, active experimentation, knowledge of cognition and regulation of cognition. Conclusion: Personality traits, learning styles and metacognition, as dispositional-cognitive factors, play a significant role in students' critical thinking.

  16. Thinking while drinking: Fear of negative evaluation predicts drinking behaviors of students with social anxiety.

    Science.gov (United States)

    Villarosa-Hurlocker, Margo C; Whitley, Robert B; Capron, Daniel W; Madson, Michael B

    2018-03-01

    College students with social anxiety disorder experience more alcohol-related negative consequences, regardless of the amount of alcohol they consume. Social anxiety refers to psychological distress and physiological arousal in social situations due to an excessive fear of negative evaluation by others. The current study examined within-group differences in alcohol-related negative consequences of students who met or exceeded clinically-indicated social anxiety symptoms. In particular, we tested a sequential mediation model of the cognitive (i.e., fear of negative evaluation) and behavioral (protective behavioral strategies) mechanisms for the link between social anxiety disorder subtypes (i.e., interaction and performance-type) and alcohol-related negative consequences. Participants were 412 traditional-age college student drinkers who met or exceeded the clinically-indicated threshold for social anxiety disorder and completed measures of fear of negative evaluation, protective behavioral strategies (controlled consumption and serious harm reduction), and alcohol-related negative consequences. Fear of negative evaluation and serious harm reduction strategies sequentially accounted for the relationship between interaction social anxiety disorder and alcohol-related negative consequences, such that students with more severe interaction social anxiety symptoms reported more fear of negative evaluation, which was related to more serious harm reduction strategies, which predicted fewer alcohol-related negative consequences. Future directions and implications are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. The Prediction of the Students' Academic Underachievement in Mathematics Using the DEA Model: A Developing Country Case Study

    Science.gov (United States)

    Moradi, Fatemeh; Amiripour, Parvaneh

    2017-01-01

    In this study, an attempt was made to predict the students' mathematical academic underachievement at the Islamic Azad University-Yadegare-Imam branch and the appropriate strategies in mathematical academic achievement to be applied using the Data Envelopment Analysis (DEA) model. Survey research methods were used to select 91 students from the…

  18. Home Away Home: Better Understanding of the Role of Social Support in Predicting Cross-Cultural Adjustment among International Students

    Science.gov (United States)

    Baba, Yoko; Hosoda, Megumi

    2014-01-01

    Numerous studies have examined international students' adjustment problems, yet, these studies have not explored the mechanisms through which social support operates in the context of stressful events in predicting cross-cultural adjustment among international students. Using Barrera's (1988) models of social support, the present study…

  19. Academic Motivation and Approaches to Learning in Predicting College Students' Academic Achievement: Findings from Turkish and US Samples

    Science.gov (United States)

    Çetin, Baris

    2015-01-01

    The aim of this study is to determine if approaches to learning and academic motivation together predict grade point averages (GPAs) of students who study at Primary School Education and Preschool Education in Turkey and of students who study at Early Childhood Education in the US. The first group of participants included 166 third- and…

  20. Using Self-Determination of Senior College Students with Disabilities to Predict Their Quality of Life One Year after Graduation

    Science.gov (United States)

    Chao, Pen-Chiang

    2018-01-01

    The purpose of this study was to assess the correlation and predictive relationship between self-determination and quality of life of college students with disabilities. Subjects were 145 senior college students recruited from northern Taiwan. Subjects' age ranged from 22 to 25 years and their disabilities varied, including visual impairments (n =…

  1. Academic Performance of First-Year Students at a College of Pharmacy in East Tennessee: Models for Prediction

    Science.gov (United States)

    Clavier, Cheri Whitehead

    2013-01-01

    With the increase of students applying to pharmacy programs, it is imperative that admissions committees choose appropriate measures to analyze student readiness. The purpose of this research was to identify significant factors that predict the academic performance, defined as grade point average (GPA) at the end of the first professional year, of…

  2. Factors Affecting Retention Behavior: A Model To Predict At-Risk Students. AIR 1997 Annual Forum Paper.

    Science.gov (United States)

    Sadler, William E.; Cohen, Frederic L.; Kockesen, Levent

    This paper describes a methodology used in an on-going retention study at New York University (NYU) to identify a series of easily measured factors affecting student departure decisions. Three logistic regression models for predicting student retention were developed, each containing data available at three distinct times during the first…

  3. Considering High School Students' Experience in Asynchronous and Synchronous Distance Learning Environments: QoE Prediction Model

    Science.gov (United States)

    Malinovski, Toni; Vasileva, Marina; Vasileva-Stojanovska, Tatjana; Trajkovik, Vladimir

    2014-01-01

    Early identification of relevant factors that influence students' experiences is vitally important to the educational process since they play an important role in learning outcomes. The purpose of this study is to determine underlying constructs that predict high school students' subjective experience and quality expectations during asynchronous…

  4. Predicting the "Freshman 15": Environmental and Psychological Predictors of Weight Gain in First-Year University Students

    Science.gov (United States)

    Vella-Zarb, Rachel A.; Elgar, Frank J.

    2010-01-01

    Objectives: (1) To investigate weight gain in first-year university students; and (2) to examine whether environmental and psychological factors, specifically accommodation and stress, predict weight gain. Methods: Eighty-four first-year university students (77 per cent female) were weighed and completed the Perceived Stress Scale (Cohen, Kamarck…

  5. Combining University Student Self-Regulated Learning Indicators and Engagement with Online Learning Events to Predict Academic Performance

    Science.gov (United States)

    Pardo, Abelardo; Han, Feifei; Ellis, Robert A.

    2017-01-01

    Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…

  6. Predicting High School Student Use of Learning Strategies: The Role of Preferred Learning Styles and Classroom Climate

    Science.gov (United States)

    Cheema, Jehanzeb; Kitsantas, Anastasia

    2016-01-01

    This study investigated the predictiveness of preferred learning styles (competitive and cooperative) and classroom climate (teacher support and disciplinary climate) on learning strategy use in mathematics. The student survey part of the Programme for International Student Assessment 2003 comprising of 4633 US observations was used in a weighted…

  7. Effects of Motivation, Academic Stress and Age in Predicting Self-Directed Learning Readiness (SDLR): Focused on Online College Students

    Science.gov (United States)

    Heo, JeongChul; Han, Sumi

    2018-01-01

    The purpose of this study is to determine whether the self-directed learning readiness (SDLR) among online students might be significantly predicted by motivation, academic stress, and age. To complete the purpose of this study, the Pearson correlation and multiple-regression are analyzed. The participants for this study are college students who…

  8. Comparing the Factors That Predict Completion and Grades among For-Credit and Open/MOOC Students in Online Learning

    Science.gov (United States)

    Almeda, Ma. Victoria; Zuech, Joshua; Utz, Chris; Higgins, Greg; Reynolds, Rob; Baker, Ryan S.

    2018-01-01

    Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…

  9. Coping Styles, Social Support, Relational Self-Construal, and Resilience in Predicting Students' Adjustment to University Life

    Science.gov (United States)

    Rahat, Enes; Ilhan, Tahsin

    2016-01-01

    The purpose of the present study is to investigate how well coping styles, social support, relational self-construal, and resilience characteristics predict first year university students' ability to adjust to university life. Participants consisted of 527 at-risk students attending a state university in Turkey. The Personal Information Form, Risk…

  10. The fairness, predictive validity and acceptability of multiple mini interview in an internationally diverse student population- a mixed methods study

    OpenAIRE

    Kelly, Maureen E.; Dowell, Jon; Husbands, Adrian; Newell, John; O'Flynn, Siun; Kropmans, Thomas; Dunne, Fidelma P.; Murphy, Andrew W.

    2014-01-01

    Background International medical students, those attending medical school outside of their country of citizenship, account for a growing proportion of medical undergraduates worldwide. This study aimed to establish the fairness, predictive validity and acceptability of Multiple Mini Interview (MMI) in an internationally diverse student population. Methods This was an explanatory sequential, mixed methods study. All students in First Year Medicine, National University of Ireland Galway 2012 we...

  11. Perceived parenting and social support: can they predict academic achievement in Argentinean college students?

    OpenAIRE

    de la Iglesia, Guadalupe; Freiberg Hoffmann, Agustin; Fernández Liporace, Mercedes

    2014-01-01

    Guadalupe de la Iglesia,1,2 Agustin Freiberg Hoffmann,2 Mercedes Fernández Liporace1,2 1National Council of Scientific and Technical Research (CONICET), 2University of Buenos Aires, Buenos Aires, Argentina Abstract: The aim of this study was to test the ability to predict academic achievement through the perception of parenting and social support in a sample of 354 Argentinean college students. Their mean age was 23.50 years (standard deviation =2.62 years) and most of them (83.3%...

  12. Pop Rocks! Engaging first-year geology students by deconstructing and correcting scientific misconceptions in popular culture. A Practice Report

    OpenAIRE

    Leslie Almberg

    2011-01-01

    Popular culture abounds with ill-conceived notions about Earth’s processes.  Movies, books, music, television and even video games frequently misrepresent fundamental scientific principles, warping viewers’ perceptions of the world around them.  First year geoscience students are not immune to pop culture’s portrayal of earth science and the misconceptions they bring to Geology 101 cloud their ability to differentiate between fact and fiction.  Working within ...

  13. Predicting College Readiness in STEM: A Longitudinal Study of Iowa Students

    Science.gov (United States)

    Rickels, Heather Anne

    The demand for STEM college graduates is increasing. However, recent studies show there are not enough STEM majors to fulfill this need. This deficiency can be partially attributed to a gender discrepancy in the number of female STEM graduates and to the high rate of attrition of STEM majors. As STEM attrition has been associated with students being unprepared for STEM coursework, it is important to understand how STEM graduates change in achievement levels from middle school through high school and to have accurate readiness indicators for first-year STEM coursework. This study aimed to address these issues by comparing the achievement growth of STEM majors to non-STEM majors by gender in Science, Math, and Reading from Grade 6 to Grade 11 through latent growth models (LGMs). Then STEM Readiness Benchmarks were established in Science and Math on the Iowas (IAs) for typical first-year STEM courses and validity evidence was provided for the benchmarks. Results from the LGM analyses indicated that STEM graduates start at higher achievement levels in Grade 6 and maintain higher achievement levels through Grade 11 in all subjects. In addition, gender differences were examined. The findings indicate that students with high achievement levels self-select as STEM majors, regardless of gender. In addition, they suggest that students who are not on-track for a STEM degree may need to begin remediation prior to high school. Results from the benchmark analyses indicate that STEM coursework is more demanding and that students need to be better prepared academically in science and math if planning to pursue a STEM degree. In addition, the STEM Readiness Benchmarks were more accurate in predicting success in STEM courses than if general college readiness benchmarks were utilized. Also, students who met the STEM Readiness Benchmarks were more likely to graduate with a STEM degree. This study provides valuable information on STEM readiness to students, educators, and college

  14. Prediction of Student Performance in Academic and Military Learning Environment: Use of Multiple Linear Regression Predictive Model and Hypothesis Testing

    Science.gov (United States)

    Khan, Wasi Z.; Al Zubaidy, Sarim

    2017-01-01

    The variance in students' academic performance in a civilian institute and in a military technological institute could be linked to the environment of the competition available to the students. The magnitude of talent, domain of skills and volume of efforts students put are identical in both type of institutes. The significant factor is the…

  15. Predictive factors of premedical student retention and degree completion within a private undergraduate university

    Science.gov (United States)

    Carter, Frances E.

    Undergraduate retention and eventual graduation is of paramount importance to universities globally. Approximately 58% of students who began their college career at a four-year institution with the intention of receiving a bachelor's degree actually received that degree in a 6-year timeframe, according to the National Center for Education Statistics (NCES) annual report The Condition of Education 2009 (Planty, 2009). In certain subgroups of the undergraduate population, this graduation rate is even lower. This dissertation presents research into the academic integration of students in premedical programs subgroup based on Vincent Tinto's Integrationist Model of Student Departure. Pre-entry factors of interest for this study included incoming high school grade point average (GPA), incoming SAT total test scores, while post-matriculation factors included grade in organic chemistry, and the initial calculus course taken. A sample of 519 students from a private coeducational institution in the southeastern United States was examined. A logistic regression was performed to determine the effect of high school GPA, SAT total scores, organic chemistry grades, and calculus-readiness on graduation. A significant regression equation was found. The findings suggest that of the four predictor variables, high school GPA and organic chemistry grade were the only variables that showed significant predictive ability based on a significance level of p < .05. Further research should involve the examination of additional indicators of academic integration as well as information on the social integration of the student. Additionally, institutional leaders should continue to evaluate the premedical curriculum based on potential changes in medical school requirements.

  16. Statistical model for predicting correct amount of deoxidizer of Al-killed grade casted at slab continuous caster of Pakistan steel

    International Nuclear Information System (INIS)

    Siddiqui, A.R.; Khan, M.M.A.; Ismail, B.M.

    1999-01-01

    Oxygen is blown in Converter process to oxidize hot metal. This introduces dissolved oxygen in the metal, which may cause embrittlement, voids, inclusion and other undesirable properties in steel. The steel bath at the time of tapping contains 400 to 800 ppm oxygen. Deoxidation is carried out during tapping by adding into the tap ladle appropriate amounts of ferromanganese, ferrosilicon and/or aluminum or other special deoxidizers. In the research aluminum killed grade steel which are casted at the slab caster of Pakistan Steel were investigated. Amount of aluminum added is very critical because if we add lesser amount of aluminum then the required quantity then there will be an incomplete killing of oxygen which results uncleanness in steel. Addition of larger amount of aluminum not only increases the cost of the production but also results as higher amount of alumina, which results in nozzle clogging and increase, loses. The purpose of the research is to develop a statistical model which would predict correct amount of aluminum addition for complete deoxidation of aluminum killed grade casted at slab continuous caster of Pakistan Steel. In the model aluminum added is taken as dependent variable while tapping temperature, turn down carbon composition, turndown manganese composition and oxygen content in steel would be the independent variable. This work is based on operational practice on 130 tons Basic Oxygen furnace. (author)

  17. Perceived parenting and social support: can they predict academic achievement in Argentinean college students?

    Science.gov (United States)

    de la Iglesia, Guadalupe; Freiberg Hoffmann, Agustin; Fernández Liporace, Mercedes

    2014-01-01

    The aim of this study was to test the ability to predict academic achievement through the perception of parenting and social support in a sample of 354 Argentinean college students. Their mean age was 23.50 years (standard deviation =2.62 years) and most of them (83.3%) were females. As a prerequisite for admission to college, students are required to pass a series of mandatory core classes and are expected to complete them in two semesters. Delay in completing the curriculum is considered low academic achievement. Parenting was assessed taking into account the mother and the father and considering two dimensions: responsiveness and demandingness. Perceived social support was analyzed considering four sources: parents, teachers, classmates, and best friend or boyfriend/girlfriend. Path analysis showed that, as hypothesized, responsiveness had a positive indirect effect on the perception of social support and enhanced achievement. Demandingness had a different effect in the case of the mother as compared to the father. In the mother model, demandingness had a positive direct effect on achievement. In the case of the father, however, the effect of demandingness had a negative and indirect impact on the perception of social support. Teachers were the only source of perceived social support that significantly predicted achievement. The pathway that belongs to teachers as a source of support was positive and direct. Implications for possible interventions are discussed.

  18. Trait impulsivity predicts D-KEFS tower test performance in university students.

    Science.gov (United States)

    Lyvers, Michael; Basch, Vanessa; Duff, Helen; Edwards, Mark S

    2015-01-01

    The present study examined a widely used self-report index of trait impulsiveness in relation to performance on a well-known neuropsychological executive function test in 70 university undergraduate students (50 women, 20 men) aged 18 to 24 years old. Participants completed the Barratt Impulsiveness Scale (BIS-11) and the Frontal Systems Behavior Scale (FrSBe), after which they performed the Tower Test of the Delis-Kaplan Executive Function System. Hierarchical linear regression showed that after controlling for gender, current alcohol consumption, age at onset of weekly alcohol use, and FrSBe scores, BIS-11 significantly predicted Tower Test Achievement scores, β = -.44, p impulsiveness is associated with poorer executive cognitive performance even in a sample likely to be characterized by relatively high general cognitive functioning (i.e., university students). The results also support the role of inhibition as a key aspect of executive task performance. Elevated scores on the BIS-11 and FrSBe are known to be linked to risky drinking in young adults as confirmed in this sample; however, only BIS-11 predicted Tower Test performance.

  19. Predicting the "graduate on time (GOT)" of PhD students using binary logistics regression model

    Science.gov (United States)

    Shariff, S. Sarifah Radiah; Rodzi, Nur Atiqah Mohd; Rahman, Kahartini Abdul; Zahari, Siti Meriam; Deni, Sayang Mohd

    2016-10-01

    Malaysian government has recently set a new goal to produce 60,000 Malaysian PhD holders by the year 2023. As a Malaysia's largest institution of higher learning in terms of size and population which offers more than 500 academic programmes in a conducive and vibrant environment, UiTM has taken several initiatives to fill up the gap. Strategies to increase the numbers of graduates with PhD are a process that is challenging. In many occasions, many have already identified that the struggle to get into the target set is even more daunting, and that implementation is far too ideal. This has further being progressing slowly as the attrition rate increases. This study aims to apply the proposed models that incorporates several factors in predicting the number PhD students that will complete their PhD studies on time. Binary Logistic Regression model is proposed and used on the set of data to determine the number. The results show that only 6.8% of the 2014 PhD students are predicted to graduate on time and the results are compared wih the actual number for validation purpose.

  20. Motivation and emotion predict medical students' attention to computer-based feedback.

    Science.gov (United States)

    Naismith, Laura M; Lajoie, Susanne P

    2017-12-14

    Students cannot learn from feedback unless they pay attention to it. This study investigated relationships between the personal factors of achievement goal orientations, achievement emotions, and attention to feedback in BioWorld, a computer environment for learning clinical reasoning. Novice medical students (N = 28) completed questionnaires to measure their achievement goal orientations and then thought aloud while solving three endocrinology patient cases and reviewing corresponding expert solutions. Questionnaires administered after each case measured participants' experiences of five feedback emotions: pride, relief, joy, shame, and anger. Attention to individual text segments of the expert solutions was modelled using logistic regression and the method of generalized estimating equations. Participants did not attend to all of the feedback that was available to them. Performance-avoidance goals and shame positively predicted attention to feedback, and performance-approach goals and relief negatively predicted attention to feedback. Aspects of how the feedback was displayed also influenced participants' attention. Findings are discussed in terms of their implications for educational theory as well as the design and use of computer learning environments in medical education.

  1. Predicting Student Academic Performance: A Comparison of Two Meta-Heuristic Algorithms Inspired by Cuckoo Birds for Training Neural Networks

    Directory of Open Access Journals (Sweden)

    Jeng-Fung Chen

    2014-10-01

    Full Text Available Predicting student academic performance with a high accuracy facilitates admission decisions and enhances educational services at educational institutions. This raises the need to propose a model that predicts student performance, based on the results of standardized exams, including university entrance exams, high school graduation exams, and other influential factors. In this study, an approach to the problem based on the artificial neural network (ANN with the two meta-heuristic algorithms inspired by cuckoo birds and their lifestyle, namely, Cuckoo Search (CS and Cuckoo Optimization Algorithm (COA is proposed. In particular, we used previous exam results and other factors, such as the location of the student’s high school and the student’s gender as input variables, and predicted the student academic performance. The standard CS and standard COA were separately utilized to train the feed-forward network for prediction. The algorithms optimized the weights between layers and biases of the neuron network. The simulation results were then discussed and analyzed to investigate the prediction ability of the neural network trained by these two algorithms. The findings demonstrated that both CS and COA have potential in training ANN and ANN-COA obtained slightly better results for predicting student academic performance in this case. It is expected that this work may be used to support student admission procedures and strengthen the service system in educational institutions.

  2. Correction for the Hematocrit Bias in Dried Blood Spot Analysis Using a Nondestructive, Single-Wavelength Reflectance-Based Hematocrit Prediction Method.

    Science.gov (United States)

    Capiau, Sara; Wilk, Leah S; De Kesel, Pieter M M; Aalders, Maurice C G; Stove, Christophe P

    2018-02-06

    bias obtained with Bland and Altman analysis was -0.015 and the limits of agreement were -0.061 and 0.031, indicating that the simplified, noncontact Hct prediction method even outperforms the original method. In addition, using caffeine as a model compound, it was demonstrated that this simplified Hct prediction method can effectively be used to implement a Hct-dependent correction factor to DBS-based results to alleviate the Hct bias.

  3. Prediction of intention to continue sport in athlete students: A self-determination theory approach.

    Directory of Open Access Journals (Sweden)

    Mohammad Keshtidar

    Full Text Available Grounded on the self-determination theory (Deci & Ryan, 1985, 2000 and achievement goals theory (Ames, 1992; Nicholls, 1989, this study via structural equation modelling, predicted intention to continue in sport from goal orientations and motivations among athlete students. 268 athlete students (Mage = 21.9, in Iranian universities completed a multi-section questionnaire tapping the targeted variables. Structural equation modelling (SEM offered an overall support for the proposed model. The results showed that there are positive relationships between intention to continue in sport and both orientations as well as both motivations. A task-involving orientation emerged as a positive predictor of the autonomous motivation, while an ego-involving orientation was a positive predictor controlled motivation as well as autonomous motivation. The results also support positive paths between autonomous motivation and future intention to participate in sport. Autonomous motivation also was a positive mediator in relationship between task orientation and the intentions. As a conclusion, the implications of the task-involving orientation are discussabled in the light of its importance for the quality and potential maintenance of sport involvement among athlete students.

  4. Prediction of intention to continue sport in athlete students: A self-determination theory approach.

    Science.gov (United States)

    Keshtidar, Mohammad; Behzadnia, Behzad

    2017-01-01

    Grounded on the self-determination theory (Deci & Ryan, 1985, 2000) and achievement goals theory (Ames, 1992; Nicholls, 1989), this study via structural equation modelling, predicted intention to continue in sport from goal orientations and motivations among athlete students. 268 athlete students (Mage = 21.9), in Iranian universities completed a multi-section questionnaire tapping the targeted variables. Structural equation modelling (SEM) offered an overall support for the proposed model. The results showed that there are positive relationships between intention to continue in sport and both orientations as well as both motivations. A task-involving orientation emerged as a positive predictor of the autonomous motivation, while an ego-involving orientation was a positive predictor controlled motivation as well as autonomous motivation. The results also support positive paths between autonomous motivation and future intention to participate in sport. Autonomous motivation also was a positive mediator in relationship between task orientation and the intentions. As a conclusion, the implications of the task-involving orientation are discussabled in the light of its importance for the quality and potential maintenance of sport involvement among athlete students.

  5. Testing the predictions of the existential constructivist theory of suicide in a college student sample.

    Science.gov (United States)

    Lockman, Jennifer D; Servaty-Seib, Heather L

    2018-04-01

    There is a lack of empirically supported theories explaining suicidal ideation and few theories describe how suicidal ideation can be prevented in the context of normative human development. Rogers (2001) proposed an existential constructivist theory of suicide (ECTS) wherein existential distress and the inability to reconstruct meaning from adverse life events contribute to suicidal ideation. The ECTS includes a distinct focus on meaning reconstruction from adverse life events, which is congruent with existing research on college students and developmental frameworks used by counseling psychologists. Thus, in the present study, we tested the predictions of the ECTS in a college student sample. We collected data online from 195 college students (i.e., ages 18-25) attending a large, Midwestern university and analyzed the data using structural equation modeling. Findings provided partial support for the original ECTS. Post hoc analyses of an alternate ECTS model indicated that existential distress mediated the negative association between meaning reconstruction and suicidal ideation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  6. Predictive validity of the post-enrolment English language assessment tool for commencing undergraduate nursing students.

    Science.gov (United States)

    Glew, Paul J; Hillege, Sharon P; Salamonson, Yenna; Dixon, Kathleen; Good, Anthony; Lombardo, Lien

    2015-12-01

    Nursing students with English as an additional language (EAL) may underperform academically. The post-enrolment English language assessment (PELA) is used in literacy support, but its predictive validity in identifying those at risk of underperformance remains unknown. To validate a PELA, as a predictor of academic performance. Prospective survey design. The study was conducted at a university located in culturally and linguistically diverse areas of western Sydney, Australia. Commencing undergraduate nursing students who were Australian-born (n=1323, 49.6%) and born outside of Australia (n=1346, 50.4%) were recruited for this study. The 2669 (67% of 3957) participants provided consent and completed a first year nursing unit that focussed on developing literacy skills. Between 2010 and 2013, commencing students completed the PELA and English language acculturation scale (ELAS), a previously validated instrument. The grading levels of the PELA tool were: Level 1 (proficient), Level 2 (borderline), and Level 3 (poor, and requiring additional support). Participants with a PELA Level 2 or 3 were more likely to be: a) non-Australian-born (χ(2): 520.6, df: 2, pstudent (χ(2): 225.6, df: 2, pstudents who are at risk of academic underachievement. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  7. Publisher Correction

    DEFF Research Database (Denmark)

    Turcot, Valérie; Lu, Yingchang; Highland, Heather M

    2018-01-01

    In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.......In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article....

  8. Author Correction

    DEFF Research Database (Denmark)

    Grundle, D S; Löscher, C R; Krahmann, G

    2018-01-01

    A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.......A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper....

  9. The Role of Trusting in God in Predicting Mental Health of Tehran University Students

    Directory of Open Access Journals (Sweden)

    Fatemeh Sharif Mousavi

    2014-12-01

    Full Text Available Introduction: in light of the importance of mental health in today life, attending to mental health of the youth to pave the way for a better future is of paramount importance. Various factors can influence mental health, one of which is the quality of attachment to and trust in God. The aim of this paper was to examine the capability of this quality so as to predict the mental health of Tehran University students. Methods: This research was of correlation type which utilized analysis of regression and the multiple correlation factor to analyze data. The participants were 300 students studying at University of Tehran (207 males and 93 females who were stratified into theology 34, biology 38, art 21, literature 54, economics 21, technical 68, English Language 38, and Psychology 26. Data collection was done on the basis of the revised list of mental symptoms, Kirkpatric test of attachment to God method and Rahyaft questionnaire in life events. Findings: in this study, it was demonstrated that 29% of the variance of students' mental health was represented by factors of attachment to God, and the value of F (found in the analysis of regression showed that only the aspects of attributive and action were meaningful at the significance level of below 0.5% among other variances and the other predictors of students' metal health all were meaningful at the significance level of below 0.01%. Conclusion: The findings of the study demonstrate the relation between spirituality and mental health in such a way that mental health can be helped by strengthening and reinforcing the students’ sources of spirituality including trust in God.

  10. Intrinsic predictive factors for ankle sprain in active university students: a prospective study.

    Science.gov (United States)

    de Noronha, M; França, L C; Haupenthal, A; Nunes, G S

    2013-10-01

    The ankle is the joint most affected among the sports-related injuries. The current study investigated whether certain intrinsic factors could predict ankle sprains in active students. The 125 participants were submitted to a baseline assessment in a single session were then followed-up for 52 weeks regarding the occurrence of sprain. The baseline assessment were performed in both ankles and included the questionnaire Cumberland ankle instability tool - Portuguese, the foot lift test, dorsiflexion range of motion, Star Excursion Balance Test (SEBT), the side recognition task, body mass index, and history of previous sprain. Two groups were used for analysis: one with those who suffered an ankle sprain and the other with those who did not suffer an ankle sprain. After Cox regression analysis, participants with history of previous sprain were twice as likely to suffer subsequent sprains [hazard ratio (HR) 2.21 and 95% confidence interval (CI) 1.07-4.57] and people with better performance on the SEBT in the postero-lateral (PL) direction were less likely to suffer a sprain (HR 0.96 and 95% CI 0.92-0.99). History of previous sprain was the strongest predictive factor and a weak performance on SEBT PL was also considered a predictive factor for ankle sprains. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. A correlational and predictive study of creativity and personality of college students.

    Science.gov (United States)

    Sanz de Acedo Baquedano, María Teresa; Sanz de Acedo Lizarraga, María Luisa

    2012-11-01

    The goals of this study were to examine the relationship between creativity and personality, to identify what personality variables better predict creativity, and to determine whether significant differences exist among them in relation to gender. The research was conducted with a sample of 87 students at the Universidad Pública de Navarra, Spain. We administered the Creative Intelligence Test (CREA), which provides a cognitive measure for creativity and the Situational Personality Questionnaire (SPQ), which is composed of 15 personality features. Positive and significant correlations between creativity and independence, cognitive control, and tolerance personality scales were found. Negative and significant correlations between creativity and anxious, dominant, and aggressive personalities were also found. Moreover, four personality variables that positively predicted creativity (efficacy, independence, cognitive control, and integrity-honesty) and another four that negatively predicted creativity (emotional stability, anxiety, dominance, and leadership) were identified. The results did not show significant differences in creativity and personality in relation to gender, except in self-concept and in social adjustment. In conclusion, the results from this study can potentially be used to expand the types of features that support creative personalities.

  12. Undergraduate Student Retention in Context: An Examination of First-Year Risk Prediction and Advising Practices within a College of Education

    Science.gov (United States)

    Litchfield, Bradley C.

    2013-01-01

    This study examined the use of an institutionally-specific risk prediction model in the university's College of Education. Set in a large, urban, public university, the risk model predicted incoming students' first-semester GPAs, which, in turn, predicted the students' risk of attrition. Additionally, the study investigated advising practices…

  13. Perceived competence and enjoyment in predicting students' physical activity and cardiorespiratory fitness.

    Science.gov (United States)

    Gao, Zan

    2008-10-01

    This study investigated the predictive strength of perceived competence and enjoyment on students' physical activity and cardiorespiratory fitness in physical education classes. Participants (N = 307; 101 in Grade 6, 96 in Grade 7, 110 in Grade 8; 149 boys, 158 girls) responded to questionnaires assessing perceived competence and enjoyment of physical education, then their cardiorespiratory fitness was assessed on the Progressive Aerobic Cardiovascular Endurance Run (PACER) test. Physical activity in one class was estimated via pedometers. Regression analyses showed enjoyment (R2 = 16.5) and perceived competence (R2 = 4.2) accounted for significant variance of only 20.7% of physical activity and, perceived competence was the only significant contributor to cardiorespiratory fitness performance (R2 = 19.3%). Only a small amount of variance here leaves 80% unaccounted for. Some educational implications and areas for research are mentioned.

  14. Predicting English Word Reading Skills for Spanish-Speaking Students in First Grade.

    Science.gov (United States)

    Páez, Mariela; Rinaldi, Claudia

    2006-10-01

    This article describes the word reading skills in English and Spanish for a sample of 244 Spanish-speaking, English-learning (hence, bilingual) students in first grade and presents a predictive model for English word reading skills. The children in the study were assessed at the end of kindergarten and first grade, respectively. Data were gathered with 3 subtests of the Woodcock Language Proficiency Battery and a researcher-developed phonological awareness task. Results showed that, on average, children's English word reading skills were similar to monolingual norms whereas their Spanish word reading skills averaged 1 SD below the mean. English vocabulary, English phonological awareness, and Spanish word reading skills in kindergarten were found to be significant predictors of English word reading skills in first grade. Educational implications for screening language and reading skills and promising areas for targeted instruction for this population are discussed.

  15. Teacher-Student Interactions as Predicted by Teaching Stress and the Perceived Quality of the Student-Teacher Relationship.

    Science.gov (United States)

    Abidin, Richard R.; Kmetz, Christal A.

    This paper reports on a study that examined teachers' perceptions of their relationships with specific students, their experience of stress in relation to those students, and whether those perceptions and experiences translate into observable differences in actual teacher behavior toward those students in the classroom. Specifically, the project…

  16. Does television viewing predict dietary intake five years later in high school students and young adults?

    Directory of Open Access Journals (Sweden)

    Neumark-Sztainer Dianne

    2009-01-01

    Full Text Available Abstract Background Prior research has found that television viewing is associated with poor diet quality, though little is known about its long-term impact on diet, particularly during adolescence. This study examined the associations between television viewing behavior with dietary intake five years later. Methods Survey data, which included television viewing time and food frequency questionnaires, were analyzed for 564 middle school students (younger cohort and 1366 high school students (older cohort who had complete data available at Time 1 (1998–1999 and five years later at Time 2 (mean age at Time 2, 17.2 ± 0.6 and 20.5 ± 0.8 years, respectively. Regression models examined longitudinal associations between Time 1 television viewing behavior and Time 2 dietary intake adjusting for sociodemographic characteristics, Time 1 dietary intake, and Time 2 total daily energy intake. Results Respondents were categorized as limited television users (2 hours/daily, moderately high television viewers (2–5 hours/daily, and heavy television viewers (≥5 hours/daily. Among the younger cohort, Time 1 heavy television viewers reported lower fruit intake and higher sugar-sweetened beverage consumption than the other two groups. Among the older cohort, watching five or more hours of television per day at Time 1, predicted lower intakes of fruits, vegetables, whole grain and calcium-rich foods, and higher intakes of trans fat, fried foods, fast food menu items, snack products, and sugar-sweetened beverages (products commonly advertised on television five years later. Conclusion Television viewing in middle and high school predicted poorer dietary intake five years later. Adolescents are primary targets of advertising for fast food restaurants, snack foods, and sugar-sweetened beverages, which may influence their food choices. Television viewing, especially during high school, may have long-term effects on eating choices and contribute to poor eating

  17. Perceived parenting and social support: can they predict academic achievement in Argentinean college students?

    Directory of Open Access Journals (Sweden)

    de la Iglesia G

    2014-09-01

    Full Text Available Guadalupe de la Iglesia,1,2 Agustin Freiberg Hoffmann,2 Mercedes Fernández Liporace1,2 1National Council of Scientific and Technical Research (CONICET, 2University of Buenos Aires, Buenos Aires, Argentina Abstract: The aim of this study was to test the ability to predict academic achievement through the perception of parenting and social support in a sample of 354 Argentinean college students. Their mean age was 23.50 years (standard deviation =2.62 years and most of them (83.3% were females. As a prerequisite for admission to college, students are required to pass a series of mandatory core classes and are expected to complete them in two semesters. Delay in completing the curriculum is considered low academic achievement. Parenting was assessed taking into account the mother and the father and considering two dimensions: responsiveness and demandingness. Perceived social support was analyzed considering four sources: parents, teachers, classmates, and best friend or boyfriend/girlfriend. Path analysis showed that, as hypothesized, responsiveness had a positive indirect effect on the perception of social support and enhanced achievement. Demandingness had a different effect in the case of the mother as compared to the father. In the mother model, demandingness had a positive direct effect on achievement. In the case of the father, however, the effect of demandingness had a negative and indirect impact on the perception of social support. Teachers were the only source of perceived social support that significantly predicted achievement. The pathway that belongs to teachers as a source of support was positive and direct. Implications for possible interventions are discussed. Keywords: academic achievement, parenting, social support, college

  18. Role of Procrastination and Motivational Self-Regulation in Predicting Students\\' Behavioral Engagement

    Directory of Open Access Journals (Sweden)

    Abbasi M

    2015-12-01

    Full Text Available Aims: As an important intervening factor to enhance educational and motivational performance of the students, understating the effective factors on behavioral enthusiasm plays a very important role. The aim of this study was to explain the role of motivational self-regulation and procrastination in predicting the students’ behavioral enthusiasm.  Instrument & Methods: In the correlational descriptive cross-sectional study, 311 students of Arak University of Medical Sciences were selected via Available Sampling using Cochran’s Formula in 2014-15 academic year. Data was collected, using Students’ Educational Procrastination Scale, Motivational Self-regulating Scale, and Behavioral Enthusiasm Scale. Data was analyzed in SPSS 19 software using Pearson Correlation Coefficient, and Multiple Regression Analysis. Findings: The highest and the lowest correlations were between procrastination and behavioral enthusiasm and between environmental control and behavioral enthusiasm, respectively (p<0.05. There was a positive and significant correlation between self-regulation and behavioral enthusiasm. In addition, there was a negative and significant correlation between procrastination and behavioral enthusiasm (p<0.001. Totally, procrastination (β=-0.233 and motivational self-regulation (β=0.238 explained 10% of the students’ behavioral enthusiasm variance (p<0.001; R²=0.102. Conclusion: Any reduction in procrastination and any enhancement in motivational self-regulation can enhance the students’ behavioral enthusiasm. 

  19. Alcohol-related problems and life satisfaction predict motivation to change among mandated college students.

    Science.gov (United States)

    Diulio, Andrea R; Cero, Ian; Witte, Tracy K; Correia, Christopher J

    2014-04-01

    The present study investigated the role specific types of alcohol-related problems and life satisfaction play in predicting motivation to change alcohol use. Participants were 548 college students mandated to complete a brief intervention following an alcohol-related policy violation. Using hierarchical multiple regression, we tested for the presence of interaction and quadratic effects on baseline data collected prior to the intervention. A significant interaction indicated that the relationship between a respondent's personal consequences and his/her motivation to change differs depending upon the level of concurrent social consequences. Additionally quadratic effects for abuse/dependence symptoms and life satisfaction were found. The quadratic probes suggest that abuse/dependence symptoms and poor life satisfaction are both positively associated with motivation to change for a majority of the sample; however, the nature of these relationships changes for participants with more extreme scores. Results support the utility of using a multidimensional measure of alcohol related problems and assessing non-linear relationships when assessing predictors of motivation to change. The results also suggest that the best strategies for increasing motivation may vary depending on the types of alcohol-related problems and level of life satisfaction the student is experiencing and highlight potential directions for future research. Copyright © 2014. Published by Elsevier Ltd.

  20. Professional choice self-efficacy: predicting traits and personality profiles in high school students

    Directory of Open Access Journals (Sweden)

    Rodolfo Augusto Matteo Ambiel

    2016-01-01

    Full Text Available Abstract This study aimed to verify the predictive capacity of the Big Five personality factors related to professional choice self-efficacy, as well as to draw a personality profile of people with diverse self-efficacy levels. There were 308 high school students participating, from three different grades (57.5 % women, from public and private schools, average 26.64 years of age. Students completed two instruments, Escala de Autoeficácia para Escolha Profissional (Professional Choice Self-efficacy Scale and Bateria Fatorial de Personalidade (Factorial Personality Battery. Results were obtained using multiple regression analysis, analysis of variance with repeated measures profile and Cohen’s d to estimate the effect size of differences. Results showed that Extraversion, Agreeableness and Conscientiousness were the main predictors of self-efficacy. Differences from medium to large were observed between extreme groups, and Extraversion and Conscientiousness were the personality factors that better distinguish people with low and high levels of self-efficacy. Theses results partially corroborate with the hypothesis. Results were discussed based on literature and on the practical implications of the results. New studies are proposed.

  1. Predicting dropout using student- and school-level factors: An ecological perspective.

    Science.gov (United States)

    Wood, Laura; Kiperman, Sarah; Esch, Rachel C; Leroux, Audrey J; Truscott, Stephen D

    2017-03-01

    High school dropout has been associated with negative outcomes, including increased rates of unemployment, incarceration, and mortality. Dropout rates vary significantly depending on individual and environmental factors. The purpose of our study was to use an ecological perspective to concurrently explore student- and school-level predictors associated with dropout for the purpose of better understanding how to prevent it. We used the Education Longitudinal Study of 2002 dataset. Participants included 14,106 sophomores across 684 public and private schools. We identified variables of interest based on previous research on dropout and implemented hierarchical generalized linear modeling. In the final model, significant student-level predictors included academic achievement, retention, sex, family socioeconomic status (SES), and extracurricular involvement. Significant school-level predictors included school SES and school size. Race/ethnicity, special education status, born in the United States, English as first language, school urbanicity, and school region did not significantly predict dropout after controlling for the aforementioned predictors. Implications for prevention and intervention efforts within a multitiered intervention model are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  2. Perfectionism and self-conscious emotions in British and Japanese students: Predicting pride and embarrassment after success and failure

    OpenAIRE

    Stoeber, Joachim; Kobori, Osamu; Tanno, Yoshihiko

    2013-01-01

    Regarding self-conscious emotions, studies have shown that different forms of perfectionism show different relationships with pride, shame, and embarrassment depending on success and failure. What is unknown is whether these relationships also show cultural variations. Therefore, we conducted a study investigating how self-oriented and socially prescribed perfectionism predicted pride and embarrassment after success and failure comparing 363 British and 352 Japanese students. Students were as...

  3. Predicting success for college students enrolled in an online, lab-based, biology course for non-majors

    Science.gov (United States)

    Foster, Regina

    Online education has exploded in popularity. While there is ample research on predictors of traditional college student success, little research has been done on effective methods of predicting student success in online education. In this study, a number of demographic variables including GPA, ACT, gender, age and others were examined to determine what, if any, role they play in successfully predicting student success in an online, lab-based biology for non-majors course. Within course variables such as participation in specific categories of assignment and frequency of online visits were also examined. Groups of students including Native American/Non-Native American and Digital Immigrants and Digital Natives and others were also examined to determine if overall course success differed significantly. Good predictors of online success were found to be GPA, ACT, previous course experience and frequency of online visits with the course materials. Additionally, students who completed more of the online assignments within the course were more successful. Native American and Non-Native American students were found to differ in overall course success significantly as well. Findings indicate student academic background, previous college experience and time spent with course materials are the most important factors in course success. Recommendations include encouraging enrollment advisors to advise students about the importance of maintaining high academic levels, previous course experience and spending time with course materials may impact students' choices for online courses. A need for additional research in several areas is indicated, including Native American and Non-Native American differences. A more detailed examination of students' previous coursework would also be valuable. A study involving more courses, a larger number of students and surveys from faculty who teach online courses would help improve the generalizability of the conclusions.

  4. Alcohol-Related Facebook Activity Predicts Alcohol Use Patterns in College Students

    Science.gov (United States)

    Marczinski, Cecile A.; Hertzenberg, Heather; Goddard, Perilou; Maloney, Sarah F.; Stamates, Amy L.; O’Connor, Kathleen

    2016-01-01

    The purpose of this study was to determine if a brief 10-item alcohol-related Facebook® activity (ARFA) questionnaire would predict alcohol use patterns in college students (N = 146). During a single laboratory session, participants first privately logged on to their Facebook® profiles while they completed the ARFA measure, which queries past 30 day postings related to alcohol use and intoxication. Participants were then asked to complete five additional questionnaires: three measures of alcohol use (the Alcohol Use Disorders Identification Test [AUDIT], the Timeline Follow-Back [TLFB], and the Personal Drinking Habits Questionnaire [PDHQ]), the Barratt Impulsiveness Scale (BIS-11), and the Marlowe-Crowne Social Desirability Scale (MC-SDS). Regression analyses revealed that total ARFA scores were significant predictors of recent drinking behaviors, as assessed by the AUDIT, TLFB, and PDHQ measures. Moreover, impulsivity (BIS-11) and social desirability (MC-SDS) did not predict recent drinking behaviors when ARFA total scores were included in the regressions. The findings suggest that social media activity measured via the ARFA scale may be useful as a research tool for identifying risky alcohol use. PMID:28138317

  5. La correction et la révision de l’écrit en français langue seconde: médiation humaine, médiation informatique Correcting and editing texts written by FSL students: human mediation vs. computer-assisted mediation

    Directory of Open Access Journals (Sweden)

    Chantal Dion

    2003-06-01

    Full Text Available L’apprentissage de la correction / révision de l’écrit par les apprenants de français langue seconde peut-elle tirer profit des correcteurs orthographiques et grammaticaux des traitements de texte ou des correcticiels spécialisés ? La nature de la médiation informatique permet-elle aux apprenants de corriger de façon efficace leurs textes et comment se compare-t-elle avec la correction humaine ? Qu’est-ce qui différencie ces deux médiations ? Des textes rédigés par des anglophones ont été soumis aux deux types de corrections, humaine et informatique, soit deux enseignantes ayant vingt ans d’expérience et la correction informatique effectuée par le correcteur orthographique et grammatical de Word et les deux correcticiels canadiens, Le correcteur 101 et Antidote. Les résultats montrent que la nature de ces médiations n’est pas comparable et que la médiation informatique, pour être efficace, nécessite la participation active, intelligente et instruite de l’utilisateur et que les correcticiels ne peuvent pas corriger efficacement des textes d’étudiants de niveau intermédiaire.Can spellcheckers or grammar correctors, be they part of a word processor or stand-alone programs, help FSL students become more adept at correcting or editing the written texts they produce? Does computer-assisted mediation enable learners to correct their work efficiently and how does it compare with human mediation? What differentiates them? Texts written by anglophone students were corrected using both methods, i.e., on the one hand, by two teachers with 20 years experience and, on the other hand, using the specialized tools available with MSWord as well as two Canadian text correction programs, Le Correcteur 101 and Antidote. It turns out that the two methods are of very different natures ; computer-based correction can only give some positive results if the users have received appropriate training enabling them to actively and

  6. Application Of Data Mining Techniques For Student Success And Failure Prediction The Case Of DebreMarkos University

    Directory of Open Access Journals (Sweden)

    Muluken Alemu Yehuala

    2015-04-01

    Full Text Available Abstract This research work has investigated the potential applicability of data mining technology to predict student success and failure cases on University students datasets. CRISP-DM Cross Industry Standard Process for Data mining is a data mining methodology to be used by the research. Classification and prediction data mining functionalities are used to extract hidden patterns from students data. These patterns can be seen in relation to different variables in the students records. The classification rule generation process is based on the decision tree and Bayes as a classification technique and the generated rules were studied and evaluated. Data collected from MSEXCEL files and it has been preprocessed for model building. Models were built and tested by using a sample dataset of 11873 regular undergraduate students. Analysis is done by using WEKA 3.7 application software. The research results offer a helpful and constructive recommendations to the academic planners in universities of learning to enhance their decision making process. This will also aid in the curriculum structure and modification in order to improve students academic performance. Students able to decide about their field of study before they are enrolled in specific field of study based on the previous experience taken from the research-findings. The research findings indicated that EHEECE Ethiopian Higher Education Entrance Certificate Examination result Sex Number of students in a class number of courses given in a semester and field of study are the major factors affecting the student performances. So on the bases of the research findings the level of student success will increase and it is possible to prevent educational institutions from serious financial strains.

  7. Publisher Correction

    DEFF Research Database (Denmark)

    Stokholm, Jakob; Blaser, Martin J.; Thorsen, Jonathan

    2018-01-01

    The originally published version of this Article contained an incorrect version of Figure 3 that was introduced following peer review and inadvertently not corrected during the production process. Both versions contain the same set of abundance data, but the incorrect version has the children...

  8. Publisher Correction

    DEFF Research Database (Denmark)

    Flachsbart, Friederike; Dose, Janina; Gentschew, Liljana

    2018-01-01

    The original version of this Article contained an error in the spelling of the author Robert Häsler, which was incorrectly given as Robert Häesler. This has now been corrected in both the PDF and HTML versions of the Article....

  9. Correction to

    DEFF Research Database (Denmark)

    Roehle, Robert; Wieske, Viktoria; Schuetz, Georg M

    2018-01-01

    The original version of this article, published on 19 March 2018, unfortunately contained a mistake. The following correction has therefore been made in the original: The names of the authors Philipp A. Kaufmann, Ronny Ralf Buechel and Bernhard A. Herzog were presented incorrectly....

  10. Predicting Learning-Related Emotions from Students' Textual Classroom Feedback via Twitter

    Science.gov (United States)

    Altrabsheh, Nabeela; Cocea, Mihaela; Fallahkhair, Sanaz

    2015-01-01

    Teachers/lecturers typically adapt their teaching to respond to students' emotions, e.g. provide more examples when they think the students are confused. While getting a feel of the students' emotions is easier in small settings, it is much more difficult in larger groups. In these larger settings textual feedback from students could provide…

  11. Future Time Orientation Predicts Academic Engagement among First-Year University Students

    Science.gov (United States)

    Horstmanshof, Louise; Zimitat, Craig

    2007-01-01

    Background: Enhancing student engagement is considered an important strategy for improving retention. Students' Time Perspective is an under-researched factor that may significantly influence student engagement. Aims: This study examines interrelationships between elements of student engagement and relationship with Time Perspective. We propose…

  12. Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies

    Science.gov (United States)

    Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; vom Hofe, Rudolf

    2013-01-01

    This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10;…

  13. The Predictive Strength of Perceived Parenting and Parental Attachment Styles on Psychological Symptoms among Turkish University Students

    Science.gov (United States)

    Körük, Serdar; Öztürk, Abdülkadir; Kara, Ahmet

    2016-01-01

    This study aims to investigate the relationships between perceived parenting, parental attachment styles and psychological symptoms among Turkish university students and it also aims to find out which perceived parenting and parental attachment styles predict psychological symptoms which were measured. This study is a quantitative research and…

  14. Differential Predictive Validity of High School GPA and College Entrance Test Scores for University Students in Yemen

    Science.gov (United States)

    Al-Hattami, Abdulghani Ali Dawod

    2012-01-01

    High school grade point average and college entrance test scores are two admission criteria that are currently used by most colleges in Yemen to select their prospective students. Given their widespread use, it is important to investigate their predictive validity to ensure the accuracy of the admission decisions in these institutions. This study…

  15. Predictive Ability from ePortfolios of Student Achievement Associated with Professional Teaching Standards: An Exploratory Case Study

    Science.gov (United States)

    Payne, Phillip; Burrack, Frederick

    2017-01-01

    This exploratory case study, focused on a music teacher preparation program, examined the coursework ePortfolios of pre-service music teachers to determine if any parts of the ePortfolio process predicted teaching effectiveness in the classroom during the student teaching semester. Sixty-five undergraduate pre-service music teachers made up the…

  16. An Investigation of the Variables Predicting Faculty of Education Students' Speaking Anxiety through Ordinal Logistic Regression Analysis

    Science.gov (United States)

    Bozpolat, Ebru

    2017-01-01

    The purpose of this study is to determine whether Cumhuriyet University Faculty of Education students' levels of speaking anxiety are predicted by the variables of gender, department, grade, such sub-dimensions of "Speaking Self-Efficacy Scale for Pre-Service Teachers" as "public speaking," "effective speaking,"…

  17. Predicting Day-to-Day Changes in Students' School-Related Affect from Daily Academic Experiences and Social Interactions

    Science.gov (United States)

    Altermatt, Ellen Rydell

    2015-01-01

    This study examined the role that everyday academic successes and failures--and the interactions with family members and peers that follow these events--play in predicting day-to-day changes in children's emotional responses to school. Middle school students (N = 101; mean age = 11.62 years) completed daily assessments of their academic…

  18. Engaging Students Emotionally: The Role of Emotional Intelligence in Predicting Cognitive and Affective Engagement in Higher Education

    Science.gov (United States)

    Maguire, Rebecca; Egan, Arlene; Hyland, Philip; Maguire, Phil

    2017-01-01

    Student engagement is a key predictor of academic performance, persistence and retention in higher education. While many studies have identified how aspects of the college environment influence engagement, fewer have specifically focused on emotional intelligence (EI). In this study, we sought to explore whether EI could predict cognitive and/or…

  19. Theory of Planned Behavior: Sensitivity and Specificity in Predicting Graduation and Drop-Out among College and University Students?

    Science.gov (United States)

    Fichten, Catherine S.; Amsel, Rhonda; Jorgensen, Mary; Nguyen, Mai Nhu; Budd, Jillian; King, Laura; Jorgensen, Shirley; Asuncion, Jennison

    2016-01-01

    We examined sensitivity and specificity when using the three theory of planned behavior (TPB) scales (Perceived Behavioral Control, Subjective Norms, Attitude) to predict graduation and drop-out in a longitudinal study of 252 college and university students with disabilities and in a separate cross-sectional study of a random sample of 1380…

  20. A Theory of Planned Behavior Research Model for Predicting the Sleep Intentions and Behaviors of Undergraduate College Students

    Science.gov (United States)

    Knowlden, Adam P.; Sharma, Manoj; Bernard, Amy L.

    2012-01-01

    The purpose of this study was to operationalize the constructs of the Theory of Planned Behavior (TPB) to predict the sleep intentions and behaviors of undergraduate college students attending a Midwestern University. Data collection spanned three phases. The first phase included a semi-structured qualitative interview (n = 11), readability by…

  1. Field-Identification IAT Predicts Students' Academic Persistence over and above Theory of Planned Behavior Constructs

    Science.gov (United States)

    Roland, Nathalie; Mierop, Adrien; Frenay, Mariane; Corneille, Olivier

    2018-01-01

    Ajzen and Dasgupta (2015) recently invited complementing Theory of Planned Behavior (TPB) measures with measures borrowed from implicit cognition research. In this study, we examined for the first time such combination, and we did so to predict academic persistence. Specifically, 169 first-year college students answered a TPB questionnaire and…

  2. The Prediction of Reading Levels between Second and Third Grade Limited English Proficient Students in a Bilingual Program

    Science.gov (United States)

    Moses, Britani Creel

    2010-01-01

    The purpose of this study was to predict the third grade English reading TAKS scores while considering the same students' native language, Spanish, reading level as assessed by a state-approved reading assessment, the Evaluacion del desarrollo de la lectura (EDL), from the end of the second grade year. In addition, this study was been designed to…

  3. Middle School Characteristics That Predict Student Achievement, as Measured by the School-Wide California API Score

    Science.gov (United States)

    Paredes, Josie Abaroa

    2013-01-01

    The purpose of this study was to investigate, through quantitative research, effective middle school characteristics that predict student achievement, as measured by the school-wide California API score. Characteristics were determined using an instrument developed by the Office of Superintendent of Public Instruction (OSPI), which asked middle…

  4. The Role of Senior University Students' Career Adaptability in Predicting Their Subjective Well-Being

    Science.gov (United States)

    Kirdök, Oguzhan; Bölükbasi, Ayten

    2018-01-01

    The aim of this study is to examine whether career adaptability and career adaptability subscales of senior undergraduates could predict subjective well-being. The research was a descriptive correlational study which was conducted on 310 senior students (173 women, 137 men) in a state-funded university on the Mediterranean coast of Turkey and…

  5. An Integrated Analysis of School Students' Aspirations for STEM Careers: Which Student and School Factors Are Most Predictive?

    Science.gov (United States)

    Holmes, Kathryn; Gore, Jennifer; Smith, Max; Lloyd, Adam

    2018-01-01

    Declining enrolments in science, technology, engineering and mathematics (STEM) disciplines and a lack of interest in STEM careers are concerning at a time when society is becoming more reliant on complex technologies. We examine student aspirations for STEM careers by drawing on surveys conducted annually from 2012 to 2015. School students in…

  6. An Examination of Faculty and Student Online Activity: Predictive Relationships of Student Academic Success in a Learning Management System (LMS)

    Science.gov (United States)

    Stamm, Randy Lee

    2013-01-01

    The purpose of this mixed method research study was to examine relationships in student and instructor activity logs and student performance benchmarks specific to enabling early intervention by the instructor in a Learning Management System (LMS). Instructor feedback was collected through a survey instrument to demonstrate perceived importance of…

  7. Predicting self-reported research misconduct and questionable research practices in university students using an augmented Theory of Planned Behavior

    Science.gov (United States)

    Rajah-Kanagasabai, Camilla J.; Roberts, Lynne D.

    2015-01-01

    This study examined the utility of the Theory of Planned Behavior model, augmented by descriptive norms and justifications, for predicting self-reported research misconduct and questionable research practices in university students. A convenience sample of 205 research active Western Australian university students (47 male, 158 female, ages 18–53 years, M = 22, SD = 4.78) completed an online survey. There was a low level of engagement in research misconduct, with approximately one in seven students reporting data fabrication and one in eight data falsification. Path analysis and model testing in LISREL supported a parsimonious two step mediation model, providing good fit to the data. After controlling for social desirability, the effect of attitudes, subjective norms, descriptive norms and perceived behavioral control on student engagement in research misconduct and questionable research practices was mediated by justifications and then intention. This revised augmented model accounted for a substantial 40.8% of the variance in student engagement in research misconduct and questionable research practices, demonstrating its predictive utility. The model can be used to target interventions aimed at reducing student engagement in research misconduct and questionable research practices. PMID:25983709

  8. Using the Integrative Model of Behavioral Prediction to Understand College Students' STI Testing Beliefs, Intentions, and Behaviors.

    Science.gov (United States)

    Wombacher, Kevin; Dai, Minhao; Matig, Jacob J; Harrington, Nancy Grant

    2018-03-22

    To identify salient behavioral determinants related to STI testing among college students by testing a model based on the integrative model of behavioral (IMBP) prediction. 265 undergraduate students from a large university in the Southeastern US. Formative and survey research to test an IMBP-based model that explores the relationships between determinants and STI testing intention and behavior. Results of path analyses supported a model in which attitudinal beliefs predicted intention and intention predicted behavior. Normative beliefs and behavioral control beliefs were not significant in the model; however, select individual normative and control beliefs were significantly correlated with intention and behavior. Attitudinal beliefs are the strongest predictor of STI testing intention and behavior. Future efforts to increase STI testing rates should identify and target salient attitudinal beliefs.

  9. Predictive analysis and data mining among the employment of fresh graduate students in HEI

    Science.gov (United States)

    Rahman, Nor Azziaty Abdul; Tan, Kian Lam; Lim, Chen Kim

    2017-10-01

    Management of higher education have a problem in producing 100% of graduates who can meet the needs of industry while industry is also facing the problem of finding skilled graduates who suit their needs partly due to the lack of an effective method in assessing problem solving skills as well as weaknesses in the assessment of problem-solving skills. The purpose of this paper is to propose a suitable classification model that can be used in making prediction and assessment of the attributes of the student's dataset to meet the selection criteria of work demanded by the industry of the graduates in the academic field. Supervised and unsupervised Machine Learning Algorithms were used in this research where; K-Nearest Neighbor, Naïve Bayes, Decision Tree, Neural Network, Logistic Regression and Support Vector Machine. The proposed model will help the university management to make a better long-term plans for producing graduates who are skilled, knowledgeable and fulfill the industry needs as well.

  10. A predictive study of reading comprehension in third-grade Spanish students.

    Science.gov (United States)

    López-Escribano, Carmen; Elosúa de Juan, María Rosa; Gómez-Veiga, Isabel; García-Madruga, Juan Antonio

    2013-01-01

    The study of the contribution of language and cognitive skills to reading comprehension is an important goal of current reading research. However, reading comprehension is not easily assessed by a single instrument, as different comprehension tests vary in the type of tasks used and in the cognitive demands required. This study examines the contribution of basic language and cognitive skills (decoding, word recognition, reading speed, verbal and nonverbal intelligence and working memory) to reading comprehension, assessed by two tests utilizing various tasks that require different skill sets in third-grade Spanish-speaking students. Linguistic and cognitive abilities predicted reading comprehension. A measure of reading speed (the reading time of pseudo-words) was the best predictor of reading comprehension when assessed by the PROLEC-R test. However, measures of word recognition (the orthographic choice task) and verbal working memory were the best predictors of reading comprehension when assessed by means of the DARC test. These results show, on the one hand, that reading speed and word recognition are better predictors of Spanish language comprehension than reading accuracy. On the other, the reading comprehension test applied here serves as a critical variable when analyzing and interpreting results regarding this topic.

  11. Corrective Jaw Surgery

    Medline Plus

    Full Text Available ... out more. Corrective Jaw Surgery Corrective Jaw Surgery Orthognathic surgery is performed to correct the misalignment of jaws ... out more. Corrective Jaw Surgery Corrective Jaw Surgery Orthognathic surgery is performed to correct the misalignment of jaws ...

  12. Near-infrared spectra of Penicillium camemberti strains separated by extended multiplicative signal correction improved prediction of physical and chemical variations

    DEFF Research Database (Denmark)

    Decker, Marianne; Nielsen, Per Væggemose; Martens, Harald

    2005-01-01

    signal correction (TWEMSC) preprocessing, whereby three patterns of variation in near-infrared (NIR) log(1/R) spectra of fungal colonies could be separated mathematically: (1) physical light scattering and its wavelength dependency, (2) differences in light absorption of water due to varying sample...

  13. Comparative Study of the Effect of Three Teaching Methods of Group, Personal (Face-to-Face, and Compact Disc on Correcting the Pronunciation and Reading of the Prayer in the Students of Qom University of Medical Sciences

    Directory of Open Access Journals (Sweden)

    Shabanali Khansanami

    2013-07-01

    Full Text Available Background and Objectives: Emphasis is placed on the correction of reading the prayer as an important precept in Islamic culture, and it is essential to use an effective teaching method to promote the status of reading the prayers in youth. This study was conducted with the aim of comparing the effect of the methods of group teaching, personal (face-to-face teaching and using compact disc (CD on correcting the pronunciation and reading of the prayer in the students of Qom University of Medical Sciences in 2011.Methods: This semi-experimental study was done on the students of the Faculty of Nursery and Midwifery of Qom University of Medical Sciences. The samples were randomly assigned into three groups, and the number of students in each group was 22. A checklist of reading mistakes was completed before the intervention, and then, teaching content was given to them in the form of group and face-to-face teaching and CD. In the following, reading mistakes of the students’ prayer were recorded one month after intervention. Data was analyzed using descriptive statistics, and Kruskal–Wallis and Wilcoxon tests at a significance level of p0.05.Conclusion: Based on the findings of this study, the effect of teaching methods of group, personal, and CD was the same in correcting the students’ reading of the prayer. Therefore, it is suggested that considering the students’ interest and current circumstances, various methods could be used for correction of the students’ reading of the prayer.

  14. Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies

    Science.gov (United States)

    2013-01-01

    Background Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. Methods Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. Results Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs

  15. Alcohol use longitudinally predicts adjustment and impairment in college students with ADHD: The role of executive functions.

    Science.gov (United States)

    Langberg, Joshua M; Dvorsky, Melissa R; Kipperman, Kristen L; Molitor, Stephen J; Eddy, Laura D

    2015-06-01

    The primary aim of this study was to evaluate whether alcohol consumption longitudinally predicts the adjustment, overall functioning, and grade point average (GPA) of college students with ADHD and to determine whether self-report of executive functioning (EF) mediates these relationships. Sixty-two college students comprehensively diagnosed with ADHD completed ratings at the beginning and end of the school year. Regression analyses revealed that alcohol consumption rated at the beginning of the year significantly predicted self-report of adjustment and overall impairment at the end of the year, above and beyond ADHD symptoms and baseline levels of adjustment/impairment but did not predict GPA. Exploratory multiple mediator analyses suggest that alcohol use impacts impairment primarily through EF deficits in self-motivation. EF deficits in the motivation to refrain from pursuing immediately rewarding behaviors in order to work toward long-term goals appear to be particularly important in understanding why college students with ADHD who consume alcohol have a higher likelihood of experiencing significant negative outcomes. The implications of these findings for the prevention of the negative functional outcomes often experienced by college students with ADHD are discussed. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  16. Predictive Roles of Three-Dimensional Psychological Pain, Psychache, and Depression in Suicidal Ideation among Chinese College Students

    Directory of Open Access Journals (Sweden)

    Huanhuan Li

    2017-09-01

    Full Text Available How to develop an effective screening instrument for predicting suicide risk is an important issue in suicidal research. The aim of the present research was to explore the predictive roles of three screening measures in the evaluation of preexisting suicide risk factors in a sample of undergraduate students. We assessed 1,061 students using the Beck depression and suicidal ideation scales (BDI-I (BSI, the Psychache Scale (PAS, and the three-dimensional Psychological Pain Scale (TDPPS. Simultaneous multivariate regression analysis showed that the predictive values of pain avoidance scores and BDI scores for suicidal ideation were more significant than that of the PAS scores. Subsequently, 42 patients with major depressive disorder (MDD, 39 students with subthreshold depression (SD, and 18 healthy controls were voluntarily recruited. Students with SD were divided into high suicidal ideation (HSI-SD and low suicidal ideation (LSI-SD groups. Pain avoidance scores and BDI scores differed significantly among the MDD, HSI-SD, LSI-SD, and healthy control groups. Pain avoidance and BSI scores were significantly higher in the MDD and HSI-SD groups than those in the LSI-SD and healthy control groups. However, no significant difference was observed in BDI scores between the HSI-SD and LSI-SD groups. Pain avoidance and depression, rather than psychache, may be promising predictors of suicidal ideation in a Chinese young adult population.

  17. Predicting the Attitudes and Self-Esteem of the Grade 9th Lower Secondary School Students towards Mathematics from Their Perceptions of the Classroom Learning Environment

    Science.gov (United States)

    Tran, Van Dat

    2012-01-01

    This study reports the validity of the hypothesis that students' perceptions of the learning environment of mathematics classroom may predict their attitudes and self-esteem towards mathematics. It examines data from 487 grade 9th students from 14 mathematics classes in 7 Vietnamese lower secondary schools to identify how students' perceptions of…

  18. Do Skilled Elementary Teachers Hold Scientific Conceptions and Can They Accurately Predict the Type and Source of Students' Preconceptions of Electric Circuits?

    Science.gov (United States)

    Lin, Jing-Wen

    2016-01-01

    Holding scientific conceptions and having the ability to accurately predict students' preconceptions are a prerequisite for science teachers to design appropriate constructivist-oriented learning experiences. This study explored the types and sources of students' preconceptions of electric circuits. First, 438 grade 3 (9 years old) students were…

  19. Classification Model That Predicts Medical Students' Choices of Primary Care or Non-Primary Care Specialties.

    Science.gov (United States)

    Fincher, Ruth-Marie E.; And Others

    1992-01-01

    This study identified factors in graduating medical students' choice of primary versus nonprimary care specialty. Subjects were 509 students at the Medical College of Georgia in 1988-90. Students could be classified by such factors as desire for longitudinal patient care opportunities, monetary rewards, perception of lifestyle, and perception of…

  20. Parental Involvement in Middle School Predicting College Attendance for First-Generation Students

    Science.gov (United States)

    Bui, Khanh; Rush, Ryan A.

    2016-01-01

    Using data from the National Education Longitudinal Study, this report examined the relationship between parental involvement in eighth grade and college attendance by eight years after high school for students whose parents have no college education (i.e., first-generation students; n = 1,358) in comparison to students whose parents have some…

  1. High Expectations, Strong Support: Faculty Behaviors Predicting Latina/o Community College Student Learning

    Science.gov (United States)

    Lundberg, Carol A.; Kim, Young K.; Andrade, Luis M.; Bahner, Daniel T.

    2018-01-01

    In this study we investigated the extent to which faculty interaction contributed to Latina/o student perceptions of their learning, using a sample of 10,071 Latina/o students who took the Community College Survey of Student Engagement. Findings were disaggregated for men and women, but results were quite similar between the 2 groups. Frequent…

  2. Predicting Academic Success and Psychological Wellness in a Sample of Canadian Undergraduate Students

    Science.gov (United States)

    Chow, Henry P. H.

    2010-01-01

    Introduction: University students need to cope with a complex new life role and to achieve academic success. This article explores the academic performance and psychological well-being among university students in a western Canadian city. Method: Using a convenience sample, a total of 501 undergraduate students in Regina, Saskatchewan took part in…

  3. Comparison with the Typical College Student Predicts Graduation When Identity Is Uncertain

    Science.gov (United States)

    Lane, David J.

    2017-01-01

    This study investigated the effect of personal identity and social comparison on college graduation. First-year college students completed an online survey measuring exploration and commitment to personal identity and perceptions of the prototypical student. Those who perceived the typical student as favorable but dissimilar to themselves had the…

  4. Predicting the Motivation in College-Aged Learning Disabled Students Based on the Academic Motivation Scale

    Science.gov (United States)

    Luna, Alberto D.

    2013-01-01

    Given the paucity of research on factors associated with motivation in learning disabled college students, the present study investigated the motivation levels in college students with learning disabilities. The Academic Motivation Scale (AMS) has been validated cross-nationally and across all educational age groups of students having various…

  5. Situational Judgment Tests and Their Predictiveness of College Students' Success: The Influence of Faking

    Science.gov (United States)

    Peeters, Helga; Lievens, Filip

    2005-01-01

    There is increasing interest in using situational judgment tests (SJTs) to supplement traditional student admission procedures. An important unexplored issue is whether students can intentionally distort or fake their responses on SJTs. This study examined the fakability of an SJT of college students' performance. Two hundred ninety-three…

  6. The Moderating Effect of Personality Traits on Advisor Relationships in Predicting Doctoral Student Burnout

    Science.gov (United States)

    Kosh, Emily P.

    2014-01-01

    Personality affects relationships. During the doctoral education, the second most important factor in degree completion, after financial support, is the student-advisor relationship. Approximately half of doctoral students do not finish their degrees. While it is known mentors have a profound impact on the success of doctoral students, the effect…

  7. What Factors Predict Undergraduate Students' Use of Technology for Learning? A Case from Hong Kong

    Science.gov (United States)

    Lai, Chun; Wang, Qiu; Lei, Jing

    2012-01-01

    A sound understanding of technology use from the learners' perspective is crucial. This study intends to contribute to our understanding on student technology use by focusing on identifying the factors that influence students' adoption of technology for learning and the relationships between these factors. Students studying at a Hong Kong…

  8. Prediction of Student Course Selection in Online Higher Education Institutes Using Neural Network

    Science.gov (United States)

    Kardan, Ahmad A.; Sadeghi, Hamid; Ghidary, Saeed Shiry; Sani, Mohammad Reza Fani

    2013-01-01

    Students are required to choose courses they are interested in for the coming semester. Due to restrictions, including lack of sufficient resources and overheads of running several courses, some universities might not offer all of a student's desirable courses. Universities must know every student's demands for every course prior to each semester…

  9. Comparison of Efficacy and Threat Perception Processes in Predicting Smoking among University Students Based on Extended Parallel Process Model

    Directory of Open Access Journals (Sweden)

    S. Bashirian

    2014-04-01

    Full Text Available Introduction & Objective: The survey of smoking as the most toxic, common and cheapest ad-diction, and its psychological and demographic variables especially among the youth who are efficient and constructive individuals of the society is of great importance. This study was performed to compare efficacy and threat perception in predicting cigarette smoking among university students based on Expended Parallel Process Model (EPPM. Material & Methods: This cross sectional descriptive study was carried out on 700 college stu-dents of Hamadan recruited with a stratified sampling method. The participants completed a self-administered questionnaire including demographic characteristics, smoking status and EPPM Data analysis was done with the SPSS software (version 16, using t-test, one way ANOVA, Pierson correlation and logistic regression methods. Results: The average scores of threat and efficacy perception were 39.7 and 38.6, respectively. The prevalence of cigarette smoking among participants was 27.1 percent. Also, there were significant differences between the average score of efficacy perception and age, gender, his-tory of drug abuse and dwelling of students (P<0.05. Efficacy and threat perception both predicted student cigarette smoking. Conclusions: Cognitive mediating process of threat perception was a more powerful predictor of cigarette smoking as an unsafe behavior. Therefore, increasing self efficacy and response efficacy of university students aimed at facilitating the acceptance of safe behavior could be note-worthy as a principle in education. (Sci J Hamadan Univ Med Sci 2014; 21 (1:58-65

  10. Predicting Student Success in a Major's Introductory Biology Course via Logistic Regression Analysis of Scientific Reasoning Ability and Mathematics Scores

    Science.gov (United States)

    Thompson, E. David; Bowling, Bethany V.; Markle, Ross E.

    2018-02-01

    Studies over the last 30 years have considered various factors related to student success in introductory biology courses. While much of the available literature suggests that the best predictors of success in a college course are prior college grade point average (GPA) and class attendance, faculty often require a valuable predictor of success in those courses wherein the majority of students are in the first semester and have no previous record of college GPA or attendance. In this study, we evaluated the efficacy of the ACT Mathematics subject exam and Lawson's Classroom Test of Scientific Reasoning in predicting success in a major's introductory biology course. A logistic regression was utilized to determine the effectiveness of a combination of scientific reasoning (SR) scores and ACT math (ACT-M) scores to predict student success. In summary, we found that the model—with both SR and ACT-M as significant predictors—could be an effective predictor of student success and thus could potentially be useful in practical decision making for the course, such as directing students to support services at an early point in the semester.

  11. WaLIDD score, a new tool to diagnose dysmenorrhea and predict medical leave in university students

    Science.gov (United States)

    Teherán, Aníbal A; Piñeros, Luis Gabriel; Pulido, Fabián; Mejía Guatibonza, María Camila

    2018-01-01

    Background Dysmenorrhea is a frequent and misdiagnosed symptom affecting the quality of life in young women. A working ability, location, intensity, days of pain, dysmenorrhea (WaLIDD) score was designed to diagnose dysmenorrhea and to predict medical leave. Methods This cross-sectional design included young medical students, who completed a self-administered questionnaire that contained the verbal rating score (VRS; pain and drug subscales) and WaLIDD scales. The correlation between scales was established through Spearman test. The area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and likelihood ratio (LR +/−) were evaluated to diagnose students availing medical leave due to dysmenorrhea; moreover, to predict medical leave in students with dysmenorrhea, a binary logistic regression was performed. Results In all, 585 students, with a mean age of 21 years and menarche at 12 years, participated. Most of them had regular cycles, 5 days of menstrual blood flow and 1–2 days of lower abdominal pain. The WaLIDD scale presented an adequate internal consistency and strong correlation with VRS subscales. With a cutoff of >6 for WaLIDD and 2 for VRS subscales (drug subscale and pain subscale) to identify students with dysmenorrhea, these scales presented an area under the curve (AUC) ROC of 0.82, 0.62, and 0.67, respectively. To identify students taking medical leave due to dysmenorrhea, WaLIDD (cutoff >9) and VRS subscales (cutoff >2) presented an AUC ROC of 0.97, 0.68, and 0.81; moreover, the WaLIDD scale showed a good LR +14.2 (95% CI, 13.5–14.9), LR −0.00 (95% CI, undefined), and predictive risk (OR 5.38; 95% CI, 1.78–16.2). Conclusion This research allowed a comparison between two multidimensional scales regarding their capabilities, one previously validated and a new one, to discriminate among the general population of medical students, among those with dysmenorrhea or those availing medical leave secondary to dysmenorrhea

  12. What do we need to know to predict ENSO? Student-centered learning in a Master course in Climate Physics

    Science.gov (United States)

    Lübbecke, Joke; Glessmer, Mirjam

    2017-04-01

    An important learning outcome of a Master of Sciences program is to empower students to understand which information they need, how they can gain the required knowledge and skills, and how to apply those to solve a given scientific problem. In designing a class on the El-Nino-Southern-Oscillation (ENSO) for students in the Climate Physics program at Kiel University, Germany, we have implemented various active learning strategies to meet this goal. The course is guided by an overarching question, embedded in a short story: What would we need to know to successfully predict ENSO? The students identify desired learning outcomes and collaboratively construct a concept map which then serves as a structure for the 12 weeks of the course, where each individual topic is situated in the larger context of the students' own concept map. Each learning outcome of the course is therefore directly motivated by a need to know expressed by the students themselves. During each session, students are actively involved in the learning process. They work individually or in small groups, for example testing different index definitions, analyzing data sets, setting up simple numerical models and planning and constructing hands-on experiments to demonstrate physical processes involved in the formation of El Niño events. The instructor's role is to provide the necessary background information and guide the students where it is needed. Insights are shared between groups as students present their findings to each other and combine the information, for example by cooperatively constructing a world map displaying the impacts of ENSO or by exchanging experts on different ENSO oscillator theories between groups. Development of this course was supported by the PerLe Fonds for teaching innovations at Kiel University. A preliminary evaluation has been very positive with students in particular appreciating their active involvement in the class.

  13. Validity of Medical Student Questionnaire Data in Prediction of Rural Practice Choice and Its Association With Service Orientation.

    Science.gov (United States)

    Shannon, C Ken; Jackson, Jodie

    2015-01-01

    The validity of medical student projection of, and predictors for, rural practice and the association of a measure of service orientation, projected practice accessibility to the indigent, were investigated. West Virginia (WV) medical student online pre- and postrural rotation questionnaire data were collected during the time period 2001-2009. Of the 1,517 respondent students, submissions by 1,271 met the time interval criterion for inclusion in analyses. Subsequent WV licensing data were available for 461 in 2013. These 2 databases were used to assess for validity of projection of rural practice, for predictors of rural practice, and for student projected accessibility of the future practice to indigent patients. There were statistically significant associations between both pre- and postrotation projections of rural practice and subsequent rural practice. The most significant independent predictors of rural practice were student rural background, reported primary care intent, prediction of rural practice and projection of greater accessibility of the future practice to indigent patients. For scoring of practice access, there were trends for higher scoring by rural students and rural practitioners, with greater pre-post increases for those with urban hometowns. This study demonstrates the utility of medical student questionnaires for projections of numbers of future rural physicians. It suggests that students with a rural background, rural practice intent, or greater service orientation are more likely to enter rural practice. It also suggests that students, particularly those with urban hometowns, are influenced by rural rotation experiences in forecasting greater practice accessibility and in entering rural practice. © 2015 National Rural Health Association.

  14. How the study of online collaborative learning can guide teachers and predict students' performance in a medical course.

    Science.gov (United States)

    Saqr, Mohammed; Fors, Uno; Tedre, Matti

    2018-02-06

    Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students' performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance. Interaction data were extracted from the learning management system (LMS) forum module of the Surgery course in Qassim University, College of Medicine. The data were analyzed using social network analysis. The analysis included visual as well as a statistical analysis. Correlation with students' performance was calculated, and automatic linear regression was used to predict students' performance. By using social network analysis, we were able to analyze a large number of interactions in online collaborative discussions and gain an overall insight of the course social structure, track the knowledge flow and the interaction patterns, as well as identify the active participants and the prominent discussion moderators. When augmented with calculated network parameters, SNA offered an accurate view of the course network, each user's position, and level of connectedness. Results from correlation coefficients, linear regression, and logistic regression indicated that a student's position and role in information relay in online case discussions, combined with the strength of that student's network (social capital), can be used as predictors of performance in relevant settings. By using social network analysis, researchers can analyze the social structure of an online course and reveal important information

  15. Supine Lateral Bending Radiographs Predict the Initial In-brace Correction of the Providence Brace in Patients With Adolescent Idiopathic Scoliosis

    DEFF Research Database (Denmark)

    Ohrt-Nissen, Søren; Hallager, Dennis Winge; Gehrchen, Poul Martin

    2016-01-01

     ± 10°). Mean difference for thoracic curves was 0.2° (LOA ± 8°), for thoracolumbar/lumbar curves 0.9° (LOA ± 10°) and for double major curves 0.4° (LOA ± 16). CONCLUSION: SLBR provide a close estimation to the expected in-brace correction with a mean difference of less than one degree. SLRB could...

  16. Electroweak corrections

    International Nuclear Information System (INIS)

    Beenakker, W.J.P.

    1989-01-01

    The prospect of high accuracy measurements investigating the weak interactions, which are expected to take place at the electron-positron storage ring LEP at CERN and the linear collider SCL at SLAC, offers the possibility to study also the weak quantum effects. In order to distinguish if the measured weak quantum effects lie within the margins set by the standard model and those bearing traces of new physics one had to go beyond the lowest order and also include electroweak radiative corrections (EWRC) in theoretical calculations. These higher-order corrections also can offer the possibility of getting information about two particles present in the Glashow-Salam-Weinberg model (GSW), but not discovered up till now, the top quark and the Higgs boson. In ch. 2 the GSW standard model of electroweak interactions is described. In ch. 3 some special techniques are described for determination of integrals which are responsible for numerical instabilities caused by large canceling terms encountered in the calculation of EWRC effects, and methods necessary to get hold of the extensive algebra typical for EWRC. In ch. 4 various aspects related to EWRC effects are discussed, in particular the dependence of the unknown model parameters which are the masses of the top quark and the Higgs boson. The processes which are discussed are production of heavy fermions from electron-positron annihilation and those of the fermionic decay of the Z gauge boson. (H.W.). 106 refs.; 30 figs.; 6 tabs.; schemes

  17. Universality of quantum gravity corrections.

    Science.gov (United States)

    Das, Saurya; Vagenas, Elias C

    2008-11-28

    We show that the existence of a minimum measurable length and the related generalized uncertainty principle (GUP), predicted by theories of quantum gravity, influence all quantum Hamiltonians. Thus, they predict quantum gravity corrections to various quantum phenomena. We compute such corrections to the Lamb shift, the Landau levels, and the tunneling current in a scanning tunneling microscope. We show that these corrections can be interpreted in two ways: (a) either that they are exceedingly small, beyond the reach of current experiments, or (b) that they predict upper bounds on the quantum gravity parameter in the GUP, compatible with experiments at the electroweak scale. Thus, more accurate measurements in the future should either be able to test these predictions, or further tighten the above bounds and predict an intermediate length scale between the electroweak and the Planck scale.

  18. Predicting Heavy Alcohol Use in College Students: Interactions Among Socialization of Coping, Alcohol Use Onset, and Physiological Reactivity.

    Science.gov (United States)

    Stanger, Sarah; Abaied, Jamie; Wagner, Caitlin

    2016-05-01

    Early age at onset of alcohol use is a risk factor for later heavy alcohol use, but some individuals are buffered from this risk. To better understand this process, this study investigated the interactive contributions of parental coping suggestions, skin conductance level reactivity (SCLR), and age at onset of alcohol use on heavy alcohol use in college students. College students (N = 146, 77% female) reported their age at onset of alcohol use, frequency of recent heavy alcohol use, and their parents' coping suggestions; SCLR was monitored as participants completed a laboratory challenge task. In addition, students' parents (N = 73, 77% mothers) reported on their coping suggestions. Results indicated that in the presence of physiological risk only (blunted SCLR, late age at onset of alcohol use), higher frequencies of engagement and disengagement parental coping suggestions were protective against heavy alcohol use in college students. However, if both risk factors were present (blunted SCLR, early age at onset of alcohol use), more engagement suggestions predicted more heavy alcohol use among college students. These findings extend previous findings on the impact of parenting on heavy alcohol use among college students and provide novel evidence for the moderating role of sympathetic stress reactivity.

  19. [Evaluation of thermal comfort in a student population: predictive value of an integrated index (Fanger's predicted mean value].

    Science.gov (United States)

    Catenacci, G; Terzi, R; Marcaletti, G; Tringali, S

    1989-01-01

    Practical applications and predictive values of a thermal comfort index (Fanger's PRV) were verified on a sample school population (1236 subjects) by studying the relationships between thermal sensations (subjective analysis), determined by means of an individual questionnaire, and the values of thermal comfort index (objective analysis) obtained by calculating the PMV index individually in the subjects under study. In homogeneous conditions of metabolic expenditure rate and thermal impedence from clothing, significant differences were found between the two kinds of analyses. At 22 degrees C mean radiant and operative temperature, the PMV values averaged 0 and the percentage of subjects who experienced thermal comfort did not exceed 60%. The high level of subjects who were dissatisfied with their environmental thermal conditions confirms the doubts regarding the use of the PMV index as a predictive indicator of thermal comfort, especially considering that the negative answers were not homogeneous nor attributable to the small thermal fluctuations (less than 0.5 degree C) measured in the classrooms.

  20. Using the Theory of Planned Behavior to Predict College Students' Intention to Intervene With a Suicidal Individual.

    Science.gov (United States)

    Aldrich, Rosalie S

    2015-01-01

    Suicide among college students is an issue of serious concern. College peers may effectively intervene with at-risk persons due to their regular contact and close personal relationships with others in this population of significantly enhanced risk. The current study was designed to investigate whether the theory of planned behavior constructs predicted intention to intervene when a college peer is suicidal. Undergraduate students (n = 367) completed an on-line questionnaire; they answered questions about their attitudes, subjective norms, perceived behavioral control regarding suicide and suicide intervention, as well as their intention to intervene when someone is suicidal. The data were analyzed using multiple regression. The statistical significance of this cross-sectional study indicates that the theory of planned behavior constructs predicts self-reported intention to intervene with a suicidal individual. Theory of planned behavior is an effective framework for understanding peers' intention to intervene with a suicidal individual.

  1. Opportunities to Learn in School and at Home: How can they predict students' understanding of basic science concepts and principles?

    Science.gov (United States)

    Wang, Su; Liu, Xiufeng; Zhao, Yandong

    2012-09-01

    As the breadth and depth of economic reforms increase in China, growing attention is being paid to equalities in opportunities to learn science by students of various backgrounds. In early 2009, the Chinese Ministry of Education and Ministry of Science and Technology jointly sponsored a national survey of urban eighth-grade students' science literacy along with their family and school backgrounds. The present study focused on students' understanding of basic science concepts and principles (BSCP), a subset of science literacy. The sample analyzed included 3,031 students from 109 randomly selected classes/schools. Correlation analysis, one-way analysis of variance, and two-level linear regression were conducted. The results showed that having a refrigerator, internet, more books, parents purchasing books and magazines related to school work, higher father's education level, and parents' higher expectation of the education level of their child significantly predicted higher BSCP scores; having siblings at home, owning an apartment, and frequently contacting teachers about the child significantly predicted lower BSCP scores. At the school level, the results showed that being in the first-tier or key schools, having school libraries, science popularization galleries, computer labs, adequate equipment for teaching, special budget for teacher training, special budget for science equipment, and mutual trust between teachers and students significantly predicated higher BSCP scores; and having science and technology rooms, offering science and technology interest clubs, special budget for science curriculum development, and special budget for science social practice activities significantly predicted lower BSCP scores. The implications of the above findings are discussed.

  2. Can machine learning on learner analytics produce a predictive model on student performance?

    OpenAIRE

    Busch, John; Hanna, Philip; O'Neill, Ian; McGowan, Aidan; Collins, Matthew

    2017-01-01

    The aim of this research is to analysis past student learner analytics using machine learning algorithms that had undertaken a web development and programming module. By specifically using the access and error web server logs from each student web server it provides a deeper learner analytic data. The web server logs every web file access and error access from a browser so in turn each data file can directly relate to a student's engagement level and assessment strategy. Each log holds severa...

  3. Predictive Factors of Exercise Behaviors of Junior High School Students in Chonburi Province

    OpenAIRE

    Tanida Julvanichpong

    2016-01-01

    Exercise has been regarded as a necessary and important aspect to enhance physical performance and psychology health. Body weight statistics of students in junior high school students in Chonburi Province beyond a standard risk of obesity. Promoting exercise among Junior high school students in Chonburi Province, essential knowledge concerning factors influencing exercise is needed. Therefore, this study aims to (1) determine the levels of perceived exercise behavior, exercise behavior in the...

  4. [Negative and positive predictive relationships between coping strategies and the three dimensions of burnout among Hungarian medical students].

    Science.gov (United States)

    Ádám, Szilvia; Nistor, Anikó; Nistor, Katalin; Hazag, Anikó

    2014-08-10

    Effective management and prevention of widespread burnout among medical students in Hungary require thorough understanding of its relations to coping strategies, which lacks sufficient data. To explore the prevalence of burnout and its relations to coping strategies among medical students. Cross-sectional study with 292 participants. Burnout was assessed by the Maslach Burnout Inventory-Student Survey. Coping strategies were evaluated by the Folkman-Lazarus Ways of Coping Questionnaire and questions about health-maintenance behaviours. Associations between burnout and coping strategies were explored with linear regression analyses. The prevalence of high-level burnout was 25-56%. Both problem-focused coping and support-seeking were protective factors of exhaustion and cynicism, however, they predicted reduced personal accomplishment. Emotion-focused coping predicted exhaustion and cynicism and correlated negatively with reduced personal accomplishment. Health-maintenance behaviours were protective factors for exhaustion and predicted reduced personal accomplishment. Deployment of coping strategies that target the most prevalent burnout dimension may improve effective management of burnout.

  5. The Role of Early Maladaptive Schemas in Prediction of Dysfunctional Attitudes toward Drug Abuse among Students of university

    Directory of Open Access Journals (Sweden)

    NedaNaeemi

    2016-07-01

    Full Text Available Drug addiction as the most serious social issue of the world has different sociological, psychological, legal, and political aspects. In this regard, the purpose of this study is to determine the role of early maladaptive schemas in prediction of dysfunctional attitudes toward drug abuse among students of Islamic Azad Universities in Tehran Province, Iran. Statistical population of this study includes all students of Islamic Azad Universities in Tehran Province during 2013 and sample size is equal to 300 members that are randomly chosen. First, the name of university branches in Tehran Province were determined then three branches were randomly chosen out of them and then 300 members were chosen from those branches using random sampling method. All sample members filled out Young Schema Questionnaire Short Form and Dysfunctional Attitude Scale (DAS toward drug. Data were analyzed through regression correlation method and SPSS22 software. The obtained findings indicated a significant relation (P<0/05 between early maladaptive schemas and dysfunctional attitude toward drug abuse among students. Early maladaptive schemas can predict dysfunctional attitudes toward drug among students.

  6. The Theory of Planned Behavior as it predicts potential intention to seek mental health services for depression among college students.

    Science.gov (United States)

    Bohon, Lisa M; Cotter, Kelly A; Kravitz, Richard L; Cello, Philip C; Fernandez Y Garcia, Erik

    2016-01-01

    Between 9.5% and 31.3% of college students suffer from depression (American college health association national college health assessment II: reference group executive summary spring 2013. Amer. Coll. Health Assoc. 2013; Eagan K, Stolzenberg EB, Ramirez JJ, Aragon, MC, Suchard, RS, Hurtado S. The American freshman: national norms fall 2014. Higher Educ. Res. Inst.; 2015). Universities need to understand the factors that relate to care-seeking behavior. Across 3 studies, to relate attitudes, social norms, and perceived behavioral control to intention to seek mental health services, and to investigate barriers to care-seeking. University college students (N = 845, 64% female, 26% male, and 10% unspecified). New measures were created in Studies 1 and 2, and were examined using structural equation modeling in Study 3. Partially consistent with the Theory of Planned Behavior (Ajzen, I, Fishbein, M. Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice-Hall; 1980), a model with an excellent fit revealed that more positive attitudes about care and higher perceived behavioral control directly predicted higher intention to seek mental health services. Educating college students about mental health disorders and treatments, enhancing knowledge about available services, and addressing limited access to long-term care might improve treatment rates for students suffering from depression.

  7. Working toward Literacy in Correctional Education ESL

    Science.gov (United States)

    Gardner, Susanne

    2014-01-01

    Correctional Education English as a Second Language (ESL) literacy programs vary from state to state, region to region. Some states enroll their correctional ESL students in adult basic education (ABE) classes; other states have separate classes and programs. At the Maryland Correctional Institution in Jessup, the ESL class is a self-contained…

  8. Uncorrected and Corrected Distance Visual Acuity, Predictability, Efficacy, and Safety after Femtosecond Laser in Situ Keratomileusis (FS-LASIK) and Refractive Lenticule extraction (ReLEx) for Moderate and High Myopia

    DEFF Research Database (Denmark)

    Vestergaard, Anders; Justesen, Birgitte Larsen; Melsen, Charlotte

    Title: Uncorrected and Corrected Distance Visual Acuity, Predictability, Efficacy, and Safety after Femtosecond Laser in Situ Keratomileusis (FS-LASIK) and Refractive Lenticule extraction (ReLEx) for Moderate and High Myopia. Vestergaard A., Justesen B., Melsen C., Lyhne N., Department of Ophthal......Title: Uncorrected and Corrected Distance Visual Acuity, Predictability, Efficacy, and Safety after Femtosecond Laser in Situ Keratomileusis (FS-LASIK) and Refractive Lenticule extraction (ReLEx) for Moderate and High Myopia. Vestergaard A., Justesen B., Melsen C., Lyhne N., Department...... predictability, efficacy and safety after femtosecond LASIK (FS-LASIK) with ReLEx. Setting: Department of Ophthalmology, Odense University Hospital, Denmark. Methods: Retrospective study of results after FS-LASIK and ReLEx (including ReLEx flex, ReLEx pseudo-smile, and ReLEx smile). In total, 228 eyes were...... treated with FS-LASIK and 83 eyes with ReLEx, at the Department of Ophthalmology, Odense University Hospital in the period of April to November 2011. Only otherwise healthy myopic eyes with up to 3.00 D of astigmatism and with CDVA ≤ 0.30 (logMAR) before surgery were included in this study. FS-LASIK flaps...

  9. Internet Self-Efficacy Does Not Predict Student Use of Internet-Mediated Educational Technology

    Science.gov (United States)

    Buchanan, Tom; Joban, Sanjay; Porter, Alan

    2014-01-01

    Two studies tested the hypothesis that use of learning technologies among undergraduate psychology students was associated with higher Internet self-efficacy (ISE). In Study 1, the ISE scores of 86 students were found not to be associated with either attitudes towards, or measured use of, blogs and wikis as part of an IT skills course. ISE was…

  10. Is ATAR Useful for Predicting the Success of Australian Students in Initial Teacher Education?

    Science.gov (United States)

    Wright, Vince J.

    2015-01-01

    Quality teaching is the most significant systemic factor contributing to student achievement. Attracting, developing and retaining effective teachers are important goals for Australia as they are for all nations. Debate rages currently about criteria for selection of students into Initial Teacher Education (ITE). The Australian Tertiary Admission…

  11. Early Prediction of Student Self-Regulation Strategies by Combining Multiple Models

    Science.gov (United States)

    Sabourin, Jennifer L.; Mott, Bradford W.; Lester, James C.

    2012-01-01

    Self-regulated learning behaviors such as goal setting and monitoring have been found to be crucial to students' success in computer-based learning environments. Consequently, understanding students' self-regulated learning behavior has been the subject of increasing interest. Unfortunately, monitoring these behaviors in real-time has proven…

  12. Mindfulness predicts student nurses' communication self-efficacy: A cross-national comparative study.

    Science.gov (United States)

    Sundling, Vibeke; Sundler, Annelie J; Holmström, Inger K; Kristensen, Dorte Vesterager; Eide, Hilde

    2017-08-01

    The aim of this study was to compare student nurses' communication self-efficacy, empathy, and mindfulness across two countries, and to analyse the relationship between these qualities. The study had a cross-sectional design. Data was collected from final year student nurses in Norway and Sweden. Communication self-efficacy, empathy, and mindfulness were reported by questionnaires; Clear-cut communication with patients, Jefferson Scale of Empathy, and Langer 14 items mindfulness scale. The study included 156 student nurses, 94 (60%) were Swedish. The mean communication self-efficacy score was 119 (95% CI 116-122), empathy score 115 (95% CI 113-117) and mindfulness score 79 (95% CI 78-81). A Mann-Whitney test showed that Swedish students scored significantly higher on communication self-efficacy, empathy, and mindfulness than Norwegian students did. When adjusted for age, gender, and country in a multiple linear regression, mindfulness was the only independent predictor of communication self-efficacy. The Swedish student nurses in this study scored higher on communication self-efficacy, empathy, and mindfulness than Norwegian students did. Student nurses scoring high on mindfulness rated their communication self-efficacy higher. A mindful learning approach may improve communication self-efficacy and possibly the effect of communication skills training. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Students' Engagement with a Collaborative Wiki Tool Predicts Enhanced Written Exam Performance

    Science.gov (United States)

    Stafford, Tom; Elgueta, Herman; Cameron, Harriet

    2014-01-01

    We introduced voluntary wiki-based exercises to a long-running cognitive psychology course, part of the core curriculum for an undergraduate degree in psychology. Over 2 yearly cohorts, students who used the wiki more also scored higher on the final written exam. Using regression analysis, it is possible to account for students' tendency to score…

  14. Spelling Ability in College Students Predicted by Decoding, Print Exposure, and Vocabulary

    Science.gov (United States)

    Ocal, Turkan; Ehri, Linnea

    2017-01-01

    This study examines students' exposure to print, vocabulary and decoding as predictors of spelling skills. Participants were 42 college students (Mean age 22.5, SD = 7.87; 31 females and 11 males). Hierarchical regression analyses showed that most of the variance in spelling was explained by vocabulary knowledge. When vocabulary was entered first…

  15. Psychological Distress among Nursing, Physiotherapy and Occupational Therapy Students: A Longitudinal and Predictive Study

    Science.gov (United States)

    Nerdrum, Per; Rustoen, Tone; Helge Ronnestad, Michael

    2009-01-01

    In this study, we present longitudinal data on changes in psychological distress among 232 Norwegian undergraduate students of nursing, physiotherapy, and occupational therapy. Psychological distress was assessed by applying the 12-item version of the General Health Questionnaire. Nursing students became substantially more distressed during the…

  16. What Predicts Health Students' Self-Reported Preparedness to Work in Indigenous Health Settings?

    Science.gov (United States)

    Bullen, Jonathan; Roberts, Lynne; Hoffman, Julie

    2017-01-01

    Australian undergraduate programs are implementing curriculum aimed at better preparing graduates to work in culturally diverse settings, but there remains uncertainty over the role of extant student attitudes towards Indigenous Australians. To begin to address this, we obtained baseline data on student attitudes upon entry to tertiary education.…

  17. The Predictive Role of Teaching Styles on Omani Students' Mathematics Motivation

    Science.gov (United States)

    Aldhafri, Said; Alrajhi, Marwa

    2014-01-01

    The current study explored the effects of two teaching styles, authoritative and authoritarian, on students' mathematics motivation. The two motivational constructs examined were intrinsic and extrinsic motivation. Data were collected from 425 Omani 8th grade students (males = 202/females = 223, mean age = 13.44, SD = 0.79). Through two…

  18. Predicting Students' Attitudes towards Advertising on a University Virtual Learning Environment (VLE)

    Science.gov (United States)

    Ogba, Ike-Elechi; Saul, Neil; Coates, Nigel F.

    2012-01-01

    Most if not all UK universities and many in other parts of the world support their student learning via a virtual learning environment (VLE). Online resources are going to be increasingly important to students as the internet is very much part of their lives. However, the VLE will require ongoing investment to keep pace with technological…

  19. Predicting Digital Informal Learning: An Empirical Study among Chinese University Students

    Science.gov (United States)

    He, Tao; Zhu, Chang; Questier, Frederik

    2018-01-01

    Although the adoption of digital technology has gained considerable attention in higher education, currently research mainly focuses on implementation in formal learning contexts. Investigating what factors influence students' digital informal learning is still unclear and limited. To understand better university students' digital informal…

  20. Predicting Persistence and Withdrawal: An Analysis of Factors Relating to Students' Choice of Course.

    Science.gov (United States)

    de Rome, E. A.; Wieneke, C. E.

    Information relating to course choice and commitment, and use of pre-enrollment information and advisory resources, were collected at the time of enrollment in 1980 from 1,375 first-year students at the University of New South Wales. The students were enrolled in the faculties of arts, architecture, and engineering. Multivariate analyses were used…

  1. Analytics to Action: Predictive Model Outcomes and a Communication Strategy for Student Persistence

    Science.gov (United States)

    Miller, Nathan Brad; Bell, Bryan

    2016-01-01

    Increased federal attention to student completion metrics and uncertain financial forecasts have heightened the tenor of student retention conversations. Improved institutional retention rates will lead to higher completion rates and relieve some funding concerns. To accomplish these improvements, institutions have invested in analytics to better…

  2. Predicting and Explaining Students' Stress with the Demand-Control Model: Does Neuroticism Also Matter?

    Science.gov (United States)

    Schmidt, Laura I.; Sieverding, Monika; Scheiter, Fabian; Obergfell, Julia

    2015-01-01

    University students often report high stress levels, and studies even suggest a recent increase. However, there is a lack of theoretically based research on the structural conditions that influence students' perceived stress. The current study compared the effects of Karasek's demand-control dimensions with the influence of neuroticism to address…

  3. Preschool Teaching Students' Prediction of Decision Making Strategies and Academic Achievement on Learning Motivations

    Science.gov (United States)

    Acat, M. Bahaddin; Dereli, Esra

    2012-01-01

    The purpose of this study was to identify problems and motivation sources and strategies of decision-making of the students' attending preschool education teacher department, was to determine the relationship between learning motivation and strategies of decision-making, academic achievement of students, was to determine whether strategies of…

  4. Using Learning Analytics to Predict (and Improve) Student Success: A Faculty Perspective

    Science.gov (United States)

    Dietz-Uhler, Beth; Hurn, Janet E.

    2013-01-01

    Learning analytics is receiving increased attention, in part because it offers to assist educational institutions in increasing student retention, improving student success, and easing the burden of accountability. Although these large-scale issues are worthy of consideration, faculty might also be interested in how they can use learning analytics…

  5. Predicting Burnout and Career Choice Satisfaction in Counseling Psychology Graduate Students

    Science.gov (United States)

    Clark, Heddy Kovach; Murdock, Nancy L.; Koetting, Kristin

    2009-01-01

    Counseling psychology doctoral students (N = 284) from 53 training programs throughout the United States anonymously completed online measures of burnout, career choice satisfaction, global stress, role conflict, social support (from family/friends, advisors, other students) and psychological sense of community (SOC) in the doctoral program. Two…

  6. Reductions in Negative Automatic Thoughts in Students Attending Mindfulness Tutorials Predicts Increased Life Satisfaction

    Science.gov (United States)

    Ritvo, Paul; Vora, Khushboo; Irvine, Jane; Mongrain, Myriam; Azargive, Saam; Azam, Muhammad Abid; Pirbaglou, Meysam; Guglietti, Crissa; Wayne, Noah; Perez, Daniel Felipe; Cribbie, Rob

    2013-01-01

    University education confronts students with stressful developmental challenges that can lead to mental health problems. Innovative programs must address an increasing prevalence of these problems but are impeded by the high costs involved. In this study, thirty-nine undergraduate students attended weekly one hour mindfulness meditation tutorials…

  7. Understanding and Predicting Student Self-Regulated Learning Strategies in Game-Based Learning Environments

    Science.gov (United States)

    Sabourin, Jennifer L.; Shores, Lucy R.; Mott, Bradford W.; Lester, James C.

    2013-01-01

    Self-regulated learning behaviors such as goal setting and monitoring have been found to be crucial to students' success in computer-based learning environments. Consequently, understanding students' self-regulated learning behavior has been the subject of increasing attention. Unfortunately, monitoring these behaviors in real-time has…

  8. Predicting Academic Success of Health Science Students for First Year Anatomy and Physiology

    Science.gov (United States)

    Anderton, Ryan S.; Evans, Tess; Chivers, Paola T.

    2016-01-01

    Students commencing tertiary education enter through a number of traditional and alternative academic pathways. As a result, tertiary institutions encounter a broad range of students, varying in demographic, previous education, characteristics and academic achievement. In recent years, the relatively constant increase in tertiary applications in…

  9. Bricks or Clicks? Predicting Student Intentions in a Blended Learning Buffet

    Science.gov (United States)

    Hood, Michelle

    2013-01-01

    This study examined predictors of students' intentions to access face-to-face (f2f) or online options for lectures and tutorials in a buffet-style blended learning 2nd-year psychology statistics course ("N" = 113; 84% female). Students were aged 18 to 51 years ("M" = 23.16; "SD"= 6.80). Practical and technological…

  10. Predictive Modeling to Forecast Student Outcomes and Drive Effective Interventions in Online Community College Courses

    Science.gov (United States)

    Smith, Vernon C.; Lange, Adam; Huston, Daniel R.

    2012-01-01

    Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…

  11. Relative contributions of self-efficacy, self-regulation, and self-handicapping in predicting student procrastination.

    Science.gov (United States)

    Strunk, Kamden K; Steele, Misty R

    2011-12-01

    The relative contributions of self-efficacy, self-regulation, and self-handicapping student procrastination were explored. College undergraduate participants (N = 138; 40 men, 97 women, one not reporting sex) filled out the Procrastination Scale, the Self-Handicapping Scale-Short Form, and the Self-regulation and Self-handicapping scales of the Motivated Strategies for Learning Questionnaire. A hierarchical regression of the above measures indicated that self-efficacy, self-regulation, and self-handicapping all predicted scores on the Procrastination Scale, but self-regulation fully accounted for the predictive power of self-efficacy. The results suggested self-regulation and self-handicapping predict procrastination independently. These findings are discussed in relation to the literature on the concept of "self-efficacy for self-regulation" and its use in the field of procrastination research.

  12. Mental health predicts better academic outcomes: A longitudinal study of elementary school students in Chile

    OpenAIRE

    Murphy, J. Michael; Guzmán, Javier; McCarthy, Alyssa; Squicciarini, Ana María; George, Myriam; Canenguez, Katia; Dunn, Erin C.; Baer, Lee; Simonsohn, Ariela; Smoller, Jordan W.; Jellinek, Michael

    2015-01-01

    The world’s largest school-based mental health program, Habilidades para la Vida [Skills for Life, SFL], has been operating at a national scale in Chile for fifteen years. SFL’s activities include using standardized measures to screen elementary school students and providing preventive workshops to students at risk for mental health problems. This paper used SFL’s data on 37,397 students who were in first grade in 2009 and third grade in 2011 to ascertain whether first grade mental health pre...

  13. Role of Social Well-Being and Academic Vitality in Predicting the Academic Motivation in Nursing Students

    Directory of Open Access Journals (Sweden)

    Abbasi M.

    2016-02-01

    Full Text Available Aims: Due to the studentship stressful factors and challenging clinical conditions and internship, the nursing students undergo emotional exhaustion and academic burnout. The outcomes might, also, negatively affect their academic engagement and functions. The aim of this study was to explain the academic motivation of the nursing students based on the social welfare and vitality.  Instrument & Methods: In the correlational study, the nursing students of Arak University of Medical Sciences were studied in the academic year 2014-15. 210 students were selected via available sampling. Data was collected using academic motivation, Kees social welfare, and academic vitality questionnaires. Data was analyzed by SPSS 18 software using Pearson correlation and multivariate regression tests. Findings: The total mean scores of social welfare, academic motivation, and academic vitality were 98.68±13.21, 40.55±5.98, and 18.58±7.58, respectively. There were significant and positive correlations between social welfare and academic motivation (r=0.183; p<0.001 and the subscales including emotional motivation (r=0.103; p<0.048 and cognitive motivation (r=0.154; p<0.003. Due to the lack of any correlation between academic vitality and academic motivation and its sub-scales, the academic vitality could not predict the academic motivation. Nevertheless, the social welfare could predict 33% of the variance of academic motivation. Conclusion: The social welfare plays an important role to determine the academic motivation of nursing students. Nevertheless, academic vitality plays no role. 

  14. Differential effects of two types of formative assessment in predicting performance of first-year medical students.

    Science.gov (United States)

    Krasne, Sally; Wimmers, Paul F; Relan, Anju; Drake, Thomas A

    2006-05-01

    Formative assessments are systematically designed instructional interventions to assess and provide feedback on students' strengths and weaknesses in the course of teaching and learning. Despite their known benefits to student attitudes and learning, medical school curricula have been slow to integrate such assessments into the curriculum. This study investigates how performance on two different modes of formative assessment relate to each other and to performance on summative assessments in an integrated, medical-school environment. Two types of formative assessment were administered to 146 first-year medical students each week over 8 weeks: a timed, closed-book component to assess factual recall and image recognition, and an un-timed, open-book component to assess higher order reasoning including the ability to identify and access appropriate resources and to integrate and apply knowledge. Analogous summative assessments were administered in the ninth week. Models relating formative and summative assessment performance were tested using Structural Equation Modeling. Two latent variables underlying achievement on formative and summative assessments could be identified; a "formative-assessment factor" and a "summative-assessment factor," with the former predicting the latter. A latent variable underlying achievement on open-book formative assessments was highly predictive of achievement on both open- and closed-book summative assessments, whereas a latent variable underlying closed-book assessments only predicted performance on the closed-book summative assessment. Formative assessments can be used as effective predictive tools of summative performance in medical school. Open-book, un-timed assessments of higher order processes appeared to be better predictors of overall summative performance than closed-book, timed assessments of factual recall and image recognition.

  15. Diagnostic value of thallium-201 myocardial perfusion IQ-SPECT without and with computed tomography-based attenuation correction to predict clinically significant and insignificant fractional flow reserve: A single-center prospective study.

    Science.gov (United States)

    Tanaka, Haruki; Takahashi, Teruyuki; Ohashi, Norihiko; Tanaka, Koichi; Okada, Takenori; Kihara, Yasuki

    2017-12-01

    The aim of this study was to clarify the predictive value of fractional flow reserve (FFR) determined by myocardial perfusion imaging (MPI) using thallium (Tl)-201 IQ-SPECT without and with computed tomography-based attenuation correction (CT-AC) for patients with stable coronary artery disease (CAD).We assessed 212 angiographically identified diseased vessels using adenosine-stress Tl-201 MPI-IQ-SPECT/CT in 84 consecutive, prospectively identified patients with stable CAD. We compared the FFR in 136 of the 212 diseased vessels using visual semiquantitative interpretations of corresponding territories on MPI-IQ-SPECT images without and with CT-AC.FFR inversely correlated most accurately with regional summed difference scores (rSDS) in images without and with CT-AC (r = -0.584 and r = -0.568, respectively, both P system can predict FFR at an optimal cut-off of reserved.

  16. Corrective feedback via e-mail on the correct use of past tense ...

    African Journals Online (AJOL)

    panah

    2015-11-09

    Nov 9, 2015 ... Based on descriptive studies of teacher-student interaction (Lyster, 2002; Lyster, ... supplies the correct form, and clearly indicates that what the student is saying is incorrect. ..... Cognition and second language instruction.

  17. Exploiting Academic Records for Predicting Student Drop Out: a case study in Brazilian higher education

    OpenAIRE

    Sales, Allan; Balby, Leandro; Cajueiro, Adalberto

    2017-01-01

    Students’ dropout is a major concern of the Brazilian higher education institutions as it may cause waste of resources and decrease graduation rates. The early detection of students with high probability of dropping out, as well as understanding the underlying causes, are crucial for defining more effective actions toward preventing this problem. In this paper, we cast the dropout detection problem as a classification problem. We use a large sample of academic records of students across 76 co...

  18. English Learners Perception on Lecturers’ Corrective Feedback

    Directory of Open Access Journals (Sweden)

    Titien Fatmawaty Mohammad

    2016-04-01

    Full Text Available The importance of written corrective feedback (CF has been an issue of substantial debate in the literature and this controversial issue has led to a development in latest studies to draw on foreign language acquisition (FLA research as a way to further comprehend the complexities of this issue particularly how students and teachers perceive the effectiveness of written corrective feedback. This research has largely focused on students’ perception on Lecturers’ corrective feedback, perceives the usefulness of different types of corrective feedback and the reasons they have for their preferences. Qualitative data was collected from 40 EFL students in 6th semester, by means of written questionnaires, interview and observation. Four feedback strategies were employed in this research and ranked each statement by using five-point Likert scale. Findings showed that almost all students 81.43 % want correction or feedback from lecturers for the mistakes on their writing. For the type of written corrective feedback, students prefer lecturers mark their mistakes and give comment on their work with the percentage as follows: 93% students found that giving clues or comment about how to fix errors can improve their writing ability, 76.69% of the students found that error identification is the most useful type of feedback, and 57.50% of students have a positive opinion for the provision of correction which is accompanied by comment. Those percentages of students perspective is supported by students’ explanation in an open ended question of questionnaire. Pedagogical implications of the study are also discussed.

  19. Verifying the model of predicting entrepreneurial intention among students of business and non-business orientation

    Directory of Open Access Journals (Sweden)

    Zoran Sušanj

    2015-01-01

    Full Text Available This study aims to verify whether certain entrepreneurial characteristics, like entrepreneurial potential and entrepreneurial propensity, affect the level of entrepreneurial self-efficacy and desirability of entrepreneurship, and further have direct and indirect effect on entrepreneurial intentions. Furthermore, this study seeks to compare the strength of the relationship between these variables among groups of students who receive some entrepreneurship education and students outside the business sphere. Data was collected from a sample of undergraduate students of business and non-business orientation and analyzed with multi-group analysis within SEM. Results of the multi-group analysis indicate that indeed, the strength of the relationship among tested variables is more pronounced when it comes to business students. That is, mediating effect of perceived entrepreneurial self-efficacy and desirability of entrepreneurship in the relationship between entrepreneurial characteristics and intent, is significantly stronger for the business-oriented groups, in comparison to non-business orientation group. The amount of explained variance of all constructs (except entrepreneurial propensity is also larger in business students in comparison to non-business students. Educational implications of obtained results are discussed.

  20. Predicting academic performance and clinical competency for international dental students: seeking the most efficient and effective measures.

    Science.gov (United States)

    Stacey, D Graham; Whittaker, John M

    2005-02-01

    Measures used in the selection of international dental students to a U.S. D.D.S. program were examined to identify the grouping that most effectively and efficiently predicted academic performance and clinical competency. Archival records from the International Dental Program (IDP) at Loma Linda University provided data on 171 students who had trained in countries outside the United States. The students sought admission to the D.D.S. degree program, successful completion of which qualified them to sit for U.S. licensure. As with most dental schools, competition is high for admission to the D.D.S. program. The study's goal was to identify what measures contributed to a fair and accurate selection process for dental school applicants from other nations. Multiple regression analyses identified National Board Part II and dexterity measures as significant predictors of academic performance and clinical competency. National Board Part I, TOEFL, and faculty interviews added no significant additional help in predicting eventual academic performance and clinical competency.

  1. Early Prediction of Student Dropout and Performance in MOOCSs Using Higher Granularity Temporal Information

    Science.gov (United States)

    Ye, Cheng; Biswas, Gautam

    2014-01-01

    Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…

  2. RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

    Science.gov (United States)

    Ellington, Roni; Wachira, James; Nkwanta, Asamoah

    2010-01-01

    The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…

  3. Predicting College Students' Positive Psychology Associated Traits with Executive Functioning Dimensions

    Science.gov (United States)

    Marshall, Seth

    2016-01-01

    More research is needed that investigates how positive psychology-associated traits are predicted by neurocognitive processes. Correspondingly, the purpose of this study was to ascertain how, and to what extent, four traits, namely, grit, optimism, positive affect, and life satisfaction were predicted by the executive functioning (EF) dimensions…

  4. The mediating role of internet connection, virtual friends, and mood in predicting loneliness among students with and without learning disabilities in different educational environments.

    Science.gov (United States)

    Sharabi, Adi; Margalit, Malka

    2011-01-01

    This study evaluated a multidimensional model of loneliness as related to risk and protective factors among adolescents with learning disabilities (LD). The authors aimed to identify factors that mediated loneliness among 716 adolescents in Grades 10 through 12 who were studying in high schools or in Youth Education Centers for at-risk populations. There were 334 students with LD, divided into subgroups according to disability severity (three levels of testing accommodations), and 382 students without LD. Five instruments measured participants' socioemotional characteristics: loneliness, Internet communication, mood, and social and academic achievement-oriented motivation. Using structural equation modeling, the results confirmed the loneliness model and revealed that the use of the Internet to support interpersonal communication with friends predicted less intense loneliness, whereas virtual friendships with individuals whom students knew only online predicted greater loneliness. Positive and negative mood and motivation also predicted students' loneliness. In addition, the severity of LD predicted stronger loneliness feelings.

  5. Population Size Predicts Lexical Diversity, but so Does the Mean Sea Level --Why It Is Important to Correctly Account for the Structure of Temporal Data.

    Science.gov (United States)

    Koplenig, Alexander; Müller-Spitzer, Carolin

    2016-01-01

    In order to demonstrate why it is important to correctly account for the (serial dependent) structure of temporal data, we document an apparently spectacular relationship between population size and lexical diversity: for five out of seven investigated languages, there is a strong relationship between population size and lexical diversity of the primary language in this country. We show that this relationship is the result of a misspecified model that does not consider the temporal aspect of the data by presenting a similar but nonsensical relationship between the global annual mean sea level and lexical diversity. Given the fact that in the recent past, several studies were published that present surprising links between different economic, cultural, political and (socio-)demographical variables on the one hand and cultural or linguistic characteristics on the other hand, but seem to suffer from exactly this problem, we explain the cause of the misspecification and show that it has profound consequences. We demonstrate how simple transformation of the time series can often solve problems of this type and argue that the evaluation of the plausibility of a relationship is important in this context. We hope that our paper will help both researchers and reviewers to understand why it is important to use special models for the analysis of data with a natural temporal ordering.

  6. Customized versus population-based growth curves: prediction of low body fat percent at term corrected gestational age following preterm birth.

    Science.gov (United States)

    Law, Tameeka L; Katikaneni, Lakshmi D; Taylor, Sarah N; Korte, Jeffrey E; Ebeling, Myla D; Wagner, Carol L; Newman, Roger B

    2012-07-01

    Compare customized versus population-based growth curves for identification of small-for-gestational-age (SGA) and body fat percent (BF%) among preterm infants. Prospective cohort study of 204 preterm infants classified as SGA or appropriate-for-gestational-age (AGA) by population-based and customized growth curves. BF% was determined by air-displacement plethysmography. Differences between groups were compared using bivariable and multivariable linear and logistic regression analyses. Customized curves reclassified 30% of the preterm infants as SGA. SGA infants identified by customized method only had significantly lower BF% (13.8 ± 6.0) than the AGA (16.2 ± 6.3, p = 0.02) infants and similar to the SGA infants classified by both methods (14.6 ± 6.7, p = 0.51). Customized growth curves were a significant predictor of BF% (p = 0.02), whereas population-based growth curves were not a significant independent predictor of BF% (p = 0.50) at term corrected gestational age. Customized growth potential improves the differentiation of SGA infants and low BF% compared with a standard population-based growth curve among a cohort of preterm infants.

  7. Does attainment of Piaget's formal operational level of cognitive development predict student understanding of scientific models?

    Science.gov (United States)

    Lahti, Richard Dennis, II

    Knowledge of scientific models and their uses is a concept that has become a key benchmark in many of the science standards of the past 30 years, including the proposed Next Generation Science Standards. Knowledge of models is linked to other important nature of science concepts such as theory change which are also rising in prominence in newer standards. Effective methods of instruction will need to be developed to enable students to achieve these standards. The literature reveals an inconsistent history of success with modeling education. These same studies point to a possible cognitive development component which might explain why some students succeeded and others failed. An environmental science course, rich in modeling experiences, was used to test both the extent to which knowledge of models and modeling could be improved over the course of one semester, and more importantly, to identify if cognitive ability was related to this improvement. In addition, nature of science knowledge, particularly related to theories and theory change, was also examined. Pretest and posttest results on modeling (SUMS) and nature of science (SUSSI), as well as data from the modeling activities themselves, was collected. Cognitive ability was measured (CTSR) as a covariate. Students' gain in six of seven categories of modeling knowledge was at least medium (Cohen's d >.5) and moderately correlated to CTSR for two of seven categories. Nature of science gains were smaller, although more strongly correlated with CTSR. Student success at creating a model was related to CTSR, significantly in three of five sub-categories. These results suggest that explicit, reflective experience with models can increase student knowledge of models and modeling (although higher cognitive ability students may have more success), but successfully creating models may depend more heavily on cognitive ability. This finding in particular has implications in the grade placement of modeling standards and

  8. Predicting Factors Associated with Regular Physical Activity among College Students: Applying BASNEF Model

    Directory of Open Access Journals (Sweden)

    B. Moeini

    2011-10-01

    Full Text Available Introduction & Objective: One of the important problems in modern society is people's sedentary life style. The aim of this study was to determine factors associated with regular physical activity among college students based on BASNEF model.Materials & Methods: This study was a cross-sectional study carried out on 400 students in Hamadan University of Medical Sciences. Based on the assignment among different schools, classified sampling method was chosen for data gathering using a questionnaire in three parts including: demographic information, constructs of BASNEF model, and standard international physical activity questionnaire (IPAQ. Data were analyzed by SPSS-13, and using appropriate statistical tests (Chi-square, T-test and regression. Results: Based on the results, 271 students(67.8 % had low, 124 (31% moderate ,and 5 (1.2% vigorous physical activity. There was a significant relationship (c2=6.739, df= 1, P= 0.034 between their residence and physical activity and students living in dormitory were reported to have higher level of physical activity. Behavioral intention and enabling factors from the constructs of BASNEF model were the best predictors for having physical activity in students (OR=1.215, P = 0.000 and (OR=1.119, P= 0.000 respectively.Conclusion: With regard to the fact that majority of the students did not engage in enough physical activity and enabling factors were the most effective predictors for having regular physical activity in them, it seems that providing sports facilities can promote physical activity among the students.(Sci J Hamadan Univ Med Sci 2011;18(3:70-76

  9. Can We Predict Burnout among Student Nurses? An Exploration of the ICWR-1 Model of Individual Psychological Resilience

    Science.gov (United States)

    Rees, Clare S.; Heritage, Brody; Osseiran-Moisson, Rebecca; Chamberlain, Diane; Cusack, Lynette; Anderson, Judith; Terry, Victoria; Rogers, Cath; Hemsworth, David; Cross, Wendy; Hegney, Desley G.

    2016-01-01

    The nature of nursing work is demanding and can be stressful. Previous studies have shown a high rate of burnout among employed nurses. Recently, efforts have been made to understand the role of resilience in determining the psychological adjustment of employed nurses. A theoretical model of resilience was proposed recently that includes several constructs identified in the literature related to resilience and to psychological functioning. As nursing students are the future of the nursing workforce it is important to advance our understanding of the determinants of resilience in this population. Student nurses who had completed their final practicum were invited to participate in an online survey measuring the key constructs of the ICWR-1 model. 422 students from across Australia and Canada completed the survey between July 2014 and July 2015. As well as several key demographics, trait negative affect, mindfulness, self-efficacy, coping, resilience, and burnout were measured. We used structural equation modeling and found support for the major pathways of the model; namely that resilience had a significant influence on the relationship between mindfulness, self-efficacy and coping, and psychological adjustment (burnout scores). Furthermore, as predicted, Neuroticism moderated the relationship between coping and burnout. Results are discussed in terms of potential approaches to supporting nursing students who may be at risk of burnout. PMID:27486419

  10. Can we predict burnout among student nurses? An exploration of the ICWR-1 model of individual psychological resilience

    Directory of Open Access Journals (Sweden)

    Clare Samantha Rees

    2016-07-01

    Full Text Available The nature of nursing work is demanding and can be stressful. Previous studies have shown a high rate of burnout among employed nurses. Recently, efforts have been made to understand the role of resilience in determining the psychological adjustment of employed nurses. A theoretical model of resilience was proposed recently that includes several constructs identified in the literature related to resilience and to psychological functioning. As nursing students are the future of the nursing workforce it is important to advance our understanding of the determinants of resilience in this population. Student nurses who had completed their final practicum were invited to participate in an online survey measuring the key constructs of the ICWR-1 model. 422 students from across Australia and Canada completed the survey between July 2014 and July 2015. As well as several key demographics, trait negative affect, mindfulness, self-efficacy, coping, resilience and burnout were measured. We used structural equation modelling and found support for the major pathways of the model; namely that resilience had a significant influence on the relationship between mindfulness, self-efficacy and coping and psychological adjustment (burnout scores. Furthermore, as predicted, Neuroticism moderated the relationship between coping and burnout. Results are discussed in terms of potential approaches to supporting nursing students who may be at risk of burnout.

  11. Can We Predict Burnout among Student Nurses? An Exploration of the ICWR-1 Model of Individual Psychological Resilience.

    Science.gov (United States)

    Rees, Clare S; Heritage, Brody; Osseiran-Moisson, Rebecca; Chamberlain, Diane; Cusack, Lynette; Anderson, Judith; Terry, Victoria; Rogers, Cath; Hemsworth, David; Cross, Wendy; Hegney, Desley G

    2016-01-01

    The nature of nursing work is demanding and can be stressful. Previous studies have shown a high rate of burnout among employed nurses. Recently, efforts have been made to understand the role of resilience in determining the psychological adjustment of employed nurses. A theoretical model of resilience was proposed recently that includes several constructs identified in the literature related to resilience and to psychological functioning. As nursing students are the future of the nursing workforce it is important to advance our understanding of the determinants of resilience in this population. Student nurses who had completed their final practicum were invited to participate in an online survey measuring the key constructs of the ICWR-1 model. 422 students from across Australia and Canada completed the survey between July 2014 and July 2015. As well as several key demographics, trait negative affect, mindfulness, self-efficacy, coping, resilience, and burnout were measured. We used structural equation modeling and found support for the major pathways of the model; namely that resilience had a significant influence on the relationship between mindfulness, self-efficacy and coping, and psychological adjustment (burnout scores). Furthermore, as predicted, Neuroticism moderated the relationship between coping and burnout. Results are discussed in terms of potential approaches to supporting nursing students who may be at risk of burnout.

  12. More Than Only Skin Deep: Appearance Self-Concept Predicts Most of Secondary School Students' Self-Esteem

    Directory of Open Access Journals (Sweden)

    Tanja Gabriele Baudson

    2016-10-01

    Full Text Available One important goal of education is to develop students' self-esteem which, in turn, hinges on their self-concept in the academic, physical, and social domains. Prior studies have shown that physical self-concept accounts for most of the variation in self-esteem, with academic and social self-concepts playing a much lesser role. As pressure towards perfection seems to be increasing in education, appearance, and social relationships (three aspects that relate to crucial developmental tasks of adolescence, the goal of the present field study was to examine whether former findings still hold true in the light of the changing societal context. A sample of 2,950 students from a broad range of German secondary schools (47% girls, age 10–19 years responded to a recently validated German-language questionnaire assessing multiple self-concept facets (Weber & Freund, 2016. We examined which self-concept aspects predict self-esteem best and whether the pattern is comparable across genders and achievement levels using latent regression analyses. Results show that self-concept of appearance is still by far the strongest predictor (total sample: B = 0.77, SE = 0.02, p < .01 and that this is especially the case for girls and students from special educational schools. Other aspects play a much lesser role. The discussion explores why appearance is so neglected, compared to the more academic subjects, and what school can do to account for its vast importance for students' self-esteem.

  13. Predicting health literacy of students in Kermanshah University of Medical Sciences in 2016: The role of demographic variables

    Directory of Open Access Journals (Sweden)

    Arash Ziapoor

    2016-12-01

    Full Text Available Background and objective: Health literacy is a key outcome measures of health education that should be in the context of broader health promotion. This study aims to predict the health literacy of students in Kermanshah University of Medical Sciences in 1395: the role of demographic variables was performed. Methods: A descriptive correlational study on 350 students of Kermanshah University of Medical Sciences was done. Sampling was random. Data collection was conducted through a questionnaire of health literacy Montazeri et al. Information collected through software SPSS 23 and using t-tests, ANOVA and Pearson correlation coefficient were analyzed. Results: The mean (SD total score of health literacy in students was 4.04 ± 0.43. T-test and ANOVA between health literacy by gender, age, profession, education level and location have a significant relationship. Pearson correlation coefficient between the components of health literacy in research samples showed high correlation was statistically significant (P <0.01. Conclusion: The importance and need for attention to students' health literacy for health promotion as an essential factor in the impact-transition seems to be. Paper Type: Research Article.

  14. Health beliefs affect the correct replacement of daily disposable contact lenses: Predicting compliance with the Health Belief Model and the Theory of Planned Behaviour.

    Science.gov (United States)

    Livi, Stefano; Zeri, Fabrizio; Baroni, Rossella

    2017-02-01

    To assess the compliance of Daily Disposable Contact Lenses (DDCLs) wearers with replacing lenses at a manufacturer-recommended replacement frequency. To evaluate the ability of two different Health Behavioural Theories (HBT), The Health Belief Model (HBM) and The Theory of Planned Behaviour (TPB), in predicting compliance. A multi-centre survey was conducted using a questionnaire completed anonymously by contact lens wearers during the purchase of DDCLs. Three hundred and fifty-four questionnaires were returned. The survey comprised 58.5% females and 41.5% males (mean age 34±12years). Twenty-three percent of respondents were non-compliant with manufacturer-recommended replacement frequency (re-using DDCLs at least once). The main reason for re-using DDCLs was "to save money" (35%). Predictions of compliance behaviour (past behaviour or future intentions) on the basis of the two HBT was investigated through logistic regression analysis: both TPB factors (subjective norms and perceived behavioural control) were significant (pbehaviour and future intentions) and perceived benefit (only for past behaviour) as significant factors (pbehavioural control of daily replacement (behavioural control) are of paramount importance in improving compliance. With reference to the HBM, it is important to warn DDCLs wearers of the severity of a contact-lens-related eye infection, and to underline the possibility of its prevention. Copyright © 2016 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

  15. [Efficacy of absorbance ratio of ELISA antibodies [corrected] for hepatitis C virus of 3th generation in the prediction of viremia evaluated by PCR].

    Science.gov (United States)

    Vázquez-Avila, Isidro; Vera-Peralta, Jorge Manuel; Alvarez-Nemegyei, José; Rodríguez-Carvajal, Otilia

    2007-01-01

    In order to decrease the burden of suffering and the costs derived from confirmatory molecular assays, a better strategy is badly needed to decrease the rate of false positive results of the enzyme-linked immunoassay (ELISA) for detection of hepatitis C virus (HCV) antibodies (Anti). To establish the best cutoff of the S/CO rate in subjects with a positive result of a microparticule, third generation ELISA assay for Anti-HCV, for predicting viremia as detected by polymerase chain reaction (PCR) assay. Using the result of the PCR assay as "gold standard", a ROC curve was build with the results of the S/CO rate values in subjects with a positive result for ELISA HCV assay. Fifty two subjects (30 male, 22 female, 40 +/- 12.5 years old) were included. Thirty four (65.3%) had a positive RNA HCV PCR assay. The area under the curve was 0.99 (95% CI: 0.98-1.0). The optimal cutoff for the S/CO rate was established in 29: sensitivity: 97%; specificity: 100%: PPV: 100%; NPV: 94%. Setting the cutoff of the S/CO in 29 results in a high predictive value for viremia as detected by PCR in subjects with a positive ELISA HVC assay. This knowledge may result in a better decision taking for the clinical follow up of those subjects with a positive result in the ELISA screening assay for HCV infection.

  16. The Relationship of Level of Positive Mental Health with Current Mental Disorders in Predicting Suicidal Behavior and Academic Impairment in College Students

    Science.gov (United States)

    Keyes, Corey L. M.; Eisenberg, Daniel; Perry, Geraldine S.; Dube, Shanta R.; Kroenke, Kurt; Dhingra, Satvinder S.

    2012-01-01

    Objective: To investigate whether level of positive mental health complements mental illness in predicting students at risk for suicidal behavior and impaired academic performance. Participants: A sample of 5,689 college students participated in the 2007 Healthy Minds Study and completed an Internet survey that included the Mental Health…

  17. Theory of Planned Behavior Predicts Graduation Intentions of Canadian and Israeli Postsecondary Students with and without Learning Disabilities/Attention Deficit Hyperactivity Disorder

    Science.gov (United States)

    Fichten, Catherine S.; Heiman, Tali; Jorgensen, Mary; Nguyen, Mai Nhu; Havel, Alice; King, Laura; Budd, Jillian; Amsel, Rhonda

    2016-01-01

    We tested the ability of Ajzen's Theory of Planned Behavior (TPB) model to predict intention to graduate among Canadian and Israeli students with and without a learning disability/attention deficit hyperactivity disorder (LD/ADHD). Results based on 1486 postsecondary students show that the model's predictors (i.e., attitude, subjective norms,…

  18. Investigating University Students' Attitudes towards Physics Lesson, Their Self-Efficacy Beliefs and Burnout Levels for the Prediction of Their Academic Success in Physics Lessons

    Science.gov (United States)

    Capri, Burhan

    2013-01-01

    The purpose of this study is to find out whether university students' attitudes towards physics lesson, their self-efficacy beliefs and burnout levels predict their academic success in physics lessons. The research group consists of 641 university students of which 307 are girls (47.1%) and 334 boys (52.9%). The research data were collected using…

  19. Predictive validity of measurements of clinical competence using the team objective structured bedside assessment (TOSBA): assessing the clinical competence of final year medical students.

    LENUS (Irish Health Repository)

    Meagher, Frances M

    2009-11-01

    The importance of valid and reliable assessment of student competence and performance is gaining increased recognition. Provision of valid patient-based formative assessment is an increasing challenge for clinical teachers in a busy hospital setting. A formative assessment tool that reliably predicts performance in the summative setting would be of value to both students and teachers.

  20. The Role of Positive Psychological Capital and the Family Function in Prediction of Happiness in high school students

    Directory of Open Access Journals (Sweden)

    F rashidi kochi

    2016-11-01

    Full Text Available The aim of this study was to determine the role of positive psychological capital and family functioning in predicting happiness among adolescence. Correlational research method was recruited to analyze the data. The sample comprised of 290 high Scholl students that selected by the convenience sampling method. In this research Snyder’s hope, Nezami and Colleagues self-efficacy, Scheier and Carver's optimism, McMaster's family functioning and Connor and Davidson's Resiliency and Oxford happiness questionnaire used to collect data. Pearson correlation and stepwise regression were used to analyze data. The finding showed that there was a significant positive relationship between family function components and positive psychological capital with happiness. The results of stepwise regression showed that roles, Resiliency, self-efficacy, optimism and emotion expression had significant and important role in predicting happiness. Totally, explained 35% of the variance happiness. In conclusion, these findings indicate the importance roles of family and positive psychological capital in adolescence's happiness.

  1. Low RMRratio as a surrogate marker for energy deficiency, the choice of predictive equation vital for correctly identifying male and female ballet dancers at risk

    DEFF Research Database (Denmark)

    Staal, Sarah; Sjödin, Anders Mikael; Fahrenholtz, Ida Lysdahl

    2018-01-01

    Ballet dancers are reported to have an increased risk for energy deficiency with or without disordered eating (DE) behavior. A low ratio between measured (m) and predicted (p) resting metabolic rate (RMRratio... the prevalence of suppressed RMR using different methods to calculatepRMR and to explore associations with additional markers of energy deficiency. Female (n=20) and male (n=20) professional ballet dancers, 19-35 years of age were enrolled. mRMR was assessed by respiratory calorimetry (ventilated open hood). p......% hypotension. Forty percent of females had elevated LEAF-Q score, and 50% were underweight. Suppressed RMR was associated with elevated LEAF-Q score in females and with higher training volume in males. In conclusion, professional ballet dancers are at risk for energy deficiency. The number of identified...

  2. Low RMRratio as a Surrogate Marker for Energy Deficiency, the Choice of Predictive Equation Vital for Correctly Identifying Male and Female Ballet Dancers at Risk.

    Science.gov (United States)

    Staal, Sarah; Sjödin, Anders; Fahrenholtz, Ida; Bonnesen, Karen; Melin, Anna Katarina

    2018-06-22

    Ballet dancers are reported to have an increased risk for energy deficiency with or without disordered eating behavior. A low ratio between measured ( m ) and predicted ( p ) resting metabolic rate (RMR ratio  energy deficiency. We aimed to evaluate the prevalence of suppressed RMR using different methods to calculate p RMR and to explore associations with additional markers of energy deficiency. Female (n = 20) and male (n = 20) professional ballet dancers, 19-35 years of age, were enrolled. m RMR was assessed by respiratory calorimetry (ventilated open hood). p RMR was determined using the Cunningham and Harris-Benedict equations, and different tissue compartments derived from whole-body dual-energy X-ray absorptiometry assessment. The protocol further included assessment of body composition and bone mineral density, blood pressure, disordered eating (Eating Disorder Inventory-3), and for females, the Low Energy Availability in Females Questionnaire. The prevalence of suppressed RMR was generally high but also clearly dependent on the method used to calculate p RMR, ranging from 25% to 80% in males and 35% to 100% in females. Five percent had low bone mineral density, whereas 10% had disordered eating and 25% had hypotension. Forty percent of females had elevated Low Energy Availability in Females Questionnaire score and 50% were underweight. Suppressed RMR was associated with elevated Low Energy Availability in Females Questionnaire score in females and with higher training volume in males. In conclusion, professional ballet dancers are at risk for energy deficiency. The number of identified dancers at risk varies greatly depending on the method used to predict RMR when using RMR ratio as a marker for energy deficiency.

  3. Using psychological constructs from the MUSIC Model of Motivation to predict students' science identification and career goals: results from the U.S. and Iceland

    Science.gov (United States)

    Jones, Brett D.; Sahbaz, Sumeyra; Schram, Asta B.; Chittum, Jessica R.

    2017-05-01

    We investigated students' perceptions related to psychological constructs in their science classes and the influence of these perceptions on their science identification and science career goals. Participants included 575 middle school students from two countries (334 students in the U.S. and 241 students in Iceland). Students completed a self-report questionnaire that included items from several measures. We conducted correlational analyses, confirmatory factor analyses, and structural equation modelling to test our hypotheses. Students' class perceptions (i.e. empowerment, usefulness, success, interest, and caring) were significantly correlated with their science identification, which was correlated positively with their science career goals. Combining students' science class perceptions, science identification, and career goals into one model, we documented that the U.S. and Icelandic samples fit the data reasonably well. However, not all of the hypothesised paths were statistically significant. For example, only students' perceptions of usefulness (for the U.S. and Icelandic students) and success (for the U.S. students only) significantly predicted students' career goals in the full model. Theoretically, our findings are consistent with results from samples of university engineering students, yet different in some ways. Our results provide evidence for the theoretical relationships between students' perceptions of science classes and their career goals.

  4. The Extent to Which Teacher Attitudes and Expectations Predict Academic Achievement of Final Year Students

    Science.gov (United States)

    Jacobs, Nicky; Harvey, David

    2010-01-01

    Competition in the market is a perennial and ever-increasing problem for independent schools. How schools can meet this pressure and find ways to attract (the best) students is a continuing question and one that will get more onerous as the government funding for education is, in relative terms, decreasing. One of the ways in which schools can…

  5. Butterflies in Formation: Predicting How Speech Order in College Public Speaking Affects Student Communication Apprehension

    Science.gov (United States)

    Osmond, Erica R.

    2013-01-01

    This study addressed pedagogical practices in the public speaking classroom in an attempt to help control communication apprehension (CA) levels and improve retention rates among college students in the basic public speaking course. Guided by the theoretical frameworks of Berger and Calabrese's uncertainty reduction theory and Weiner's attribution…

  6. A Tale of Two MOOCs: How Student Motivation and Participation Predict Learning Outcomes in Different MOOCs

    Science.gov (United States)

    Brooker, Abi; Corrin, Linda; de Barba, Paula; Lodge, Jason; Kennedy, Gregor

    2018-01-01

    Recent scholarly discussions about massive open online courses (MOOCs) highlight pedagogical and practical issues that separate MOOCs from other learning settings, especially how theories of learning translate to MOOC students' motivation, participation, and performance. What is missing from these discussions is the purpose of the MOOC. We report…

  7. Examining Readability Estimates' Predictions of Students' Oral Reading Rate: Spache, Lexile, and Forcast

    Science.gov (United States)

    Ardoin, Scott P.; Williams, Jessica C.; Christ, Theodore J.; Klubnik, Cynthia; Wellborn, Claire

    2010-01-01

    Beyond reliability and validity, measures used to model student growth must consist of multiple probes that are equivalent in level of difficulty to establish consistent measurement conditions across time. Although existing evidence supports the reliability of curriculum-based measurement in reading (CBMR), few studies have empirically evaluated…

  8. Early Prediction of Students' Grade Point Averages at Graduation: A Data Mining Approach

    Science.gov (United States)

    Tekin, Ahmet

    2014-01-01

    Problem Statement: There has recently been interest in educational databases containing a variety of valuable but sometimes hidden data that can be used to help less successful students to improve their academic performance. The extraction of hidden information from these databases often implements aspects of the educational data mining (EDM)…

  9. Attachment Predicts College Students' Knowledge, Attitudes, and Skills for Working with Infants, Toddlers, and Families

    Science.gov (United States)

    Vallotton, Claire D.; Torquati, Julia; Ispa, Jean; Chazan-Cohen, Rachel; Henk, Jennifer; Fusaro, Maria; Peterson, Carla A.; Roggman, Lori A.; Stacks, Ann M.; Cook, Gina; Brophy-Herb, Holly

    2016-01-01

    Research Findings: Adults' attitudes about attachment relationships are central to how they perceive and respond to children. However, little is known about how attachment styles are related to teachers' attitudes toward and interactions with infants and toddlers. From a survey of 207 students taking early childhood (EC) courses at 4 U.S.…

  10. Passion and Motivation for Studying: Predicting Academic Engagement and Burnout in University Students

    Science.gov (United States)

    Stoeber, Joachim; Childs, Julian H.; Hayward, Jennifer A.; Feast, Alexandra R.

    2011-01-01

    Research on the dualistic model of passion has investigated harmonious and obsessive passion in many domains. However, few studies have investigated passion for studying and the role passion for studying plays in student engagement and well-being. The present study investigated the relationships between harmonious and obsessive passion for…

  11. Predicting Students' Academic Performance Based on School and Socio-Demographic Characteristics

    Science.gov (United States)

    Thiele, Tamara; Singleton, Alexander; Pope, Daniel; Stanistreet, Debbi

    2016-01-01

    Students' trajectories into university are often uniquely dependent on school qualifications though these alone are limited as predictors of academic potential. This study endorses this, examining associations between school grades, school type, school performance, socio-economic deprivation, neighbourhood participation, sex and academic…

  12. A Review of Predictive Factors of Student Success in and Satisfaction with Online Learning

    Science.gov (United States)

    Kauffman, Heather

    2015-01-01

    Students perceive online courses differently than traditional courses. Negative perceptions can lead to unfavourable learning outcomes including decreased motivation and persistence. Throughout this review, a broad range of factors that affect performance and satisfaction within the online learning environment for adult learners will be examined…

  13. What Learning Analytics‐Based Prediction Models Tell Us About Feedback Preferences of Students

    NARCIS (Netherlands)

    Nguyen, Quan; Tempelaar, Dirk; Rienties, Bart; Giesbers, Bas

    2016-01-01

    Learning analytics seeks to enhance learning processes through systematic measurements of learning-related data and to provide informative feedback to learners and educators (Siemens & Long, 2011). This study examined the use of preferred feedback modes in students by using a dispositional

  14. Predicting Entrepreneurial Motivation among University Students: The Role of Entrepreneurship Education

    Science.gov (United States)

    Farhangmehr, Minoo; Gonçalves, Paulo; Sarmento, Maria

    2016-01-01

    Purpose: The purpose of this paper is to better understand the main drivers of entrepreneurial motivation among university students and to determine whether entrepreneurship education has a moderating effect on improving the impact of knowledge base and entrepreneurship competencies on entrepreneurial motivation. Design/methodology/approach: This…

  15. Can Learning Style Predict Student Satisfaction with Different Instruction Methods and Academic Achievement in Medical Education?

    Science.gov (United States)

    Gurpinar, Erol; Alimoglu, Mustafa Kemal; Mamakli, Sumer; Aktekin, Mehmet

    2010-01-01

    The curriculum of our medical school has a hybrid structure including both traditional training (lectures) and problem-based learning (PBL) applications. The purpose of this study was to determine the learning styles of our medical students and investigate the relation of learning styles with each of satisfaction with different instruction methods…

  16. Predicting Role Conflict, Overload and Contagion in Adult Women University Students with Families and Jobs.

    Science.gov (United States)

    Home, Alice M.

    1998-01-01

    Data from 443 women combining work, family, and schooling showed that lower income increased their vulnerability to role conflict. Perceived intensity of student demands was the strongest predictor of role conflict, overload, and contagion (preoccupation with one role while performing another). Conflict and overload were eased somewhat by distance…

  17. Predicting Dropout Using Student- and School-Level Factors: An Ecological Perspective

    Science.gov (United States)

    Wood, Laura; Kiperman, Sarah; Esch, Rachel C.; Leroux, Audrey J.; Truscott, Stephen D.

    2017-01-01

    High school dropout has been associated with negative outcomes, including increased rates of unemployment, incarceration, and mortality. Dropout rates vary significantly depending on individual and environmental factors. The purpose of our study was to use an ecological perspective to concurrently explore student- and school-level predictors…

  18. Admitting At-Risk Students into a Principal Preparation Program: Predicting Success.

    Science.gov (United States)

    Malone, Bobby G.; Nelson, Jacquelyn S.; Nelson, C. Van

    2001-01-01

    Study of graduation rates of at-risk students admitted to a master's degree program at a doctoral-degree-granting university found that the best predictor of degree completion was the product of the undergraduate GPA multiplied by the GRE Verbal score. (Contains 41 references.)

  19. Role of Family Background, Student Behaviors, and School-Related Beliefs in Predicting High School Dropout

    Science.gov (United States)

    Parr, Alyssa K.; Bonitz, Verena S.

    2015-01-01

    The authors' purpose was to test a parsimonious model derived from social cognitive career theory (R. W. Lent, S. D. Brown, & G. Hackett, 1994) and expectancy value theory (J. S. Eccles & A. Wigfield, 2002) that integrates groups of variables (demographic background, student behaviors, and school-related beliefs) with the goal of…

  20. Applying Learning Analytics for the Early Prediction of Students' Academic Performance in Blended Learning

    Science.gov (United States)

    Lu, Owen H. T.; Huang, Anna Y. Q.; Huang, Jeff C. H.; Lin, Albert J. Q.; Ogata, Hiroaki; Yang, Stephen J. H.

    2018-01-01

    Blended learning combines online digital resources with traditional classroom activities and enables students to attain higher learning performance through well-defined interactive strategies involving online and traditional learning activities. Learning analytics is a conceptual framework and is a part of our Precision education used to analyze…

  1. Do the Critical Success Factors from Learning Analytics Predict Student Outcomes?

    Science.gov (United States)

    Strang, Kenneth David

    2016-01-01

    This article starts with a detailed literature review of recent studies that focused on using learning analytics software or learning management system data to determine the nature of any relationships between online student activity and their academic outcomes within university-level business courses. The article then describes how data was…

  2. Introduction to Psychology Students' Parental Status Predicts Learning Preferences and Life Meaning

    Science.gov (United States)

    Lovell, Elyse D'nn; Munn, Nathan

    2017-01-01

    This study explores Introduction to Psychology students' learning preferences and their personal search for meaning while considering their parental status. The findings suggest that parents show preferences for project-based learning and have lower levels of searching for meaning than non-parents. When parental status, age, and finances were…

  3. Can Medical Students Accurately Predict Their Learning? A Study Comparing Perceived and Actual Performance in Neuroanatomy

    Science.gov (United States)

    Hall, Samuel R.; Stephens, Jonny R.; Seaby, Eleanor G.; Andrade, Matheus Gesteira; Lowry, Andrew F.; Parton, Will J. C.; Smith, Claire F.; Border, Scott

    2016-01-01

    It is important that clinicians are able to adequately assess their level of knowledge and competence in order to be safe practitioners of medicine. The medical literature contains numerous examples of poor self-assessment accuracy amongst medical students over a range of subjects however this ability in neuroanatomy has yet to be observed. Second…

  4. Role of the Big Five Personality Traits in Predicting College Students' Academic Motivation and Achievement

    Science.gov (United States)

    Komarraju, Meera; Karau, Steven J.; Schmeck, Ronald R.

    2009-01-01

    College students (308 undergraduates) completed the Five Factor Inventory and the Academic Motivations Scale, and reported their college grade point average (GPA). A correlation analysis revealed an interesting pattern of significant relationships. Further, regression analyses indicated that conscientiousness and openness explained 17% of the…

  5. Exploring Predictability of Instructor Ratings Using a Quantitative Tool for Evaluating Soft Skills among MBA Students

    Science.gov (United States)

    Brill, Robert T.; Gilfoil, David M.; Doll, Kristen

    2014-01-01

    Academic researchers have often touted the growing importance of "soft skills" for modern day business leaders, especially leadership and communication skills. Despite this growing interest and attention, relatively little work has been done to develop and validate tools to assess soft skills. Forty graduate students from nine MBA…

  6. Predicting High School Completion Using Student Performance in High School Algebra: A Mixed Methods Research Study

    Science.gov (United States)

    Chiado, Wendy S.

    2012-01-01

    Too many of our nation's youth have failed to complete high school. Determining why so many of our nation's students fail to graduate is a complex, multi-faceted problem and beyond the scope of any one study. The study presented herein utilized a thirteen-step mixed methods model developed by Leech and Onwuegbuzie (2007) to demonstrate within a…

  7. Recall of vegetable eating affects future predicted enjoyment and choice of vegetables in British University undergraduate students.

    Science.gov (United States)

    Robinson, Eric; Blissett, Jackie; Higgs, Suzanne

    2011-10-01

    Predictions about enjoyment of future experiences are influenced by recalling similar past experiences. However, little is known about the relationship between hedonic memories of past eating episodes and future eating behavior. We investigated recall of previous experiences of eating vegetables and the effect of recall on future predicted liking for and consumption of vegetables. British University undergraduate students were asked to retrieve memories of previous occasions when they ate vegetables and were asked to rate how enjoyable those experiences were (Study 1, n=54). The effect of different types of memory recall (including vegetable eating recall) and visualization of someone else eating vegetables (to control for priming effects) on predicted likelihood of choosing vegetables and predicted enjoyment of eating vegetables was examined (Study 2, n=95). Finally, the effect of recalling vegetable eating memories on actual food choice from a buffet was assessed (Study 3, n=63). It is reported that people recall positive memories of past vegetable consumption (Precall of a personal nonfood memory, a nonvegetable food memory, or visualization of someone else enjoying eating vegetables (increase of approximately 70% in vegetable portion size compared to controls). The results suggest that recall of previous eating experiences could be a potential strategy for altering food choices. Copyright © 2011 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

  8. Application of the Transtheoretical Model to Predict Exercise Activities in the Students of Islamic Azad University of Sabzevar

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    M. Mohammadi

    2012-04-01

    Full Text Available Background: Based on report of World Health Organization (WHO, about 60-85% of the world's population fails to complete the recommended amount of physical activity required to induce health benefits. It is necessary to assess health status for designing and programming about exercise activities. In this study the effectiveness of Transtheoretical Model (TTM in predicting exercise activities among the students of Islmaic Azad University of Sabzevar was examined. Methods: In this cross sectional-Correlational study. A random (clustered sample of 234 university students in Islamic Azad university of Sabzevar, participated in the study. A standard instrument was used to measure the variables of interest based on transtheoretical model. Reliability and validity of the questionnaire was examined by a panel of experts and cronbach alpha (N=30, α=0.83-0.95. The data were analyzed by SPSS 16.00 statistical software using Path analysis based regression, t-test and ANOVA and Correlation. Results: According to the results, the average age of students was 22.5±3.8 years. The distribution of the participants according to the stages of change model was as follows: pre-contemplation 36.3%, contemplation 25.6%, preparation, 18.9%, action, 10.5% and maintenance 8.7%.These were significant differences between mean of self efficacy, process of change, decisional balance by sex (p<0.05 and stages of change (p<0.01. Behavioral process of change (β=0.399 and self efficacy (β=0.350 were the most important variables for improving levels of exercise. Conclusion: Because the most students (62% were at precontemplation, contemplation and preparation stages and the results showed that behavioral process of change perceived barriers and self efficacy are the most important predictors for improving levels of exercise. Thus, policies and programs to strengthen these factors to promote exercise activities among students is recommended.

  9. Evaluating the Effects of Formal Corrective Feedback on Off-Task/On-Task Behavior of Mild Intellectually Disabled Students: An Action Research Study

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    George, Kevin

    2016-01-01

    The off-task behavior demonstrated by the study participants appears to interfere with classroom instruction, contribute to poor academic performance and in many instances lead to disciplinary actions such as suspension. The purpose of the study entailed determining if formal corrective feedback has an effect on the off-task/on-task behavior of…

  10. Person-environment fit: using commensurate scales to predict student stress.

    Science.gov (United States)

    Puccio, G J; Talbot, R J; Joniak, A J

    1993-11-01

    The relationship between person-environment fit and stress was examined for two samples of university students (N = 55 and 79). The Kirton Adaption-Innovation Inventory (KAI) was modified to assess the students' perceptions of the adaptor-innovator style required by their course, the styles they exhibited in the course, and their ideal style preferences. To ascertain fit, the KAI total scores and subscale scores (Originality, Efficiency, and Rule/Group Conformity) were used to classify students on three dimensions: (1) perception of what style their course required, adaptive or innovative; (2) congruence between the style the course required and the style they exhibited in the course; and (3) the magnitude of the difference, if any, between the required style and the exhibited style. Points two and three are measures of fit. The dependent variable was stress. Also the students' ideal style scores, KAI total and subscales, were substituted for the exhibited scores and the classification and analyses were repeated. Analysis of the total scores revealed that a course requiring adaptive behaviours was perceived as more stressful than a course requiring innovative behaviours. Similarly, an analysis of the Rule/Group Conformity scores revealed that the greater the conformity required the greater the stress. Also the less originality demanded in the course the greater was the perceived stress. For the KAI total scores and Rule/Group Conformity scores, the two measures of fit (incongruity and magnitude of the incongruity) were not related to stress. However, analyses of the Originality and Efficiency subscales supported the importance of the P-E fit position. For both subscales, stress was associated with the magnitude of the difference between what was required in the course and what students exhibited in the course. Educational implications derived from these findings as well as recommendations for future research are discussed.

  11. Choice is good, but relevance is excellent: autonomy-enhancing and suppressing teacher behaviours predicting students' engagement in schoolwork.

    Science.gov (United States)

    Assor, Avi; Kaplan, Haya; Roth, Guy

    2002-06-01

    This article examines two questions concerning teacher-behaviours that are characterised in Self-Determination Theory (Ryan & Deci, 2000) as autonomy-supportive or suppressive: (1) Can children differentiate among various types of autonomy-enhancing and suppressing teacher behaviours? (2) Which of those types of behaviour are particularly important in predicting feelings toward and engagement in schoolwork? It was hypothesised that teacher behaviours that help students to understand the relevance of schoolwork for their personal interests and goals are particularly important predictors of engagement in schoolwork. Israeli students in grades 3-5 (N = 498) and in grades 6-8 (N = 364) completed questionnaires assessing the variables of interest. Smallest Space Analyses indicated that both children and early adolescents can differentiate among three types of autonomy enhancing teacher behaviours - fostering relevance, allowing criticism, and providing choice - and three types of autonomy suppressing teacher behaviours - suppressing criticism, intruding, and forcing unmeaningful acts. Regression analyses supported the hypothesis concerning the importance of teacher behaviours that clarify the personal relevance of schoolwork. Among the autonomy-suppressing behaviours, 'Criticism-suppression' was the best predictor of feelings and engagement. The findings underscore the active and empathic nature of teachers' role in supporting students' autonomy, and suggest that autonomy-support is important not only for early adolescents but also for children. Discussion of potential determinants of the relative importance of various autonomy-affecting teacher actions suggests that provision of choice should not always be viewed as a major indicator of autonomy support.

  12. More Than Only Skin Deep: Appearance Self-Concept Predicts Most of Secondary School Students' Self-Esteem.

    Science.gov (United States)

    Baudson, Tanja G; Weber, Kira E; Freund, Philipp A

    2016-01-01

    One important goal of education is to develop students' self-esteem which, in turn, hinges on their self-concept in the academic, physical, and social domains. Prior studies have shown that physical self-concept accounts for most of the variation in self-esteem, with academic and social self-concepts playing a much lesser role. As pressure toward perfection seems to be increasing in education, appearance, and social relationships (three aspects that relate to crucial developmental tasks of adolescence), the goal of the present field study was to examine whether former findings still hold true in the light of the changing societal context. A sample of 2,950 students from a broad range of German secondary schools (47% girls, age 10-19 years) responded to a recently validated German-language questionnaire assessing multiple self-concept facets (Weber and Freund, 2016). We examined which self-concept aspects predict self-esteem best and whether the pattern is comparable across genders and achievement levels using latent regression analyses. Results show that self-concept of appearance is still by far the strongest predictor (total sample: B = 0.77, SE = 0.02, p educational schools. Other aspects play a much lesser role. The discussion explores why appearance is so neglected, compared to the more academic subjects, and what school can do to account for its vast importance for students' self-esteem.

  13. Predicting the academic success of architecture students by pre-enrolment requirement: using machine-learning techniques

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    Ralph Olusola Aluko

    2016-12-01

    Full Text Available In recent years, there has been an increase in the number of applicants seeking admission into architecture programmes. As expected, prior academic performance (also referred to as pre-enrolment requirement is a major factor considered during the process of selecting applicants. In the present study, machine learning models were used to predict academic success of architecture students based on information provided in prior academic performance. Two modeling techniques, namely K-nearest neighbour (k-NN and linear discriminant analysis were applied in the study. It was found that K-nearest neighbour (k-NN outperforms the linear discriminant analysis model in terms of accuracy. In addition, grades obtained in mathematics (at ordinary level examinations had a significant impact on the academic success of undergraduate architecture students. This paper makes a modest contribution to the ongoing discussion on the relationship between prior academic performance and academic success of undergraduate students by evaluating this proposition. One of the issues that emerges from these findings is that prior academic performance can be used as a predictor of academic success in undergraduate architecture programmes. Overall, the developed k-NN model can serve as a valuable tool during the process of selecting new intakes into undergraduate architecture programmes in Nigeria.

  14. Predicting Oral Health Behavior using the Health Promotion Model among School Students: a Cross-sectional Survey

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    Abdurrahman Charkazi

    2016-07-01

    Full Text Available teeth and T=permanent teeth has been increasing from 1957 to 2015 years in Iran. The current survey aimed to test the power of health promotion model for predicting the oral health behavior among high-school students.  Materials and Methods: A cross-sectional study was conducted on 482 high school students in Gorgan city, Iran. Multi-cluster sampling was used to recruit the samples. A researcher-made questionnaire based on HPM was implemented to collect data. To analyze, SPSS-18 and statistical tests, including t-test, Pearson correlation coefficient and univariate and multivariate regression models were used. Results: A total of 482 high-school students including 255 (52.9% male and 227 (47.1% with mean age of 16.02 ± 0.5 were investigated. The highest and lowest prevalent positive oral health behavior were tooth brushing (73% and using fluidized oral irrigator (3.6%, respectively. Except for perceived barriers (with negative correlation, all constructs of HBM were positively related to oral health behaviors. Self-efficacy was the strongest predictor of oral health behavior (β=0.653 (r=0.541, P

  15. Investigation of aggravating psychosocial factors on health and predictability of smoking and alcohol use in post adolescent students

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    Effrosyni Barmpagianni

    2013-04-01

    Full Text Available Purpose of this study is to explore those factors which affect the health of students in postadolescent age, focusing on smoking and alcohol use, especially in regard to ways of predicting adoption of this behavior and its frequency to detect future users of tobacco and alcohol use but also high-risk groups, i.e. those people who are led to abuses. On the basis of the research part is the Theory of Planned Behaviour, the axes of which are to be investigated. Specifically, the factors evaluated, except for population parameters, behavioral attitudes, i.e. attitudes towards the behavior of tobacco use and alcohol regulations subjective perceptions and perceptions of control, perceived behavioral control and self-efficacy. Intention is explored to continue or start using tobacco and alcohol in the future and evaluate the behavior. The sample consisted of 138 students of postadolescent age, 18-25 years of both sexes, all of the University of Peloponnese and the Technological Educational Institute of Kalamata, Department of Sparta, Greece. The results of a series of statistical analysis, via SPSS 21.0 statistical program revealed the predictive power of perceived behavioral control and subjective norms to the intention of interpreting 64% of the variance of the latter, of the attitudes toward alcohol in relation to intention that interpret 69% of the variance, of the normative beliefs toward smoking with 69% range of interpretation to the dependent variable, of the perceived behavioral control of smoking with 72% and of the attitudes toward smoking with 77% of interpretation. The results demonstrate the significance and application in universities and technological educational institutes appropriate primary preventive interventions for students nonusers of tobacco and alcohol and appropriate programs of secondary and tertiary prevention in heavy users of tobacco and alcohol use and high-risk individual.

  16. Metacognition and Self-Regulated Learning in Predicting University Students' Academic Achievement in Turkey

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    Çetin, Baris

    2017-01-01

    The purpose of this study was to determine whether perceived levels of self-regulated learning and metacognition predicted the ultimate grade point average (GPA) attained by 206 female and 70 male college seniors (aged 21 to 27) finishing their elementary education teaching certification studies at a university in Turkey. Data regarding individual…

  17. Corrections to the free-nucleon values of the single-particle matrix elements of the M1 and Gamow-Teller operators, from a comparison of shell-model predictions with sd-shell data

    International Nuclear Information System (INIS)

    Brown, B.A.; Wildenthal, B.H.

    1983-01-01

    The magnetic dipole moments of states in mirror pairs of the sd-shell nuclei and the strengths of the Gamow-Teller beta decays which connect them are compared with predictions based on mixed-configuration shell-model wave functions. From this analysis we extract the average effective values of the single-particle matrix elements of the l, s, and [Y/sup( 2 )xs]/sup( 1 ) components of the M1 and Gamow-Teller operators acting on nucleons in the 0d/sub 5/2/, 1s/sub 1/2/, and 0d/sub 3/2/ orbits. These results are compared with the recent calculations by Towner and Khanna of the corrections to the free-nucleon values of these matrix elements which arise from the effects of isobar currents, mesonic-exchange currents, and mixing with configurations outside the sd shell

  18. Can adaptive threshold-based metabolic tumor volume (MTV) and lean body mass corrected standard uptake value (SUL) predict prognosis in head and neck cancer patients treated with definitive radiotherapy/chemoradiotherapy?

    Science.gov (United States)

    Akagunduz, Ozlem Ozkaya; Savas, Recep; Yalman, Deniz; Kocacelebi, Kenan; Esassolak, Mustafa

    2015-11-01

    To evaluate the predictive value of adaptive threshold-based metabolic tumor volume (MTV), maximum standardized uptake value (SUVmax) and maximum lean body mass corrected SUV (SULmax) measured on pretreatment positron emission tomography and computed tomography (PET/CT) imaging in head and neck cancer patients treated with definitive radiotherapy/chemoradiotherapy. Pretreatment PET/CT of the 62 patients with locally advanced head and neck cancer who were treated consecutively between May 2010 and February 2013 were reviewed retrospectively. The maximum FDG uptake of the primary tumor was defined according to SUVmax and SULmax. Multiple threshold levels between 60% and 10% of the SUVmax and SULmax were tested with intervals of 5% to 10% in order to define the most suitable threshold value for the metabolic activity of each patient's tumor (adaptive threshold). MTV was calculated according to this value. We evaluated the relationship of mean values of MTV, SUVmax and SULmax with treatment response, local recurrence, distant metastasis and disease-related death. Receiver-operating characteristic (ROC) curve analysis was done to obtain optimal predictive cut-off values for MTV and SULmax which were found to have a predictive value. Local recurrence-free (LRFS), disease-free (DFS) and overall survival (OS) were examined according to these cut-offs. Forty six patients had complete response, 15 had partial response, and 1 had stable disease 6 weeks after the completion of treatment. Median follow-up of the entire cohort was 18 months. Of 46 complete responders 10 had local recurrence, and of 16 partial or no responders 10 had local progression. Eighteen patients died. Adaptive threshold-based MTV had significant predictive value for treatment response (p=0.011), local recurrence/progression (p=0.050), and disease-related death (p=0.024). SULmax had a predictive value for local recurrence/progression (p=0.030). ROC curves analysis revealed a cut-off value of 14.00 mL for

  19. Predicting the educational performance of Isfahan University students of medical sciences based on their behaviour profile, mental health and demographic characteristic.

    Science.gov (United States)

    Samouei, Rahele; Fooladvand, Maryam; Janghorban, Shahla; Khorvash, Fariba

    2015-01-01

    The issue of students' academic failure is one of the most important educational, economic, and social issues. Cognizance of the factors related to academic downfall is so efficient in its prevention and control and leads to protecting governmental assets and labor force. In order to achieve this goal, this study intends to determine the predictive factors of the students' academic performance in Isfahan University of Medical Sciences in terms of their personality profile, mental health, and their demographic characteristics. This study was a descriptive-correlation study on 771 students who entered Isfahan University of Medical Sciences between 2005 and 2007. The information was gathered through using the students' educational and clinical files (for measuring personality characteristics and mental health) and SAMA Software (To get the mean scores). Minnesota Multiphasic Personality Inventory short form and General Health Questionnaire were used for collecting clinical data. The data were analyzed using SPSS 15 (stepwise regression coefficient, variance analysis, Student's t-test, and Spearman correlation coefficient). The results showed that the aforementioned students obtained a normal average for their personality profile and mental health indicators. Of all the reviewed variables, education, age, gender, depression, and hypochondria were the predictive factors of the students' educational performance. It could be concluded that some of the personality features, mental health indicators, and personality profile play such a significant role in the students' educational life that the disorder in any of them affects the students' educational performance and academic failure.

  20. The Prediction of Students' Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning.

    Science.gov (United States)

    Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Xu, Fen

    2015-01-01

    The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school.