Full Text Available There are many reasons for students of Sport Science to use English. Yet, knowing the importance of learning English is sometimes not enough to encourage them to learn English well. Based on the experience in teaching them, erroneous belief seems to be held by many of them. It arouses curiosity about the beliefs which might be revealed to help the students to be successful in language learning. By investigating sport science students‘ beliefs about language learning, it is expected that types of the beliefs which they hold can be revealed. Understanding students‘ beliefs about language learning is essential because these beliefs can have possible consequences for second language learning and instruction. This study is expected to provide empirical evidence. The subjects of this study were 1st semester students majoring in Sport Science of Sport Science Faculty. There were 4 classes with 38 students in each class. There were approximately 152 students as the population of the study. The sample was taken by using random sampling. All members of the population received the questionnaire. The questionnaire which was later handed back to the researcher is considered as the sample. The instrument in this study is the newest version of Beliefs About Language Learning Inventory (BALLI, version 2.0, developed by Horwitz to asses the beliefs about learning a foreign language.
Inayati, Dian; Emaliana, Ive
This paper elucidates the relationship among pre-service teachers' beliefs about language learning, pedagogical beliefs, and beliefs about ICT Integration through survey methodology. This study employed a quantitative approach, particularly a correlational relationship to investigate the relationships among beliefs about language learning,…
Boer, Hendrik; Emons, P.A.A.; Emons, P.A.A.
We assessed the relation between accurate beliefs about HIV transmission and inaccurate beliefs about HIV transmission and emotional reactions to people with AIDS (PWA) and AIDS risk groups, stigmatizing attitudes and motivation to protect from HIV. In Chiang Rai, northern Thailand, 219 respondents
Ke, Jie; Kang, Rui; Liu, Di
This study was designed to initiate the process of building professional development learning communities for pre-service math teachers through revealing those teachers' conceptions/beliefs of students' learning and their own learning in China. It examines Chinese pre-service math teachers' conceptions of student learning and their related…
Altan, Mustafa Zulkuf
Beliefs are central constructs in every discipline which deals with human behaviour and learning. In addition to learner beliefs about language learning, language teachers themselves may hold certain beliefs about language learning that will have an impact on their instructional practices and that are likely to influence their students' beliefs…
This paper examines the nature, prevalence and effect of superstitious beliefs as constraints to the appropriate learning of science in our schools. Studies done on identification and analysis of types and degrees of superstitious beliefs have been reported as well as to how these beliefs inhibit the individual learner\\'s ...
De Hei, Miranda Suzanna Angelique; Strijbos, Jan-Willem; Sjoer, Ellen; Admiraal, Wilfried
Collaborative learning can, if designed and implemented properly, contribute to student learning outcomes and prepare them for teamwork. However, the design and implementation of collaborative learning in practice depend on beliefs of lecturers about teaching and learning in general, and collaborative learning in particular. One hundred and…
Zeng, Jia; Cheung, William K; Liu, Jiming
Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interest and touches on many important applications in text mining, computer vision and computational biology. This paper represents the collapsed LDA as a factor graph, which enables the classic loopy belief propagation (BP) algorithm for approximate inference and parameter estimation. Although two commonly used approximate inference methods, such as variational Bayes (VB) and collapsed Gibbs sampling (GS), have gained great success in learning LDA, the proposed BP is competitive in both speed and accuracy, as validated by encouraging experimental results on four large-scale document datasets. Furthermore, the BP algorithm has the potential to become a generic scheme for learning variants of LDA-based topic models in the collapsed space. To this end, we show how to learn two typical variants of LDA-based topic models, such as author-topic models (ATM) and relational topic models (RTM), using BP based on the factor graph representations.
Ichinose, Cherie; Bonsangue, Martin
This study examined students' mathematical self-related beliefs in an online mathematics course. Mathematical self-related beliefs of a sample of high school students learning mathematics online were compared with student response data from the 2012 Programme for International Student Assessment (PISA). The treatment group reported higher levels…
Landers, Andrew James
Past research indicates that teachers' beliefs are influential in their decisions and behaviors in the classroom. Teachers are also influenced by the socioeconomic status of their students. The present study on beliefs and evaluation of knowledge about working with students with learning disabilities included kindergarten through 12th grade…
Ismail, Habsah; Hassan, Aminuddin; Muhamad, Mohd. Mokhtar; Ali, Wan Zah Wan; Konting, Mohd. Majid
This is an investigation of the students' beliefs about the nature of knowledge or epistemological beliefs, and the relation of these beliefs on their learning approaches. Students chosen as samples of the study were from both public and private higher institutions of learning in Malaysia. The instrument used in the study consists of 49 items…
The paper will present the relation between students’ beliefs and their behaviours observed in the process of learning critical thinking skills. In the first place some consideration concerning the fundamental epistemological concepts used in the research and about the particular critical thinking skills are to be sketched. Then the testing- learning procedure will be shortly summarized. Thirdly the evaluation of beliefs, their relations with knowledge and the associated behaviors are present...
Full Text Available The basal ganglia are known to play a crucial role in movement execution, but their importance for motor skill learning remains unclear. Obstacles to our understanding include the lack of a universally accepted definition of motor skill learning (definition confound, and difficulties in distinguishing learning deficits from execution impairments (performance confound. We studied how healthy subjects and subjects with a basal ganglia disorder learn fast accurate reaching movements, and we addressed the definition and performance confounds by: 1 focusing on an operationally defined core element of motor skill learning (speed-accuracy learning, and 2 using normal variation in initial performance to separate movement execution impairment from motor learning abnormalities. We measured motor skill learning learning as performance improvement in a reaching task with a speed-accuracy trade-off. We compared the performance of subjects with Huntington’s disease (HD, a neurodegenerative basal ganglia disorder, to that of premanifest carriers of the HD mutation and of control subjects. The initial movements of HD subjects were less skilled (slower and/or less accurate than those of control subjects. To factor out these differences in initial execution, we modeled the relationship between learning and baseline performance in control subjects. Subjects with HD exhibited a clear learning impairment that was not explained by differences in initial performance. These results support a role for the basal ganglia in both movement execution and motor skill learning.
Kalish, Charles W.; Rogers, Timothy T.; Lang, Jonathan; Zhu, Xiaojin
Three experiments with 88 college-aged participants explored how unlabeled experiences--learning episodes in which people encounter objects without information about their category membership--influence beliefs about category structure. Participants performed a simple one-dimensional categorization task in a brief supervised learning phase, then…
Boon, Anne; Raes, Elisabeth; Kyndt, Eva; Dochy, Filip
Purpose: Teams, teamwork and team learning have been the subject of many research studies over the last decades. This article aims at investigating and confirming the Team Learning Beliefs and Behaviours (TLB&B) model within a very specific population, i.e. police and firemen teams. Within this context, the paper asks whether the team's…
Full Text Available A key challenge in many reinforcement learning problems is delayed rewards, which can significantly slow down learning. Although reward shaping has previously been introduced to accelerate learning by bootstrapping an agent with additional...
Full Text Available The paper will present the relation between students’ beliefs and their behaviours observed in the process of learning critical thinking skills. In the first place some consideration concerning the fundamental epistemological concepts used in the research and about the particular critical thinking skills are to be sketched. Then the testing- learning procedure will be shortly summarized. Thirdly the evaluation of beliefs, their relations with knowledge and the associated behaviors are presented. The results of the periodic testing procedures that were taking place according to the established methodology are to be discussed. Finally, some general considerations concerning the relations between beliefs, behaviors and knowledge that have emerged in the process of learning are going to be presented.
Dandy, Kristina L.; Bendersky, Karen
Beliefs about learning can influence whether or not a student learns course material. However, few studies in higher education have compared student and faculty beliefs about learning. In the current study, students and faculty agreed on many aspects of learning--including the definition of learning, which most hinders learning and where learning…
Basaran, Süleyman; Cabaroglu, Nese
The ubiquitous use of Internet-based mobile devices in educational contexts means that mobile learning has become a plausible alternative to or a good complement for conventional classroom-based teaching. However, there is a lack of research that explores and defines the characteristics and effects of mobile language learning (LL) through language…
Full Text Available What beliefs do Chinese learners hold about language learning? What is the effect of these beliefs on their autonomous learning? These are the two questions that this study aims to address. I employed naturalistic inquiry (Lincoln & Guba, 1985 to investigate five Chinese ESL learners’ beliefs about language learning and their learning behaviour. A number of instruments (interviews, classroom observations and stimulated recall, learning logs were used to collect triangulated data over a 12-week period. Following standard procedures of qualitative data analysis, I identified five categories of learners’ beliefs. The results revealed that the beliefs that the learners held were context-specific, reflecting their learning experiences. Some of them were conducive to learning autonomy while others were not. The beliefs influenced the level of the learners’ autonomy. The study suggests that educators should take into account learners’ beliefs when promoting autonomous learning.
Lunn Brownlee, Jo; Johansson, Eva; Cobb-Moore, Charlotte; Boulton-Lewis, Gillian; Walker, Sue; Ailwood, Joanne
While investment in young children is recognised as important for the development of moral values for a cohesive society, little is known about early years teaching practices that promote learning of moral values. This paper reports on observations and interviews with 11 Australian teachers, focusing on their epistemic beliefs and beliefs about…
Full Text Available Geomagnetic-based indoor positioning has drawn a great attention from academia and industry due to its advantage of being operable without infrastructure support and its reliable signal characteristics. However, it must overcome the problems of ambiguity that originate with the nature of geomagnetic data. Most studies manage this problem by incorporating particle filters along with inertial sensors. However, they cannot yield reliable positioning results because the inertial sensors in smartphones cannot precisely predict the movement of users. There have been attempts to recognize the magnetic sequence pattern, but these attempts are proven only in a one-dimensional space, because magnetic intensity fluctuates severely with even a slight change of locations. This paper proposes accurate magnetic indoor localization using deep learning (AMID, an indoor positioning system that recognizes magnetic sequence patterns using a deep neural network. Features are extracted from magnetic sequences, and then the deep neural network is used for classifying the sequences by patterns that are generated by nearby magnetic landmarks. Locations are estimated by detecting the landmarks. AMID manifested the proposed features and deep learning as an outstanding classifier, revealing the potential of accurate magnetic positioning with smartphone sensors alone. The landmark detection accuracy was over 80% in a two-dimensional environment.
Xie, Kui; Huang, Kun
Epistemic and learning beliefs were found to affect college students' cognitive engagement and study strategies, as well as motivation in classroom settings. However, the relationships between epistemic and learning beliefs, motivation, learning perception, and students' actual learning participation in asynchronous online settings have been…
Wang, Xiaofeng; Liu, Yiguang
The belief propagation (BP) algorithm has some limitations, including ambiguous edges and textureless regions, and slow convergence speed. To address these problems, we present a novel algorithm that intrinsically improves both the accuracy and the convergence speed of BP. First, traditional BP generally consumes time due to numerous iterations. To reduce the number of iterations, inspired by the crucial importance of the initial value in nonlinear problems, a novel initial-value belief propagation (IVBP) algorithm is presented, which can greatly improve both convergence speed and accuracy. Second, .the majority of the existing research on BP concentrates on the smoothness term or other energy terms, neglecting the significance of the data term. In this study, a self-adapting dissimilarity data term (SDDT) is presented to improve the accuracy of the data term, which incorporates an additional gradient-based measure into the traditional data term, with the weight determined by the robust measure-based control function. Finally, this study explores the effective combination of local methods and global methods. The experimental results have demonstrated that our method performs well compared with the state-of-the-art BP and simultaneously holds better edge-preserving smoothing effects with fast convergence speed in the Middlebury and new 2014 Middlebury datasets.
The purpose of the research was to investigate the effects of think pair share (TPS) instructional strategy on students' conceptual learning and epistemological beliefs on physics and physics learning. The research was conducted with two groups. One of the groups was the experimental group (EG) and the other group was the control group (CG). 35…
Dral, Pavlo O.; Lilienfeld, O. Anatole von; Thiel, Walter
We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempirical OM2 method using a set of 6095 constitutional isomers C 7 H 10 O 2 , for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules
Chmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel E.; Poltavsky, Igor; Schütt, Kristof T.; Müller, Klaus-Robert
Using conservation of energy—a fundamental property of closed classical and quantum mechanical systems—we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories. The GDML implementation is able to reproduce global potential energy surfaces of intermediate-sized molecules with an accuracy of 0.3 kcal mol−1 for energies and 1 kcal mol−1 Å̊−1 for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods. PMID:28508076
Genç, Gülten; Kulusakli, Emine; Aydin, Savas
Learners' perceived self-efficacy and beliefs on English language learning are important in education. Taking into consideration the important impact of individual variables on language learning, this study seeks to highlight the relationship between Turkish EFL learners' beliefs about language learning and their sense of self-efficacy. The…
.... In this research project, we have investigated methods and implemented algorithms for efficiently making certain classes of inference in belief networks, and for automatically learning certain...
Ariel, Robert; Hines, Jarrod C.; Hertzog, Christopher
People estimate minimal changes in learning when making predictions of learning (POLs) for future study opportunities despite later showing increased performance and an awareness of that increase (Kornell & Bjork, 2009). This phenomenon is conceptualized as a stability bias in judgments about learning. We investigated the malleability of this effect, and whether it reflected people’s underlying beliefs about learning. We manipulated prediction framing to emphasize the role of testing vs. studying on memory and directly measured beliefs about multi-trial study effects on learning by having participants construct predicted learning curves before and after the experiment. Mean POLs were more sensitive to the number of study-test opportunities when performance was framed in terms of study benefits rather than testing benefits and POLs reflected pre-existing beliefs about learning. The stability bias is partially due to framing and reflects discounted beliefs about learning benefits rather than inherent belief in the stability of performance. PMID:25067885
Robert, Nancy J.
This study investigated resident scientific evidence epistemology beliefs, evidence based medicine (EBM) self-efficacy beliefs, and EBM skills. A convenience sample of fifty-one residents located in six U.S. based residency programs completed an online instrument. Hofer's epistemology survey questionnaire was modified to test responses based on four types of scientific evidence encountered in medical practice (Clinical Trial Phase 1, Clinical Trial Phase 3, Meta-analysis and Qualitative). It was hypothesized that epistemology beliefs would differ based on the type of scientific evidence considered. A principal components analysis produced a two factor solution that was significant across type of scientific evidence suggesting that when evaluating epistemology beliefs context does matter. Factor 1 is related to the certainty of research methods and the certainty of medical conclusions and factor 2 denotes medical justification. For each type of scientific evidence, both factors differed on questions comprising the factor structure with significant differences found for the factor 1 and 2 questions. A justification belief case problem using checklist format was triangulated with the survey results, and as predicted the survey and checklist justification z scores indicated no significant differences, and two new justification themes emerged. Modified versions of Finney and Schraw's statistical self-efficacy and skill instruments produced expected significant EBM score correlations with unexpected results indicating that the number of EBM and statistics courses are not significant for EBM self-efficacy and skill scores. The study results were applied to the construction of a learning profile that provided residents belief and skill feedback specific to individual learning needs. The learning profile design incorporated core values related to 'Believer' populations that focus on art, harmony, tact and diplomacy. Future research recommendations include testing context
Ridley, Janice Rebecca Becky
The purpose of this dissertation was to assess K-12 teachers' perceptions of knowledge, beliefs, and practices toward brain-based learning strategies, how their knowledge relates to their beliefs and practices, and how their beliefs relate to their classroom practices. This research also investigated relationships between teachers' gender, years…
Altan, Mustapha X.
Beliefs are a central construct in every discipline which deals with human behavior and learning. Teachers' beliefs influence their consciousness, teaching attitude, teaching methods and teaching policies. Teachers' beliefs also strongly influence teaching behavior and, finally, learners' development. The formation of teachers' educational beliefs…
Oppermann, Elisa; Brunner, Martin; Eccles, Jacquelynne S.; Anders, Yvonne
Young children, ages 5-6 years, develop first beliefs about science and themselves as science learners, and these beliefs are considered important precursors of children's future motivation to pursue science. Yet, due to a lack of adequate measures, little is known about young children's motivational beliefs about learning science. The present…
Normahani, Pasha; Powezka, Katarzyna; Aslam, Mohammed; Standfield, Nigel J; Jaffer, Usman
We aimed to train podiatrists to perform a focused duplex ultrasound scan (DUS) of the tibial vessels at the ankle in diabetic patients; podiatry ankle (PodAnk) duplex scan. Thirteen podiatrists underwent an intensive 3-hour long simulation training session. Participants were then assessed performing bilateral PodAnk duplex scans of 3 diabetic patients with peripheral arterial disease. Participants were assessed using the duplex ultrasound objective structured assessment of technical skills (DUOSATS) tool and an "Imaging Score". A total of 156 vessel assessments were performed. All patients had abnormal waveforms with a loss of triphasic flow. Loss of triphasic flow was accurately detected in 145 (92.9%) vessels; the correct waveform was identified in 139 (89.1%) cases. Participants achieved excellent DUOSATS scores (median 24 [interquartile range: 23-25], max attainable score of 26) as well as "Imaging Scores" (8 [8-8], max attainable score of 8) indicating proficiency in technical skills. The mean time taken for each bilateral ankle assessment was 20.4 minutes (standard deviation ±6.7). We have demonstrated that a focused DUS for the purpose of vascular assessment of the diabetic foot is readily learned using intensive simulation training.
Ronald A. Beghetto
Full Text Available The purpose of this article is to provide an overview of the assessment of students' motivational beliefs. The..body of the article is focused on a particular type of motivational belief, namely, beliefs involving..achievement goal orientations. I explain why these beliefs are an important aspect of academic learning,..and suggest how teachers can incorporate assessments of them within existing classroom routines.
Ronald A. Beghetto
The purpose of this article is to provide an overview of the assessment of students' motivational beliefs. The..body of the article is focused on a particular type of motivational belief, namely, beliefs involving..achievement goal orientations. I explain why these beliefs are an important aspect of academic learning,..and suggest how teachers can incorporate assessments of them within existing classroom routines.
Solis, Carmen A.
Research shows that the belief the teachers have about teaching, learning, and their students affect their planning, instructing and evaluation processes in the classroom, and also that they have a repercussion on the student's learning and performance in the classroom. In the case of university teachers, the beliefs about the teaching-learning…
Aziz, Fakhra; Quraishi, Uzma
The present descriptive study aimed to get an insight into secondary school students' beliefs regarding English language learning. The survey method was employed for obtaining data from the secondary school students (N = 664). A modified version of "beliefs about language learning inventory" was used to collect data. Five out of nine…
Kizilgunes, Berna; Tekkaya, Ceren; Sungur, Semra
The authors proposed a model to explain how epistemological beliefs, achievement motivation, and learning approach related to achievement. The authors assumed that epistemological beliefs influence achievement indirectly through their effect on achievement motivation and learning approach. Participants were 1,041 6th-grade students. Results of the…
Lee, Silvia Wen-Yu; Liang, Jyh-Chong; Tsai, Chin-Chung
This study investigated the relationships among college students' epistemic beliefs in biology (EBB), conceptions of learning biology (COLB), and strategies of learning biology (SLB). EBB includes four dimensions, namely "multiple-source," "uncertainty," "development," and "justification." COLB is further…
Full Text Available It has been determined that beliefs about language learning are significant for the learning and teaching process, and that learners may differ in their beliefs towards learning a new language. Similarly, student-teachers of different subjects may differ in their beliefs about language learning. The main aim of this study was thus to investigate pre-service preschool teachers’, primary school teachers’, and special education teachers’ beliefs about foreign language learning in Slovenia. Three different areas were researched more closely: beliefs about foreign language aptitude, beliefs about the nature of learning and beliefs about foreign language motivations and expectations. The BALLI questionnaire was used to gather data, with responses provided by170 first-year students. The results show that despite attending different teacher training study programmes, students do not differ significantly in their beliefs about language learning; however, in comparison to other studies, the results imply that learners from different cultures see language learning differently.
Platas, Linda M.
The Mathematical Development Beliefs Survey was developed to measure early childhood teachers' beliefs about mathematics teaching and learning in the preschool classroom. This instrument was designed to measure beliefs concerning (a) age-appropriateness of mathematics instruction, (b) classroom locus of generation of mathematical knowledge…
Tamilselvan, Prasanna; Wang, Pingfeng
Effective health diagnosis provides multifarious benefits such as improved safety, improved reliability and reduced costs for operation and maintenance of complex engineered systems. This paper presents a novel multi-sensor health diagnosis method using deep belief network (DBN). DBN has recently become a popular approach in machine learning for its promised advantages such as fast inference and the ability to encode richer and higher order network structures. The DBN employs a hierarchical structure with multiple stacked restricted Boltzmann machines and works through a layer by layer successive learning process. The proposed multi-sensor health diagnosis methodology using DBN based state classification can be structured in three consecutive stages: first, defining health states and preprocessing sensory data for DBN training and testing; second, developing DBN based classification models for diagnosis of predefined health states; third, validating DBN classification models with testing sensory dataset. Health diagnosis using DBN based health state classification technique is compared with four existing diagnosis techniques. Benchmark classification problems and two engineering health diagnosis applications: aircraft engine health diagnosis and electric power transformer health diagnosis are employed to demonstrate the efficacy of the proposed approach
Bryan, Lynn Ann
This study examines how preservice elementary teacher beliefs and experiences within the context of reflective science teacher education influence the development of professional knowledge. From a cognitive constructivist theoretical perspective, I conducted a case analysis to investigate the beliefs about science teaching and learning held by a preservice teacher (Barbara), identify the tensions she encountered in learning to teach elementary science, understand the frames from which she identified problems of practice, and discern how her experiences influenced the process of reflecting on her own science teaching. From an analysis of interviews, observation, and written documents, I constructed a profile of Barbara's beliefs that consisted of three foundational and three dualistic beliefs about science teaching and learning. Her foundational beliefs concerned: (a) the value of science and science teaching, (b) the nature of scientific concepts and goals of science instruction, and (c) control in the science classroom. Barbara held dualistic beliefs about: (a) how children learn science, (b) the science students' role, and (c) the science teacher's role. The dualistic beliefs formed two contradictory nests of beliefs. One nest, grounded in life-long science learner experiences, reflected a didactic teaching orientation and predominantly guided her practice. The second nest, not well-grounded in experience, embraced a hands-on approach and predominantly guided her vision of practice. Barbara encountered tensions in thinking about science teaching and learning as a result of inconsistencies between her vision of science teaching and her actual practice. Confronting these tensions prompted Barbara to rethink the connections between her classroom actions and students' learning, create new perspectives for viewing her practice, and consider alternative practices more resonant with her visionary beliefs. However, the self-reinforcing belief system created by her
Kapucu, Serkan; Bahçivan, Eralp
Background: There are some theoretical evidences that explain the relationships between core beliefs (i.e., epistemological beliefs) and peripheral beliefs (self-efficacy in learning) in the literature. The close relationships of such type of beliefs with attitudes are also discussed by some researchers. Constructing a model that investigates…
Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan
Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.
Zikre, Nuraini Mohd; Eu, Leong Kwan
Teachers play a vital role in nurturing and shaping learners in school. Extensive researches have been conducted showing that beliefs in the nature of teaching and learning held by the teachers will affect their actual classroom practices. In Malaysia, not many studies have been done on mathematics teacher's beliefs at the national level. The…
Elder, Anastasia D.
The purpose of this study is to explore college students' self-reported cell phone use and beliefs and investigate the effect on student learning. Eighty-eight college students responded to a questionnaire about their use of cell phones during classes, studying, and driving and about their beliefs about how cell phones impact their schoolwork. In…
Chiu, Yen-Lin; Liang, Jyh-Chong; Tsai, Chin-Chung
Epistemic beliefs have been considered as important components of the self-regulatory model; however, their relationships with self-regulated learning processes in the Internet context need further research. The main purpose of this study was to examine the relationships between Internet-specific epistemic belief dimensions and self-regulated…
Ill-structured tasks presented in an inquiry learning environment have the potential to affect students' beliefs and attitudes towards mathematics. This empirical research followed a Design Experiment approach to explore how aspects of using ill-structured tasks may have affected students' beliefs and attitudes. Results showed this task type and…
Gilakjani, Abbas Pourhosein; Sabouri, Narjes Banou
Beliefs form part of the process of understanding how teachers shape their work which is significant to the comprehending of their teaching methods and their decisions in the classroom. Teachers' beliefs have been an interesting topic for researchers due to the input they provide for the improvement of English language teaching and learning.…
The present study intended to investigate the possible difference between EAP and EFL learners' beliefs concerning learning and teaching of language components, namely, vocabulary, pronunciation and grammar. Furthermore, this study examined the association between EAP and EFL learners' beliefs and their language components' development. To this…
Describes a study that determined the implications of computer graphics types and epistemological beliefs with regard to the design of computer-based mathematical concept learning with elementary school students in Taiwan. Discusses the factor structure of the epistemological belief questionnaire, student performance, and students' attitudes…
Doig, Brian; Adams, Ray
If teachers do not determine children's understandings and beliefs the children cannot be challenged. Five individual units are presented that have the intention of drawing out the underlying beliefs that children hold with respect to various aspects of science. "Skateboard News" is a newsletter which discusses aspects of skateboards and…
Trembath, David; Vivanti, Giacomo; Iacono, Teresa; Dissanayake, Cheryl
Children with autism spectrum disorder (ASD) are often described as visual learners. We tested this assumption in an experiment in which 25 children with ASD, 19 children with global developmental delay (GDD), and 17 typically developing (TD) children were presented a series of videos via an eye tracker in which an actor instructed them to manipulate objects in speech-only and speech + pictures conditions. We found no group differences in visual attention to the stimuli. The GDD and TD groups performed better when pictures were available, whereas the ASD group did not. Performance of children with ASD and GDD was positively correlated with visual attention and receptive language. We found no evidence of a prominent visual learning style in the ASD group.
Skipper, Mads; Nøhr, Susanne Backman; Jacobsen, Tine Klitgaard; Musaeus, Peter
Several studies have examined how doctors learn in the workplace, but research is needed linking workplace learning with the organisation of doctors' daily work. This study examined residents' and consultants' attitudes and beliefs regarding workplace learning and contextual and organisational factors influencing the organisation and planning of medical specialist training. An explorative case study in three paediatric departments in Denmark including 9 days of field observations and focus group interviews with 9 consultants responsible for medical education and 16 residents. The study aimed to identify factors in work organisation facilitating and hindering residents' learning. Data were coded through an iterative process guided by thematic analysis. Findings illustrate three main themes: (1) Learning beliefs about patient care and apprenticeship learning as inseparable in medical practice. Beliefs about training and patient care expressed in terms of training versus production caused a potential conflict. (2) Learning context. Continuity over time in tasks and care for patients is important, but continuity is challenged by the organisation of daily work routines. (3) Organisational culture and regulations were found to be encouraging as well inhibiting to a successful organisation of the work in regards to learning. Our findings stress the importance of consultants' and residents' beliefs about workplace learning as these agents handle the potential conflict between patient care and training of health professionals. The structuring of daily work tasks is a key factor in workplace learning as is an understanding of underlying relations and organisational culture in the clinical departments.
Lin, Tzung-Jin; Tsai, Chin-Chung
The purpose of this study was to develop and validate two survey instruments to evaluate high school students' scientific epistemic beliefs and goal orientations in learning science. The initial relationships between the sampled students' scientific epistemic beliefs and goal orientations in learning science were also investigated. A final valid sample of 600 volunteer Taiwanese high school students participated in this survey by responding to the Scientific Epistemic Beliefs Instrument (SEBI) and the Goal Orientations in Learning Science Instrument (GOLSI). Through both exploratory and confirmatory factor analyses, the SEBI and GOLSI were proven to be valid and reliable for assessing the participants' scientific epistemic beliefs and goal orientations in learning science. The path analysis results indicated that, by and large, the students with more sophisticated epistemic beliefs in various dimensions such as Development of Knowledge, Justification for Knowing, and Purpose of Knowing tended to adopt both Mastery-approach and Mastery-avoidance goals. Some interesting results were also found. For example, the students tended to set a learning goal to outperform others or merely demonstrate competence (Performance-approach) if they had more informed epistemic beliefs in the dimensions of Multiplicity of Knowledge, Uncertainty of Knowledge, and Purpose of Knowing.
Rosanna Y.-Y. Chan
Full Text Available Online social networks are popular venues for computer-supported collaborative work and computer-supported collaborative learning. Professionals within the same discipline, such as software developers, often interact over various social network sites for knowledge updates and collective understandings. The current study aims at gathering empirical evidences concerning gender differences in online social network beliefs and behaviors. A total of 53 engineering postgraduate students were engaged in a blogging community for collaborative learning. Participants’ beliefs about collaboration and nature of knowledge and knowing (i.e. epistemological beliefs are investigated. More specifically, social network analysis metrics including in-degree, out-degree, closeness centrality, and betweenness centrality are obtained from an 8-interval longitudinal SNA. Methodologically speaking, the current work puts forward mixed methods of longitudinal SNA and quantitative beliefs survey to explore online social network participants’ beliefs and behaviors. The study’s findings demonstrate significant gender differences in collaborative learning through online social networks, including (1 female engineering postgraduate students engage significantly more actively in online communications, (2 male engineering postgraduate students are more likely to be the potential controllers of information flows, and (3 gender differences exist in belief gains related to social aspects, but not individual's epistemic aspects. Overall, participants in both genders demonstrated enhanced beliefs in collaboration as well as the nature of knowledge and knowing.
Mutholib, Ahmad Abdul; Sujadi, Imam; Subanti, Sri
SA is the approach used for the exploration of research and answer questions. Teachers' beliefs have a greater influence than the teacher's knowledge of designing lesson plans in the classroom. The objectives of this study are to explore the teachers' beliefs in SA, to reveal how the beliefs are reflected in classroom practices; and to figure out the factors affecting their beliefs and practices of SA to the teaching of mathematics. This qualitative research applied case study. The data was gained from classroom observation, face-to-face interview, and documentation. Interactive models from Miles and Huberman were used to examine the data. Results of the study: 1) The teachers believe about the conception of SA. They also believe that the SA is important and gives impact to students' progress. They believe that by applying SA, the target of mathematics learning is acquired. As to learning procedure, they believe that SA steps are conducted in sequence by combining some steps for each. 2) Teachers formulate their beliefs of applying the five scientific step of integrating all steps by keeping the sequence. Teachers argue that target of mathematics learning can be attained by some ways, namely presence of theoretical and practical support, teachers' guidance, providing variety of media and motivation to students. 3) There are five factors which influence teachers' beliefs and practices of SA, namely learning and teaching experience, teachers' motivation, sharing with colleagues and facility. This study concludes that teachers believe in the importance of SA, therefore they implement it in the classroom.
The purpose of this paper is to investigate the impact of problem-based learning (PBL) on freshmen engineering students' beliefs about physics and physics learning (referred to as epistemological beliefs) and conceptual understanding of physics. The multiple-choice test of energy and momentum concepts and the Colorado learning attitudes about…
Sen, S.; Yilmaz, A.; Yurdagül, H.
This study aims at analysing the relations between students' achievement motivation, learning strategies and their epistemological beliefs in learning through structural equation modelling, and at exploring the mediation role of motivation in the relations between learning strategies and epistemological beliefs. The study group was composed of 446…
Jääskelä, Päivikki; Häkkinen, Päivi; Rasku-Puttonen, Helena
This study examines university teachers' beliefs about the role of technology in achieving the pedagogical aims of learning within teaching development initiatives at a Finnish university. The initiatives targeted technology adoption in teaching and learning and were enhanced within teacher groups, with support from a university-level network…
Boschman, F.; McKenney, S.; Pieters, J.M.; Voogt, J.
Teacher engagement in the design of technology-rich learning material is beneficial to teacher learning and may create a sense of ownership, both of which are conducive to bringing about innovation with technology. During collaborative design, teachers draw on various types of knowledge and beliefs:
Kormos, Judit; Kiddle, Thom; Csizer, Kata
In the present study, we surveyed the English language-learning motivations of 518 secondary school students, university students, and young adult learners in the capital of Chile, Santiago. We applied multi-group structural-equation modeling to analyze how language-learning goals, attitudes, self-related beliefs, and parental encouragement…
Çam, Aylin; Geban, Ömer
The purpose of the study was to investigate the effectiveness of case-based learning instruction over traditionally designed chemistry instruction on eleventh grade students' epistemological beliefs and their attitudes toward chemistry as a school subject. The subjects of this study consisted of 63 eleventh grade students from two intact classes of an urban high school instructed with same teacher. Each teaching method was randomly assigned to one class. The experimental group received case-based learning and the control group received traditional instruction. At the experimental group, life cases were presented with small group format; at the control group, lecturing and discussion was carried out. The results showed that there was a significant difference between the experimental and control group with respect to their epistemological beliefs and attitudes toward chemistry as a school subject in favor of case-based learning method group. Thus, case base learning is helpful for development of students' epistemological beliefs and attitudes toward chemistry.
Sahin, Elif Adibelli; Deniz, Hasan; Topçu, Mustafa Sami
The present study investigated to what extent Turkish preservice elementary teachers' orientations to teaching science could be explained by their epistemological beliefs, conceptions of learning, and approaches to learning science. The sample included 157 Turkish preservice elementary teachers. The four instruments used in the study were School…
Zhu, Lusha; Mathewson, Kyle E; Hsu, Ming
Decision-making in the presence of other competitive intelligent agents is fundamental for social and economic behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions of others competing for the same rewards. However, whereas we know much about strategic learning at both theoretical and behavioral levels, we know relatively little about the underlying neural mechanisms. Here, we show using a multi-strategy competitive learning paradigm that strategic choices can be characterized by extending the reinforcement learning (RL) framework to incorporate agents' beliefs about the actions of their opponents. Furthermore, using this characterization to generate putative internal values, we used model-based functional magnetic resonance imaging to investigate neural computations underlying strategic learning. We found that the distinct notions of prediction errors derived from our computational model are processed in a partially overlapping but distinct set of brain regions. Specifically, we found that the RL prediction error was correlated with activity in the ventral striatum. In contrast, activity in the ventral striatum, as well as the rostral anterior cingulate (rACC), was correlated with a previously uncharacterized belief-based prediction error. Furthermore, activity in rACC reflected individual differences in degree of engagement in belief learning. These results suggest a model of strategic behavior where learning arises from interaction of dissociable reinforcement and belief-based inputs.
Abdullah, Melissa Ng Lee Yen
Purpose: This study aimed to examine the interaction effects of gender and motivational beliefs on students' self-regulated learning. Specifically, three types of motivational beliefs under the Expectancy-Value Model were examined, namely self-efficacy, control beliefs and anxiety. Methodology: A quantitative correlational research design was used…
Orawiwatnakul, Wiwat; Wichadee, Saovapa
The concept of learner autonomy is now playing an important role in the language learning field. An emphasis is put on the new form of learning which enables learners to direct their own learning. This study aimed to examine how undergraduate students believed about autonomous language learning in a university setting and to find out whether some…
Noroozi, Omid; Hatami, Javad
Although the importance of students’ argumentative peer feedback for learning is undeniable, there is a need for further empirical evidence on whether and how it is related to various aspects of argumentation-based learning namely argumentative essay writing, domain-specific learning, and attitudinal change while considering their epistemic beliefs which are known to be related to argumentation. In this study, a pre-test–post-test design was conducted with 42 higher education students who wer...
Wisniewski, Matthew G; Bartone, Anne; Hastrup, Janice L; Coutinho, Mariana V C; Geer, Micah; Simms, Leonard J
University students' beliefs about tobacco and nicotine were assessed before an educational intervention aimed at correcting tobacco-related misinformation. Beliefs were again measured immediately after the intervention, and then again after a 2-, 4-, 6-, or 8-week retention interval. Initially, participants showed significantly more accurate beliefs about tobacco than pre-intervention, but this improvement decreased after the retention interval. Results suggest that methods currently used in an attempt to alleviate tobacco misinformation in the public may be effective for short-term, but not long-term retention. The current study accents the need to design tobacco programs that optimize retention of belief change so that people may use that knowledge confidently in future health-related decisions.
Full Text Available The study tends to explore the possible reforms to raise the proficiency level of the adult English as Foreign Language (EFL learners. With this end in view, it investigates non-native EFL teachers’ beliefs in relation to adult learners’ beliefs in teaching grammar to university students in the Saudi Arabian EFL context. It finds out the harmony and disharmony between the teachers at the giving end and the taught at the receiving end to create a culture of awareness and to build a better teaching-learning environment. The study tries to fill the existing research gap as no previous research has tried to find out the solution to the problem from this angle. The main data collection tools are two five-point Likert-scale questionnaires, administered to 70 non-native EFL teachers and their 80 adult students. Teachers and learners have been selected based on stratified random sampling. Quantitative data have been analyzed using the statistical package for social sciences (SPSS. The major findings of the study are that there is discrepancy in the grammar teaching beliefs of the EFL teachers and the taught and there is a communication gap between them which result into low English proficiency level of the EFL adult learners. Eventually, pedagogical implications of the lack of harmony between the teachers’ teaching creeds and the learners’ learning demands/expectations are provided for effective grammar teaching and better EFL classroom environment. The study recommends a better communicative harmony in both the stakeholders to bring reforms in adult education in EFL context.
Sadi, Özlem; Dagyar, Miray
The current work reveals the data of the study which examines the relationships among epistemological beliefs, conceptions of learning, and self-efficacy for biology learning with the help of the Structural Equation Modeling. Three questionnaires, the Epistemological Beliefs, the Conceptions of Learning Biology and the Self-efficacy for Learning…
This paper presents a model for the type of classroom environment believed to facilitate scientific conceptual change. A survey based on this model contains items about students' motivational beliefs, their study approach and their perceptions of their teacher's actions and learning goal orientation. Results obtained from factor analyses, correlations and analyses of variance, based on responses from 113 students, suggest that an empowering interpersonal teacher-student relationship is related to a deep approach to learning, a positive attitude to science, and positive self-efficacy beliefs, and may be increased by a constructivist approach to teaching.
Full Text Available The beliefs a teacher carries into the classroom are a strong predictor of behaviour and, thus, have educational implications. With more English Language Learners (ELLs worldwide, in mainstream classrooms in English speaking countries and in content-based classes in other countries around the globe than ever before, it is essential that preservice teachers’ beliefs about these students are understood and, when possible, altered to ensure positive and productive educational experiences. This study examined the initial language learning beliefs and attitudes toward ELLs among 354 pre-service teachers in a large public university and compared it to their beliefs after their ESL related coursework. The findings demonstrate beliefs about ELLs can be changed, influencing preservice teachers’ practices in future classrooms. Survey data collected before and after specific coursework revealed a significant shift in preservice teachers’ beliefs, indicating more alignment with current research and sound educational practice. Semi-structured focus-group interviews provided supporting evidence. These findings suggest pre-service teachers need evidence-based coursework in language development and language learning processes to overcome misconceptions regarding ELLs.
Clapp, Francis Neely
In the last decade, science education reform in the United States has emphasized the exploration of cognitive learning pathways, which are theories on how a person learns a particular science subject matter. These theories are based, in part, by Piagetian developmental theory. One such model, called Learning Progressions (LP), has become prominent within science education reform. Science education researchers design LPs which in turn are used by science educators to sequence their curricula. The new national science standards released in April 2013 (Next Generation Science Standards) are, in part, grounded in the LP model. Understanding how teachers apply and use LPs, therefore, is valuable because professional development programs are likely to use this model, given the federal attention LP have received in science education reform. I sought to identify the beliefs and discourse that both LP developers and intended LP implementers have around student learning, teaching, and learning progressions. However, studies measuring beliefs or perspectives of LP-focused projects are absent in published works. A qualitative research is therefore warranted to explore this rather uncharted research area. Research questions were examined through the use of an instrumental case study. A case study approach was selected over other methodologies, as the research problem is, in part, bound within a clearly identifiable case (a professional development experience centering on a single LP model). One of the broadest definitions of a case study is noted by Becker (1968), who stated that goals of case studies are "to arrive at a comprehensive understanding of the groups under study" and to develop "general theoretical statements about regularities in social structure and process." (p.233). Based on Merriam (1985) the general consensus in the case study literature is that the assumptions underlying this method are common to naturalistic inquiry with research conducted primarily in the
Nelson, Adrienne Fleurette
The purpose of this mixed method research study was to examine the constructivist beliefs and instructional practices of secondary science teachers. The research also explored situations that impacted whether or not student centered instruction occurred. The study revealed science teachers held constructive beliefs pertaining to student questioning of the learning process and student autonomy in interacting with other learners. Teachers held the least constructivist beliefs pertaining to student teacher collaboration on lesson design. Additionally, teacher beliefs and practice were not congruent due to instructional practices being deemed less constructivist than reported. The study found that curricular demands, teacher perceptions about students, inadequate laboratory resources, and the lack of teacher understanding about the components of constructivist instruction inhibited student centered instruction. The results of this study led to six recommendations that can be implemented by school districts in collaboration with science teachers to promote constructivist instruction.
Green, Angela; Jeffs, Debra A; Boateng, Beatrice A; Lowe, Gary R; Walden, Marlene
This research examined evidence-based practice (EBP) knowledge and beliefs before and after a 3-month e-learning program was implemented to build EBP capacity at a large children's hospital. Ten clinicians completed the development, implementation, and evaluation of the e-learning education, comprising phase one. Revision and participation by 41 clinicians followed in phase two. Participants in both phases completed the EBP Beliefs and Implementation Scales preintervention, postintervention, and 6 months after postintervention. EBP beliefs and implementation increased immediately and 6 months after postintervention, with statistically significant increases in both phases. Participants in both phases applied knowledge by completing mentor-supported EBP projects. Although EBP beliefs and implementation scores increased and e-learning provided flexibility for clinician participation, challenges arose, resulting in lower-than-expected completion. Subsequent revisions resulted in hybrid education, integrating classroom and e-learning with project mentoring. This funded e-learning research contributes knowledge to the growing specialty of professional development. J Contin Educ Nurs. 2017;48(7):304-311. Copyright 2017, SLACK Incorporated.
Lin, Yi-Chun; Liang, Jyh-Chong; Tsai, Chin-Chung
The aim of this study was to investigate the relationships between students' epistemic beliefs in biology and their approaches to learning biology. To this end, two instruments, the epistemic beliefs in biology and the approaches to learning biology surveys, were developed and administered to 520 university biology students, respectively. By and…
Saylan, Asli; Armagan, Fulya Öner; Bektas, Oktay
The present study investigated the relationship between pre-service science teachers' epistemological beliefs and perceptions of a constructivist learning environment. The Turkish version of Constructivist Learning Environment Survey and Schommer's Epistemological Belief Questionnaire were administered to 531 pre-service science teachers attending…
Dignath-van Ewijk, Charlotte; van der Werf, Greetje
In order to foster self-regulated learning (SRL), teachers should provide students with learning strategies, as well as with constructivist learning environments that allow them to self-regulate their learning. These two components complement each other. When investigating teachers’ promotion of SRL, not only teacher behavior, but also teachers’ beliefs as well as their knowledge about SRL are relevant aspects to consider. Therefore, this study seeks to examine teachers’ knowledge and beliefs...
Full Text Available The present study attempted to examine the relationship between English as a Foreign Language (EFL learnersâ motivational beliefs and their use of learning strategies. The three components of motivation, i.e. expectancy component, value component and affective component, were examined in relation to metacognitive, cognitive and effort management strategies. Two hundred and fifty seven EFL learners representing different proficiency levels completed the Persian version of the Motivated Strategies for Learning Questionnaire (MSLQ, which consisted of motivation scale and learning strategies scale. The analysis of the effect of proficiency level on motivational beliefs showed a significant effect of proficiency level on test anxiety and extrinsic goal orientation, suggesting that less proficient learners were significantly more anxious and more extrinsically oriented compared to advanced learners of English. It was also found that self-efficacy, control of learning beliefs, intrinsic goal orientation and task value could account for 70% of variations in self-regulated learning (SRL strategies. Based on the findings of this study, several suggestions are made to aid instructors in creating a non-product-oriented approach to learning, which promotes foreign language learnersâ learning outcomes.
This study examined the educational beliefs about teaching and learning of Chinese international and American-born graduate students in the disciplines of pure and applied sciences and mathematics at Auburn University by comparing their similarities and differences. The study reported (a) participants' demographic characteristics, (b) the dominant…
Examines how the demographic values of foreign travel, previous foreign-language learning, major field of study, and other factors affect students' beliefs about the study of German. The article focuses on student-perceived improvement in the four skills and cultural knowledge, student motivation, and the expected contributions of teachers and…
This paper examines the importance of future kindergarten teachers' beliefs about the usefulness of Games Based Learning in Early Childhood Education. Data were collected by using questionnaires which were given to the participants at the end of an introductory level, Information and Communication Technologies course. The sample of this study was…
Eickelmann, Birgit; Vennemann, Mario
In the debate on the integration of information and communication technologies (ICT) into schools, the beliefs and attitudes of teachers towards ICT in teaching and learning have always been regarded as central criteria for successful implementation of new technologies. In this context, a study in 2013 by the International Association for the…
Ulusoy, Yagmur; Duy, Baki
The purpose of this study was to examine the effect of a psycho-education program aimed at reducing learned helplessness and irrational beliefs of eight-grade elementary students. The study was an experimental study based on the pre-test-post-test model with control and placebo group. A total of 27 participants, 9 group members in each group,…
Schroeder, Sascha; Richter, Tobias; McElvany, Nele; Hachfeld, Axinja; Baumert, Jurgen; Schnotz, Wolfgang; Horz, Holger; Ullrich, Mark
This study investigated the relations between teachers' pedagogical beliefs and students' self-reported engagement in learning from texts with instructional pictures. Participants were the biology, geography, and German teachers of 46 classes (Grades 5-8) and their students. Teachers' instructional behaviors and students' engagement in learning…
Yeung, Alexander S.; Craven, Rhonda G.; Kaur, Gurvinder
One's self-concept and value perceptions can significantly influence one's behaviours and beliefs. Australian teachers from urban and rural areas of the state of New South Wales were asked to respond to survey items on two predictors (teacher self-concept, valuing of learning) and three outcomes. Confirmatory factor analysis established the five…
Cam, Aylin; Geban, Omer
The purpose of the study was to investigate the effectiveness of case-based learning instruction over traditionally designed chemistry instruction on eleventh grade students' epistemological beliefs and their attitudes toward chemistry as a school subject. The subjects of this study consisted of 63 eleventh grade students from two intact classes…
Moekotte, Paulo; Brand-Gruwel, Saskia; Ritzen, Henk
Abstract: In this case study, we explore the beliefs of teachers (AKA teachers) who work with at-risk students and consider using social media in their learning environment. We interviewed and observed a group of teachers who, as a project team, explored social media use in order to develop their
Tam, Angela Choi Fung
This longitudinal study aimed to examine the role of a professional learning community (PLC) in changing teachers' beliefs and practices. Teachers of a Chinese department in a Hong Kong secondary school were interviewed and observed. The findings indicate that the features of a PLC-facilitating teacher change are development of a coherent…
Pedemonte, Stefano; Pierce, Larry; Van Leemput, Koen
to impose the depth-of-interaction in an experimental set-up. In this article we introduce a machine learning approach for extracting accurate forward models of gamma imaging devices from simple pencil-beam measurements, using a nonlinear dimensionality reduction technique in combination with a finite...
The Dempster-Shafer theory of belief functions provides a unified framework for handling both aleatory uncertainty, arising from statistical variability in populations, and epistemic uncertainty, arising from incompleteness of knowledge. An overview of both the fundamentals and some recent developments in this theory will first be presented. Several applications in data analysis and machine learning will then be reviewed, including learning under partial supervision, multi-label classification, ensemble clustering and the treatment of pairwise comparisons in sensory or preference analysis.
Ambrose Hans G. Aggabao
Full Text Available Path and factor analyses were used in this study to investigate direct and indirect influences of instructional interventions on achievement and retention of learning among freshmen students in Mathematics as mediated by affective beliefs. The varying classroom contexts were hypothesized to influence affective beliefs through the application of varying instructional interventions – traditional teaching, radical constructivist, and social constructivist. The randomized equivalent groups pre-posttest experimental design was used to generate the needed data for analysis. Results showed that constructivist instructional approaches directly and indirectly influenced achievement measures with the indirect effects mediated by control orientation belief of students which was found to be the only one among four affective beliefs considered in this study to influence achievement measures. Social constructivist interventions did not show direct influence on retention of conceptual understanding and procedural fluency while traditional instructional intervention was not found to be a significant predictor of both affective beliefs and achievement measures.These results confirm for the most part the hypothesized relations among instructional interventions, affective beliefs, and achievement measures.
Full Text Available The present study intended to investigate the possible difference between EAP and EFL learners’ beliefs concerning learning and teaching of language components, namely, vocabulary, pronunciation and grammar. Furthermore, this study examined the association between EAP and EFL learners’ beliefs and their language components’ development. To this end, 231 undergraduate EAP (117 and EFL (114 learners at Ferdowsi University took part in the study by completing a five-point Likert scale questionnaire adapted from Simon and Taverniers (2011. The face and content validity of the questionnaire was confirmed by the experts’ judgment and factor analysis. Moreover using Cronbach alpha coefficient the questionnaire was found acceptably reliable (α=0.88. Furthermore, for language components’ development, the EAP learners’ scores in English course and EFL learners’ average scores in their Basic English courses were taken into account. The results of an Independent Samples t-test revealed that there existed a statistically significant difference between EAP and EFL learners’ beliefs on learning and teaching language components. Furthermore, the results of Pearson correlation coefficients indicated a statistically significant positive association between EFL learners’ beliefs and their language components’ development, however no statistically significant correlation was found between EAP learners’ beliefs and their language components’ development.
Karen M. Scott
Full Text Available As universities invest in the development of e-learning resources, e-learning sustainability has come under consideration. This has largely focused on the challenges and facilitators of organisational and technological sustainability and scalability, and professional development. Little research has examined the experience of a teacher dealing with e-learning sustainability when taking over a course with an e-learning resource and associated assessment. This research focuses on a teacher who was inexperienced with e-learning technology, yet took over a blended unit of study with an e-learning resource that accounted for one-fifth of the subject assessment and was directed towards academic skills development relevant to the degree program. Taking a longitudinal approach, this research examines the challenges faced by the new teacher and the way she changed the e-learning resource and its implementation over two years. A focus of the research is the way the teacher's reflections on the challenges and changes provided an opportunity and stimulus for change in her e-learning beliefs and practices. This research has implications for the way universities support teachers taking over another teacher's e-learning resource, the need for explicit documentation of underpinning beliefs and structured handover, the benefit of teamwork in developing e-learning resources, and provision of on-going support.
Tulis, Maria; Steuer, Gabriele; Dresel, Markus
Research on learning from errors gives reason to assume that errors provide a high potential to facilitate deep learning if students are willing and able to take these learning opportunities. The first aim of this study was to analyse whether beliefs about errors as learning opportunities can be theoretically and empirically distinguished from…
Lin, Yi-Chun; Liang, Jyh-Chong; Tsai, Chin-Chung
The aim of this study was to investigate the relationships between students' epistemic beliefs in biology and their approaches to learning biology. To this end, two instruments, the epistemic beliefs in biology and the approaches to learning biology surveys, were developed and administered to 520 university biology students, respectively. By and large, it was found that the students reflected "mixed" motives in biology learning, while those who had more sophisticated epistemic beliefs tended to employ deep strategies. In addition, the results of paired t tests revealed that the female students were more likely to possess beliefs about biological knowledge residing in external authorities, to believe in a right answer, and to utilize rote learning as a learning strategy. Moreover, compared to juniors and seniors, freshmen and sophomores tended to hold less mature views on all factors of epistemic beliefs regarding biology. Another comparison indicated that theoretical biology students (e.g. students majoring in the Department of Biology) tended to have more mature beliefs in learning biology and more advanced strategies for biology learning than those students studying applied biology (e.g. in the Department of Biotechnology). Stepwise regression analysis, in general, indicated that students who valued the role of experiments and justify epistemic assumptions and knowledge claims based on evidence were more oriented towards having mixed motives and utilizing deep strategies to learn biology. In contrast, students who believed in the certainty of biological knowledge were more likely to adopt rote learning strategies and to aim to qualify in biology.
Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab
Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelity quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.
it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance.
Belo, Neeltje Annigje Hendrika
This doctoral thesis comprises two questionnaire studies and two small-scale interview studies on the content and structure of physics teachers’ belief systems. The studies focused on teachers’ beliefs about the goals and pedagogy of teaching and learning physics, and the nature of science. The samples consisted of physics teachers working at secondary schools in the Netherlands (students aged 12-18). The questionnaire studies showed that, on average, teachers’ belief systems about teaching a...
Full Text Available By the advent of new theories and approaches toward language teaching, a lot of attention has been paid to the role of those approaches on language learners. Superiority of psychology and linguistics in the area of language teaching urged scholars to develop new theories and techniques through a defined procedure. Most of the time the role of teacher’s experience as learner has been neglected. The present study was an attempt to investigate the relationship between EFL In-service teachers’ language learning strategies and their beliefs toward teaching methodologies. To find the relationship, a questionnaire was applied. The questionnaire in the study consists of three measures: (1 the individual background; (2 strategy inventory for language learning (Version 7.0 for ESL/EFL, Oxford, 1990; and, (3 beliefs toward English teaching methodologies (Chen, 2005. It was given to 252 in-service English teachers (136 female, 116 male majoring in TEFL. To analyze the quantitative data of the present study, descriptive as well as inferential analysis including ANOVA and Pearson’s correlations were used to investigate the relationships between language learning strategies and teaching beliefs toward EFL methodologies. Based on the teachers’ answers to the questionnaire, there was a meaningful relationship between language learning strategies and teacher’s methodology. The information provided in the present research can be helpful for teachers, policy holders of institutes and material developers. This study has also some implications for the researchers interested in teacher’s education studies.
Full Text Available The study investigated the effect of problem-based learning (PBL on senior secondary school students' beliefs about Further Mathematics in Nigeria within the blueprint of pre-test-post-test non-equivalent control group quasi-experimental design. Intact classes were used and in all, 96 students participated in the study (42 in the experimental group taught with the PBL and 54 in the control group taught using the Traditional Method (TM. One research instrument tagged Beliefs about Further Mathematics Questionnaire (BFMQ, Cronbach alpha (α=.86 was developed and used for the study and data collected were analysed using the descriptive statistics of mean and standard deviation which served as precursor to testing the null hypothesis for the study using an independent samples t-test and analysis of variance. Results showed that participants held strong beliefs about further mathematics and there was a statistically significant difference in the mean post-treatment scores on BFMQ (t=-6.22, p=.000 for t-test and (F(1,95=38.49; p<.001 for ANOVA between students exposed to the PBL and those exposed to the TM, in favour of the PBL group. Based on the results, the study recommended that PBL should be adopted as an instructional strategy for promoting meaningful learning in and enhancing beliefs about further mathematics and efforts should be made to integrate the philosophy of PBL into the preservice teachers' curriculum at the teacher-preparation institutions in Nigeria.
Belo, Neeltje Annigje Hendrika
This doctoral thesis comprises two questionnaire studies and two small-scale interview studies on the content and structure of physics teachers’ belief systems. The studies focused on teachers’ beliefs about the goals and pedagogy of teaching and learning physics, and the nature of science. The
The present study investigated the contribution of epistemological beliefs about learning and Asian values on pre-service teachers' value for education. The relationship of epistemological beliefs and valuing education is based on Schwartz and Bilsky's (1987; 1990) theory of human values. The participants were 362 pre-service teachers from…
Asian Americans have been recognized as the "model minority" in the United States since the 1960s. Students from Asian countries are winning in international competitions, especially in science and mathematics. Modern Western scholars working within the constructivist learning theory advocate malleable intelligence and effort, which…
Lee, Silvia Wen-Yu; Liang, Jyh-Chong; Tsai, Chin-Chung
This study investigated the relationships among college students' epistemic beliefs in biology (EBB), conceptions of learning biology (COLB), and strategies of learning biology (SLB). EBB includes four dimensions, namely 'multiple-source,' 'uncertainty,' 'development,' and 'justification.' COLB is further divided into 'constructivist' and 'reproductive' conceptions, while SLB represents deep strategies and surface learning strategies. Questionnaire responses were gathered from 303 college students. The results of the confirmatory factor analysis and structural equation modelling showed acceptable model fits. Mediation testing further revealed two paths with complete mediation. In sum, students' epistemic beliefs of 'uncertainty' and 'justification' in biology were statistically significant in explaining the constructivist and reproductive COLB, respectively; and 'uncertainty' was statistically significant in explaining the deep SLB as well. The results of mediation testing further revealed that 'uncertainty' predicted surface strategies through the mediation of 'reproductive' conceptions; and the relationship between 'justification' and deep strategies was mediated by 'constructivist' COLB. This study provides evidence for the essential roles some epistemic beliefs play in predicting students' learning.
Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong
In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.
Health care professionals are expected to provide patient care based on best evidence. The context of the acute care setting presents a challenging environment for registered nurses (RNs) to utilize research and implement best evidence in practice. No organizational infrastructure has been identified that offers acute care RNs the support needed for evidence-based practice (EBP). The value of "learning organizations" has long been understood by corporate leaders. Potentially, the dimensions of a "learning organization" may offer a supportive EBP infrastructure for acute care RNs. (1) What is the relationship of the characteristics of the learning organization to registered nurses' beliefs regarding EBP? (2) Is there an impact of EBP beliefs on RNs' implementation of EBP? A descriptive, survey design study was conducted. Three established questionnaires were distributed to 1,750 RNs employed within six acute care hospitals. There were 594 questionnaires returned for a response rate of 34%. RNs rated their organizations in the mid-range on the dimensions of learning organization. Perceptions of the learning organization were found to be significant, although relatively small, predictors explaining 6% of knowledge beliefs, 11% of value beliefs, and 14% of resource beliefs. EBP beliefs explained 23% of EBP implementation reported by RNs. The study results indicate relationships between RNs' reported perception of a learning organization and EBP beliefs, and between EBP beliefs and implementation. However, findings were mixed. Overall, nurses rated their organizations the lowest in the dimensions of "promote inquiry and dialogue" and "empower people toward a collective vision." Leaders have an opportunity to offer a more supportive infrastructure through improving their organization in these two areas. RN beliefs explained 23% of EBP implementation in this study with a residual 77% yet to be identified. Acute care hospitals were perceived mid-range on learning
Adams, W. K.; Perkins, K. K.; Podolefsky, N. S.; Dubson, M.; Finkelstein, N. D.; Wieman, C. E.
The Colorado Learning Attitudes about Science Survey (CLASS) is a new instrument designed to measure student beliefs about physics and about learning physics. This instrument extends previous work by probing additional aspects of student beliefs and by using wording suitable for students in a wide variety of physics courses. The CLASS has been validated using interviews, reliability studies, and extensive statistical analyses of responses from over 5000 students. In addition, a new methodology for determining useful and statistically robust categories of student beliefs has been developed. This paper serves as the foundation for an extensive study of how student beliefs impact and are impacted by their educational experiences. For example, this survey measures the following: that most teaching practices cause substantial drops in student scores; that a student’s likelihood of becoming a physics major correlates with their “Personal Interest” score; and that, for a majority of student populations, women’s scores in some categories, including “Personal Interest” and “Real World Connections,” are significantly different from men’s scores.
Chiu, Yen-Lin; Liang, Jyh-Chong; Hou, Cheng-Yen; Tsai, Chin-Chung
Students' epistemic beliefs may vary in different domains; therefore, it may be beneficial for medical educators to better understand medical students' epistemic beliefs regarding medicine. Understanding how medical students are aware of medical knowledge and how they learn medicine is a critical issue of medical education. The main purposes of this study were to investigate medical students' epistemic beliefs relating to medical knowledge, and to examine their relationships with students' approaches to learning medicine. A total of 340 undergraduate medical students from 9 medical colleges in Taiwan were surveyed with the Medical-Specific Epistemic Beliefs (MSEB) questionnaire (i.e., multi-source, uncertainty, development, justification) and the Approach to Learning Medicine (ALM) questionnaire (i.e., surface motive, surface strategy, deep motive, and deep strategy). By employing the structural equation modeling technique, the confirmatory factor analysis and path analysis were conducted to validate the questionnaires and explore the structural relations between these two constructs. It was indicated that medical students with multi-source beliefs who were suspicious of medical knowledge transmitted from authorities were less likely to possess a surface motive and deep strategies. Students with beliefs regarding uncertain medical knowledge tended to utilize flexible approaches, that is, they were inclined to possess a surface motive but adopt deep strategies. Students with beliefs relating to justifying medical knowledge were more likely to have mixed motives (both surface and deep motives) and mixed strategies (both surface and deep strategies). However, epistemic beliefs regarding development did not have significant relations with approaches to learning. Unexpectedly, it was found that medical students with sophisticated epistemic beliefs (e.g., suspecting knowledge from medical experts) did not necessarily engage in deep approaches to learning medicine
von Bergmann, HsingChi; Walker, Judith; Dalrymple, Kirsten R; Shuler, Charles F
The aims of this exploratory study were to explore dental faculty members' views and beliefs regarding knowledge, the dental profession, and teaching and learning and to determine how these views related to their problem-based learning (PBL) instructional practices. Prior to a PBL in dental education conference held in 2011, all attendees were invited to complete a survey focused on their pedagogical beliefs and practices in PBL. Out of a possible 55 participants, 28 responded. Additionally, during the conference, a forum was held in which preliminary survey findings were shared and participants contributed to focus group data collection. The forum results served to validate and bring deeper understanding to the survey findings. The conference participants who joined the forum (N=32) likely included some or many of the anonymous respondents to the survey, along with additional participants interested in dental educators' beliefs. The findings of the survey and follow-up forum indicated a disconnect between dental educators' reported views of knowledge and their pedagogical practices in a PBL environment. The results suggested that the degree of participants' tolerance of uncertainty in knowledge and the discrepancy between their epistemological and ontological beliefs about PBL pedagogy influenced their pedagogical choices. These findings support the idea that learner-centered, inquiry-based pedagogical approaches such as PBL may create dissonance between beliefs about knowledge and pedagogical practice that require the building of a shared understanding of and commitment to curricular goals prior to implementation to ensure success. The methods used in this study can be useful tools for faculty development in PBL programs in dental education.
Zhang, Jing; Song, Yanlin; Xia, Fan; Zhu, Chenjing; Zhang, Yingying; Song, Wenpeng; Xu, Jianguo; Ma, Xuelei
Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, artificial intelligence (AI) with deep learning technology has shown bright future in medicine. We hypothesize that AI with deep learning technology could help IOPD, with a computer trained by a dataset of intraoperative lesion images. Evidences supporting our hypothesis included the successful use of AI with deep learning technology in diagnosing skin cancer, and the developed method of deep-learning algorithm. Large size of the training dataset is critical to increase the diagnostic accuracy. The performance of the trained machine could be tested by new images before clinical use. Real-time diagnosis, easy to use and potential high accuracy were the advantages of AI for IOPD. In sum, AI with deep learning technology is a promising method to help rapid and accurate IOPD. Copyright © 2017 Elsevier Ltd. All rights reserved.
This paper examines the notion of teacher beliefs as complex ideological systems which have a bearing on actions. The focus is on the beliefs that students bring into their formal teacher education program, which are based on their predominantly authoritarian and didactic schooling experience. These students enter teacher education with…
In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.
Askew, Chris; Hagel, Anna; Morgan, Julie
Models of social anxiety suggest that negative social experiences contribute to the development of social anxiety, and this is supported by self-report research. However, there is relatively little experimental evidence for the effects of learning experiences on social cognitions. The current study examined the effect of observing a social performance situation with a negative outcome on children's (8 to 11 years old) fear-related beliefs and cognitive processing. Two groups of children were each shown 1 of 2 animated films of a person trying to score in basketball while being observed by others; in 1 film, the outcome was negative, and in the other, it was neutral. Children's fear-related beliefs about performing in front of others were measured before and after the film and children were asked to complete an emotional Stroop task. Results showed that social fear beliefs increased for children who saw the negative social performance film. In addition, these children showed an emotional Stroop bias for social-anxiety-related words compared to children who saw the neutral film. The findings have implications for our understanding of social anxiety disorder and suggest that vicarious learning experiences in childhood may contribute to the development of social anxiety. (c) 2015 APA, all rights reserved).
Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K
In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.
Charlotte Dignath-van Ewijk
Full Text Available In order to foster self-regulated learning (SRL, teachers should provide students with learning strategies, as well as with constructivist learning environments that allow them to self-regulate their learning. These two components complement each other. When investigating teachers’ promotion of SRL, not only teacher behavior, but also teachers’ beliefs as well as their knowledge about SRL are relevant aspects to consider. Therefore, this study seeks to examine teachers’ knowledge and beliefs on promoting SRL, as well as their predictive value on teachers’ promotion of SRL in the classroom. Forty-seven primary school teachers completed questionnaires on knowledge and beliefs towards both components of the promotion of SRL: strategy instruction and a constructivist learning environment. In addition, teachers had to answer open-ended questions on their understanding of SRL, as well as their implementation of SRL in their classroom. The results show that teachers are more positive towards constructivist than towards SRL (teacher beliefs, and most teachers mentioned characteristics of constructivist learning environments, while only few teachers addressed strategy instruction when being asked about their understanding of SRL (teacher knowledge. Moreover, teacher beliefs are the only predictor for teacher behavior. The results indicate how teacher education could support teachers to learn how to promote SRL effectively.
Rostamian, Marzieh; Kazemi, Ashraf
Physical activities among adolescents affects health during pubescence and adolescence and decrease in physical activities among adolescents has become a global challenge. The aim of the present study was to define the relation between the level of physical activity among adolescent girls and their health beliefs as personal factor and level of observational learning as environmental factor. The present study was a cross-sectional study that was conducted on 400 students aged from 11 to 19 years in Isfahan, Iran. Information regarding the duration of physical activity with moderate/severe intensity was measured in four dimensions of leisure time (exercising and hiking), daily activities, and transportation-related activities using the International Physical Activity questionnaire. Health belief structures included perceived sensitivity, intensity of perceived threat, perceived benefits, and barriers and self-efficacy; observational learning was measured using a researcher-made questionnaire. Results showed that perceived barriers, observational learning, and level of self-efficacy were related to the level of physical activity in all dimensions. In addition, the level of physical activity at leisure time, transportation, and total physical activity were dependent on the intensity of perceived threats ( P < 0.05). This study showed that the intensity of perceived threats, perceived barriers and self-efficacy structures, and observational learning are some of the factors related to physical activity among adolescent girls, and it is possible that by focusing on improving these variables through interventional programs physical activity among adolescent girls can be improved.
Adebileje, Sikiru Afolabi; Ghasemi, Keyvan; Aiyelabegan, Hammed Tanimowo; Saligheh Rad, Hamidreza
Proton magnetic resonance spectroscopy is a powerful noninvasive technique that complements the structural images of cMRI, which aids biomedical and clinical researches, by identifying and visualizing the compositions of various metabolites within the tissues of interest. However, accurate classification of proton magnetic resonance spectroscopy is still a challenging issue in clinics due to low signal-to-noise ratio, overlapping peaks of metabolites, and the presence of background macromolecules. This paper evaluates the performance of a discriminate dictionary learning classifiers based on projective dictionary pair learning method for brain gliomas proton magnetic resonance spectroscopy spectra classification task, and the result were compared with the sub-dictionary learning methods. The proton magnetic resonance spectroscopy data contain a total of 150 spectra (74 healthy, 23 grade II, 23 grade III, and 30 grade IV) from two databases. The datasets from both databases were first coupled together, followed by column normalization. The Kennard-Stone algorithm was used to split the datasets into its training and test sets. Performance comparison based on the overall accuracy, sensitivity, specificity, and precision was conducted. Based on the overall accuracy of our classification scheme, the dictionary pair learning method was found to outperform the sub-dictionary learning methods 97.78% compared with 68.89%, respectively. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Goebel, Camille A.
This longitudinal investigation explores the change in four (3 female, 1 male) science undergraduates' beliefs expressed about low-income elementary school students' ability to learn science. The study sought to identify how the undergraduates in year-long public school science-teaching partnerships perceived the social, cultural, and economic factors affecting student learning. Previous service-learning research infrequently focused on science undergraduates relative to science and society or detailed expressions of their beliefs and field practices over the experience. Qualitative methodology was used to guide the implementation and analysis of this study. A sample of an additional 20 science undergraduates likewise involved in intensive reflection in the service learning in science teaching (SLST) course called Elementary Science Education Partners (ESEP) was used to examine the typicality of the case participants. The findings show two major changes in science undergraduates' belief expressions: (1) a reduction in statements of beliefs from a deficit thinking perspective about the elementary school students' ability to learn science, and (2) a shift in the attribution of students, underlying problems in science learning from individual-oriented to systemic-oriented influences. Additional findings reveal that the science undergraduates perceived they had personally and profoundly changed as a result of the SLST experience. Changes include: (1) the gain of a new understanding of others' situations different from their own; (2) the realization of and appreciation for their relative positions of privilege due to their educational background and family support; (3) the gain in ability to communicate, teach, and work with others; (4) the idea that they were more socially and culturally connected to their community outside the university and their college classrooms; and (5) a broadening of the way they understood or thought about science. Women participants stated
Shao, Haidong; Jiang, Hongkai; Zhang, Haizhou; Duan, Wenjing; Liang, Tianchen; Wu, Shuaipeng
The vibration signals collected from rolling bearing are usually complex and non-stationary with heavy background noise. Therefore, it is a great challenge to efficiently learn the representative fault features of the collected vibration signals. In this paper, a novel method called improved convolutional deep belief network (CDBN) with compressed sensing (CS) is developed for feature learning and fault diagnosis of rolling bearing. Firstly, CS is adopted for reducing the vibration data amount to improve analysis efficiency. Secondly, a new CDBN model is constructed with Gaussian visible units to enhance the feature learning ability for the compressed data. Finally, exponential moving average (EMA) technique is employed to improve the generalization performance of the constructed deep model. The developed method is applied to analyze the experimental rolling bearing vibration signals. The results confirm that the developed method is more effective than the traditional methods.
Shea, Nicole A.; Mouza, Chrystalla; Drewes, Andrea
In this work, we present the design, implementation, and initial outcomes of the Climate Academy, a hybrid professional development program delivered through a combination of face-to-face and online interactions, intended to prepare formal and informal science teachers (grades 5-16) in teaching about climate change. The Climate Academy was designed around core elements of successful environmental professional development programs and aligned with practices advocated in benchmarked science standards. Data were collected from multiple sources including observations of professional development events, participants' reflections on their learning, and collection of instructional units designed during the Academy. Data were also collected from a focal case study teacher in a middle school setting. Case study data included classroom observations, teacher interviews, and student beliefs toward climate change. Results indicated that the Climate Academy fostered increased learning among participants of both climate science content and pedagogical strategies for teaching about climate change. Additionally, results indicated that participants applied their new learning in the design of climate change instructional units. Finally, results from the case study indicated positive impacts on student beliefs and greater awareness about climate change. Results have implications for the design of professional development programs on climate change, a topic included for the first time in national standards.
Serra, Michael J; Dunlosky, John
In two experiments we systematically explored whether people consider the format of text materials when judging their text learning, and whether doing so might inappropriately bias their judgements. Participants studied either text with diagrams (multimedia) or text alone and made both per-paragraph judgements and global judgements of their text learning. In Experiment 1 they judged their learning to be better for text with diagrams than for text alone. In that study, however, test performance was greater for multimedia, so the judgements may reflect either a belief in the power of multimedia or on-line processing. Experiment 2 replicated this finding and also included a third group that read texts with pictures that did not improve text performance. Judgements made by this group were just as high as those made by participants who received the effective multimedia format. These results confirm the hypothesis that people's metacomprehension judgements can be influenced by their beliefs about text format. Over-reliance on this multimedia heuristic, however, might reduce judgement accuracy in situations where it is invalid.
G, Sayantan; T, Kien P; V, Kadambari K
A new semi-supervised approach based on deep learning and active learning for classification of electrocardiogram signals (ECG) is proposed. The objective of the proposed work is to model a scientific method for classification of cardiac irregularities using electrocardiogram beats. The model follows the Association for the Advancement of medical instrumentation (AAMI) standards and consists of three phases. In phase I, feature representation of ECG is learnt using Gaussian-Bernoulli deep belief network followed by a linear support vector machine (SVM) training in the consecutive phase. It yields three deep models which are based on AAMI-defined classes, namely N, V, S, and F. In the last phase, a query generator is introduced to interact with the expert to label few beats to improve accuracy and sensitivity. The proposed approach depicts significant improvement in accuracy with minimal queries posed to the expert and fast online training as tested on the MIT-BIH Arrhythmia Database and the MIT-BIH Supra-ventricular Arrhythmia Database (SVDB). With 100 queries labeled by the expert in phase III, the method achieves an accuracy of 99.5% in "S" versus all classifications (SVEB) and 99.4% accuracy in "V " versus all classifications (VEB) on MIT-BIH Arrhythmia Database. In a similar manner, it is attributed that an accuracy of 97.5% for SVEB and 98.6% for VEB on SVDB database is achieved respectively. Graphical Abstract Reply- Deep belief network augmented by active learning for efficient prediction of arrhythmia.
This study examined the role of kindergarten children's feelings about the perceived quality of their relationships with their teachers and their emotions towards their teachers in their competence beliefs and learning motivation (intrinsic interest, learning goals), in the impact of competence beliefs on learning motivation, and in turn in school…
Gao, Xuesong; Ma, Qing
Language learners and teachers' cognition in respect of learning and teaching plays a critical role in mediating their actual behaviour and decisions in the process. This study investigates the vocabulary learning and teaching beliefs held by pre-service and in-service teachers in Hong Kong and on the Chinese mainland so that teacher education…
Al-Amoush, Siham A.; Markic, Silvija; Abu-Hola, Imfadi; Eilks, Ingo
This paper presents an exploratory study of Jordanian chemistry student teachers' and experienced teachers' beliefs about teaching and learning. Different instruments were used, focusing on different aspects of teaching and learning. The first instrument is based on teachers' and students' drawings of teaching situations. It includes open…
Ng, Florrie Fei-Yin; Pomerantz, Eva M.; Lam, Shui-fong
Chinese and American mothers' beliefs about children's learning and parents' role in it were examined using notions salient in Chinese culture. Mothers from Hong Kong ("n" = 66) and the United States ("n" = 69) indicated their endorsement of the ideas that children's learning reflects children's morality, and parents' support…
This research aimed to investigate; students' English academic achievement, beliefs about English language learning, English language learning strategies, and the relationship of them. Descriptive and correlational design, quantitative methods were applied in this research. The students' final English scores of the first year, BALLI, and SILL were…
Cheung, Sum Kwing; Ling, Elsa Ka-wei; Leung, Suzannie Kit Ying
The physical, social and temporal dimensions of the classroom environment have an important role in children's learning. This study examines the level of support for child-centred learning, and its associated beliefs, that is provided by Hong Kong's pre-service early childhood teachers. Two hundred and seventy-five students from a pre-service…
Hagmayer, York; Engelmann, Neele
Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic lite...
Full Text Available AbstractProfessional identity is a key issue spanning the entirety of teachers’ career development. Despite the abundance of existing research examining professional identity, its link with occupation-related behavior at the primary career stage (i.e., GPA in preservice education and the potential process that underlies this association is still not fully understood. This study explored the professional identity of Chinese preservice teachers, and its links with task value belief, intrinsic learning motivation, extrinsic learning motivation, and performance in the education program. Grade-point average (GPA of courses (both subject and pedagogy courses was examined as an indicator of performance, and questionnaires were used to measure the remaining variables. Data from 606 preservice teachers in the first three years of a teacher-training program indicated that: (1 variables in this research were all significantly correlated with each other, except the correlation between intrinsic learning motivation and program performance; (2 professional identity was positively linked to task value belief, intrinsic and extrinsic learning motivations, and program performance in a structural equation model (SEM; (3 task value belief was positively linked to intrinsic and extrinsic learning motivation; (4 higher extrinsic (but not intrinsic learning motivation was associated with increased program performance; and (5 task value belief and extrinsic learning motivation were significant mediators in the model.
Zhang, Yan; Hawk, Skyler T; Zhang, Xiaohui; Zhao, Hongyu
Professional identity is a key issue spanning the entirety of teachers' career development. Despite the abundance of existing research examining professional identity, its link with occupation-related behavior at the primary career stage (i.e., GPA in preservice education) and the potential process that underlies this association is still not fully understood. This study explored the professional identity of Chinese preservice teachers, and its links with task value belief, intrinsic learning motivation, extrinsic learning motivation, and performance in the education program. Grade-point average (GPA) of courses (both subject and pedagogy courses) was examined as an indicator of performance, and questionnaires were used to measure the remaining variables. Data from 606 preservice teachers in the first 3 years of a teacher-training program indicated that: (1) variables in this research were all significantly correlated with each other, except the correlation between intrinsic learning motivation and program performance; (2) professional identity was positively linked to task value belief, intrinsic and extrinsic learning motivations, and program performance in a structural equation model (SEM); (3) task value belief was positively linked to intrinsic and extrinsic learning motivation; (4) higher extrinsic (but not intrinsic) learning motivation was associated with increased program performance; and (5) task value belief and extrinsic learning motivation were significant mediators in the model.
Zhang, Yan; Hawk, Skyler T.; Zhang, Xiaohui; Zhao, Hongyu
Professional identity is a key issue spanning the entirety of teachers’ career development. Despite the abundance of existing research examining professional identity, its link with occupation-related behavior at the primary career stage (i.e., GPA in preservice education) and the potential process that underlies this association is still not fully understood. This study explored the professional identity of Chinese preservice teachers, and its links with task value belief, intrinsic learning motivation, extrinsic learning motivation, and performance in the education program. Grade-point average (GPA) of courses (both subject and pedagogy courses) was examined as an indicator of performance, and questionnaires were used to measure the remaining variables. Data from 606 preservice teachers in the first 3 years of a teacher-training program indicated that: (1) variables in this research were all significantly correlated with each other, except the correlation between intrinsic learning motivation and program performance; (2) professional identity was positively linked to task value belief, intrinsic and extrinsic learning motivations, and program performance in a structural equation model (SEM); (3) task value belief was positively linked to intrinsic and extrinsic learning motivation; (4) higher extrinsic (but not intrinsic) learning motivation was associated with increased program performance; and (5) task value belief and extrinsic learning motivation were significant mediators in the model. PMID:27199810
Full Text Available High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy.
Pärnamaa, Tanel; Parts, Leopold
High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy. Copyright © 2017 Parnamaa and Parts.
Bastani, Meysam; Vos, Larissa; Asgarian, Nasimeh; Deschenes, Jean; Graham, Kathryn; Mackey, John; Greiner, Russell
Background Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER) status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. Methods To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. Results This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. Conclusions Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions. PMID:24312637
Full Text Available BACKGROUND: Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. METHODS: To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. RESULTS: This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. CONCLUSIONS: Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions.
Iftikhar Ahmad; Muhammad Sabboor Hussain; Noor Raha Mohd Radzuan
The study tends to explore the possible reforms to raise the proficiency level of the adult English as Foreign Language (EFL) learners. With this end in view, it investigates non-native EFL teachers’ beliefs in relation to adult learners’ beliefs in teaching grammar to university students in the Saudi Arabian EFL context. It finds out the harmony and disharmony between the teachers at the giving end and the taught at the receiving end to create a culture of awareness and to build a better tea...
Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; Lilienfeld, O. Anatole von; Müller, Klaus-Robert; Tkatchenko, Alexandre
Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the 'holy grail' of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies
How are learning physics and student beliefs about learning physics connected? Measuring epistemological self-reflection in an introductory course and investigating its relationship to conceptual learning
May, David B.
To explore students' epistemological beliefs in a variety of conceptual domains in physics, and in a specific and novel context of measurement, this Dissertation makes use of Weekly Reports, a class assignment in which students reflect in writing on what they learn each week and how they learn it. Reports were assigned to students in the introductory physics course for honors engineering majors at The Ohio State University in two successive years. The Weekly Reports of several students from the first year were analyzed for the kinds of epistemological beliefs exhibited therein, called epistemological self-reflection, and a coding scheme was developed for categorizing and quantifying this reflection. The connection between epistemological self-reflection and conceptual learning in physics seen in a pilot study was replicated in a larger study, in which the coded reflections from the Weekly Reports of thirty students were correlated with their conceptual learning gains. Although the total amount of epistemological self-reflection was not found to be related to conceptual gain, different kinds of epistemological self-reflection were. Describing learning physics concepts in terms of logical reasoning and making personal connections were positively correlated with gains; describing learning from authority figures or by observing phenomena without making inferences were negatively correlated. Linear regression equations were determined in order to quantify the effects on conceptual gain of specific ways of describing learning. In an experimental test of this model, the regression equations and the Weekly Report coding scheme developed from the first year's data were used to predict the conceptual gains of thirty students from the second year. The prediction was unsuccessful, possibly because these students were not given as much feedback on their reflections as were the first-year students. These results show that epistemological beliefs are important factors affecting
Geller, Jason; Toftness, Alexander R; Armstrong, Patrick I; Carpenter, Shana K; Manz, Carly L; Coffman, Clark R; Lamm, Monica H
Prior research by Hartwig and Dunlosky [(2012). Study strategies of college students: Are self-testing and scheduling related to achievement? Psychonomic Bulletin & Review, 19(1), 126-134] has demonstrated that beliefs about learning and study strategies endorsed by students are related to academic achievement: higher performing students tend to choose more effective study strategies and are more aware of the benefits of self-testing. We examined whether students' achievement goals, independent of academic achievement, predicted beliefs about learning and endorsement of study strategies. We administered Hartwig and Dunlosky's survey, along with the Achievement Goals Questionnaire [Elliot, A. J., & McGregor, H. A. (2001). A 2 × 2 achievement goal framework. Journal of Personality & Social Psychology, 80, 501-519] to a large undergraduate biology course. Similar to results by Hartwig and Dunlosky, we found that high-performing students (relative to low-performing students) were more likely to endorse self-testing, less likely to cram, and more likely to plan a study schedule ahead of time. Independent of achievement, however, achievement goals were stronger predictors of certain study behaviours. In particular, avoidance goals (e.g., fear of failure) coincided with increased use of cramming and the tendency to be driven by impending deadlines. Results suggest that individual differences in student achievement, as well as the underlying reasons for achievement, are important predictors of students' approaches to studying.
Full Text Available This article analyzes relations between self-regulated learning, self-efficacy beliefs, and performance in tasks of solving arithmetic problems. The research includes 268 six-year-old students enrolled in the first year of primary school in Spain. The results from binary logistic regression models indicate that self-regulated learning and its interaction with self-efficacy beliefs predict performance. Finally, the cluster analysis shows four profiles of students: i positive adjusted; ii negative unadjusted I; iii negative unadjusted II y; iv negative adjusted.. Este artículo analiza relaciones entre el aprendizaje autorregulado, las creencias de autoeficacia y el desempeño en tareas de resolución de problemas aritméticos. El estudio se ha llevado a cabo con 268 escolares de seis años de edad y matriculados en el primer año de educación primaria en España. Los resultados obtenidos mediante modelos de regresión logística binaria indican que el aprendizaje autorregulado y su interacción con las creencias de autoeficacia predicen el desempeño. Por último, la aplicación de un análisis Cluster muestra cuatro perfiles de escolares, denominados: i ajustado positivo; ii desajustado negativo I; iii desajustado negativo II y; iv ajustado negativo.
Ho, Hsin-Ning Jessie; Liang, Jyh-Chong
This study explores the relationships among Taiwanese high school students' scientific epistemic beliefs (SEBs), conceptions of learning science (COLS), and motivation of learning science. The questionnaire responses from 470 high school students in Taiwan were gathered for analysis to explain these relationships. The structural equation modeling…
Cecilia Titiek Murniati
Full Text Available Recent studies have suggested that teachers beliefs have a significant influence on actual classroom practice and, consequently, on students achievements. However, little research has been done to investigate the influence of Indonesian language policy and teachers beliefs. The study reported seeks to examine the influence of English language policy on pre-service teacher's beliefs about the teaching of English language grammar in Indonesian schools. The research participants were pre-service teachers who have taken the subjects of Structure, Teaching Methods, and Micro-teaching in three public and private universities in Central Java and Yogyakarta Special District. Due to time and scheduling limitations, the sampling method used in this study was convenient sampling. Documentation, survey schedules, interviews, focus group discussions were used to gather the data. The findings revealed that although the language policy in Indonesia has put English language teaching and learning within the framework of communicative competence since the enactment of the 2006 School-based Curriculum, the pre-service teachers still believed that traditional method of teaching grammar (explicit grammar instruction was imperative to use. The pre-service teachers tended to exclude English language policy enacted by Indonesian government in their discussion about teachers beliefs. Instead, the pre-service teachers constructed their beliefs about English language grammar teaching and learning process on their prior experiences in learning and teaching grammar.
This study aimed to contribute to the growing literature on learning approaches and teacher self-efficacy beliefs by examining associations between prospective elementary school teachers' learning approaches in a social studies teaching methods course and their social studies teaching efficacy beliefs. One hundred ninety-two prospective elementary…
Hsu, Chung-Yuan; Tsai, Meng-Jung; Chang, Yu-Hsuan; Liang, Jyh-Chong
Using the Game-based-learning Teaching Belief Scale (GTBS) and the Technological Pedagogical Content Knowledge--Games questionnaire (TPACK-G), this study investigated 316 Taiwanese in-service teachers' teaching beliefs about game-based learning and their perceptions of game-based pedagogical content knowledge (GPCK). Both t-tests and ANOVA…
Zuckerman, Katharine E.; Lindly, Olivia J.; Sinche, Brianna
This study aimed to assess variation in parent beliefs about causes of learning and developmental problems in U.S. children with autism spectrum disorder, using data from a nationally representative survey. Results showed that beliefs about a genetic/hereditary cause of learning/developmental problems were most common, but nearly as many parents…
Kingir, Sevgi; Tas, Yasemin; Gok, Gulsum; Sungur Vural, Semra
Background. There are attempts to integrate learning environment research with motivation and self-regulation research that considers social context influences an individual's motivation, self-regulation and, in turn, academic performance. Purpose. This study explored the relationships among constructivist learning environment perception variables (personal relevance, uncertainty, shared control, critical voice, student negotiation), motivational beliefs (self-efficacy, intrinsic interest, goal orientation), self-regulation, and science achievement. Sample. The sample for this study comprised 802 Grade 8 students from 14 public middle schools in a district of Ankara in Turkey. Design and methods. Students were administered 4 instruments: Constructivist Learning Environment Survey, Goal Achievement Questionnaire, Motivated Strategies for Learning Questionnaire, and Science Achievement Test. LISREL 8.7 program with SIMPLIS programming language was used to test the conceptual model. Providing appropriate fit indices for the proposed model, the standardized path coefficients for direct effects were examined. Results. At least one dimension of the constructivist learning environment was associated with students' intrinsic interest, goal orientation, self-efficacy, self-regulation, and science achievement. Self-efficacy emerged as the strongest predictor of both mastery and performance avoidance goals rather than the approach goals. Intrinsic value was found to be significantly linked to science achievement through its effect on self-regulation. The relationships between self-efficacy and self-regulation and between goal orientation and science achievement were not significant. Conclusion. In a classroom environment supporting student autonomy and control, students tend to develop higher interest in tasks, use more self-regulatory strategies, and demonstrate higher academic performance. Science teachers are highly recommended to consider these findings when designing
Clark, Alex M; Bunin, Barry A; Litterman, Nadia K; Schürer, Stephan C; Visser, Ubbo
Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO) project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers.
Alex M. Clark
Full Text Available Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers.
Mcnaughton, Susan; Barrow, Mark; Bagg, Warwick; Frielick, Stanley
Practice-based learning integrates the cognitive, psychomotor, and affective domains and is influenced by students' beliefs, values, and attitudes. Concept mapping has been shown to effectively demonstrate students' changing concepts and knowledge structures. This article discusses how concept mapping was modified to capture students' perceptions of the connections between the domains of thinking and knowing, emotions, behavior, attitudes, values, and beliefs and the specific experiences related to these, over a period of eight months of practice-based clinical learning. The findings demonstrate that while some limitations exist, modified concept mapping is a manageable way to gather rich data about students' perceptions of their clinical practice experiences. These findings also highlight the strong integrating influence of beliefs and values on other areas of practice, suggesting that these need to be attended to as part of a student's educational program.
Bråten, Ivar; Strømsø, Helge I
More empirical work is needed to examine the dimensionality of personal epistemology and relations between those dimensions and motivational and strategic components of self-regulated learning. In particular, there is great need to investigate personal epistemology and its relation to self-regulated learning across cultures and academic contexts. Because the demarcation between personal epistemology and implicit theories of intelligence has been questioned, dimensions of personal epistemology should also be studied in relation to implicit theories of intelligence. The primary aim was to examine the dimensionality of personal epistemology and the relation between those dimensions and implicit theories of intelligence in the cultural context of Norwegian postsecondary education. A secondary aim was to examine the relative contribution of epistemological beliefs and theories of intelligence to motivational and strategic components of self-regulated learning in different academic contexts within that culture. The first sample included 178 business administration students in a traditional transmission-oriented instructional context; the second, 108 student teachers in an innovative pedagogical context. The dimensionality of the Schommer Epistemological Questionnaire was examined through factor analyses, and the resulting dimensions were examined in relation to implicit theories of intelligence. We performed multiple regression analyses, separately for the two academic contexts, to try to predict motivational (i.e. self-efficacy beliefs, mastery goal orientation, and interest) and strategic (i.e. self-regulatory strategy use) components of self-regulated learning with epistemological beliefs and implicit theories of intelligence. Considerable cross-cultural generalizability was found for the dimensionality of personal epistemology. Moreover, the dimensions of personal epistemology seemed to represent constructs separate from the construct of implicit theories of
Battistin, C; Roudi, Y; Hertz, J; Tyrcha, J
We propose a new algorithm for inferring the state of hidden spins and reconstructing the connections in a synchronous kinetic Ising model, given the observed history. Focusing on the case in which the hidden spins are conditionally independent of each other given the state of observable spins, we show that calculating the likelihood of the data can be simplified by introducing a set of replicated auxiliary spins. Belief propagation (BP) and susceptibility propagation (SusP) can then be used to infer the states of hidden variables and to learn the couplings. We study the convergence and performance of this algorithm for networks with both Gaussian-distributed and binary bonds. We also study how the algorithm behaves as the fraction of hidden nodes and the amount of data are changed, showing that it outperforms the Thouless–Anderson–Palmer (TAP) equations for reconstructing the connections. (paper)
Díaz Larenas Claudio
Full Text Available Beliefs continue to be an important source to get to know teachers’ thinking processes and pedagogical decisions. Research in teachers’ beliefs has traditionally come from English-speaking contexts; however, a great deal of scientific work has been written lately in Brazil, Mexico, Colombia, and Argentina. This study elicits 30 Chilean university teachers’ beliefs about their own role in the teaching and learning of English in university environments. Through a qualitative research design, the data collected from interviews and journals were analyzed, triangulated, and categorized based on semantic content analysis. Results of the study indicate that university teachers reveal challenging and complex views about what it is like to teach English as a foreign language in a university context in Chile. The article concludes with a call to reflect on the importance of beliefs unravelling in teacher education programmes.Las creencias continúan siendo una fuente de importancia para conocer los procesos de pensamiento y los estilos pedagógicos de los docentes. Los estudios sobre las creencias docentes provienen en su mayoría de contextos angloparlantes; sin embargo, en los últimos años se ha escrito una gran cantidad de trabajos científicos en Brasil, México, Colombia y Argentina. Este estudio recoge las creencias de treinta docentes universitarios chilenos sobre su papel en la enseñanza y aprendizaje del inglés en ambientes universitarios. A partir de un diseño de investigación cualitativo, los datos recolectados por medio de entrevistas y diarios personales fueron analizados, triangulados y categorizados según el análisis de contenido semántico. Los resultados indicaron que los docentes de educación superior tienen visiones desafiantes y complejas sobre lo que significa enseñar inglés como lengua extranjera en un contexto universitario en Chile. El artículo concluye con una invitación a reflexionar sobre la importancia de
Bilgin, Ibrahim; Karakuyu, Yunus; Ay, Yusuf
The purpose of this study is to investigate the effects of the Project-Based Learning (PBL) method on undergraduate students' achievement and its association with these students' self-efficacy beliefs about science teaching and pinions about PBL. The sample of the study consisted of two randomly chosen classes from a set of seven classes enrolled…
Fadlelmula, Fatma Kayan; Cakiroglu, Erdinc; Sungur, Semra
This study examines the interrelationships among students' motivational beliefs (i.e. achievement goal orientations, perception of classroom goal structure, and self-efficacy), use of self-regulated learning strategies (i.e. elaboration, organization, and metacognitive self-regulation strategies), and achievement in mathematics, by proposing and…
Agaç, Gülay; MASAL, Ercan
Related literature emphasizes that affective factors are impactful on cognitive factors. For this reason, this study aims at revealing the relationship between problem solving, which is one of metacognitive characteristics, beliefs about mathematics and learned hopelessness, which are two affective characteristics. Therefore, addressing emotional aspects together with cognitive abilities will give rise to understanding of the students’ current situation and predicting ab...
O'Neal, LaToya J.; Gibson, Philip; Cotten, Shelia R.
Technological advancements have led to changes in the expectations placed on K-12 teachers. Teachers are now expected to better equip students with 21st-century skills, making it important to understand teachers' beliefs about the role of technology in teaching and learning and the skills their students need to be successful. Using a qualitative…
Lin, Tzung-Jin; Deng, Feng; Chai, Ching Sing; Tsai, Chin-Chung
This study explored the differences in high school students' scientific epistemological beliefs (SEBs), motivation in learning science (MLS), and the different relationships between them in Taiwan and China. 310 Taiwanese and 302 Chinese high school students' SEBs and MLS were assessed quantitatively. Taiwanese students generally were more prone…
Ariani, Mohsen Ghasemi; Ghafournia, Narjes
This study explored the probable interaction between Iranian language students' beliefs about language learning and their socio-economic status. To this end, 350 postgraduate students, doing English courses at Islamic Azad University of Neyshabur participated in this study. They were grouped in terms of their socio-economic status. They answered a…
In efforts to encourage use of natural outdoor settings as learning environments within early childhood education, survey research was conducted with 46 early childhood educators from northern Minnesota (United States) to explore their beliefs and practices regarding natural outdoor settings, as well investigate predictors of and barriers to the…
Al-Samarraie, Hosam; Selim, Hassan; Zaqout, Fahed
A model is proposed to assess the effect of different content representation design principles on learners' intuitive beliefs about using e-learning. We hypothesized that the impact of the representation of course contents is mediated by the design principles of alignment, quantity, clarity, simplicity, and affordance, which influence the…
Ucar, Hasan; Yazici Bozkaya, Mujgan
This study examined the pre-service EFL teachers' self-efficacy beliefs, goal orientations, and participations in an online learning environment. Embedded mixed design was used in the study. In the quantitative part of the study, the participants were 186 senior pre-service EFL teachers and data were collected on two scales and a questionnaire.…
This study investigated parents' backgrounds and their beliefs about English language learning, and compared the receptive English vocabulary development of three to six year-old-Thai children before and after participating in a parent-child reading program with the dialogic reading (DR) method. Fifty-four single parents of 54 children voluntarily…
This article presents the results of a study on the language learning and teaching beliefs of graduate students enrolled in an applied linguistics course in a language teaching program. Ten participants completed a questionnaire at the start of the course and another at the end; their responses were analyzed both quantitatively and qualitatively.…
Ocak, Gurbuz; Yamac, Ahmet
The aim of current study was to examine predictor and explanatory relationships between fifth graders' self-regulated learning strategies, motivational beliefs, attitudes towards mathematics, and academic achievement. The study was conducted on a sample of 204 students studying in the primary schools of Afyonkarahisar province. Motivated…
The purpose of this study is to investigate the influence of the web-aided cooperative learning environment on biology preservice teachers' motivation and on their self-efficacy beliefs in biology teaching. The study was carried out with 30 biology preservice teachers attending a state university in Turkey. In the study, the pretest-posttest…
Cota Grijalva Sofía D.
Full Text Available This paper contains the description of a research project that was carried out in the Bachelor of Arts in English Language Teaching program at a Mexican university. The study was longitudinal and it tracked fourteen students for four semesters of the eight semester program. The aim was to identify pre-service teachers’ beliefs about English language teaching and learning at different stages of instruction while they were taking the teaching practice courses in the program. The instruments employed were questionnaires and semi-structured interviews. The results demonstrated that students made links between theory and practice creating some changes in previous beliefs. The study revealed an increase of awareness and a better understanding of the complex processes involved in teaching and learning. En este artículo se describe una investigación que se llevó a cabo en el programa de Licenciatura en Enseñanza del Inglés de una universidad mexicana. El estudio fue longitudinal, el cual siguió la trayectoria de catorce estudiantes de la licenciatura durante cuatro de los ocho semestres del programa académico. El propósito fue identificar las creencias de estos maestros principiantes, quienes cursabansus clases de práctica docente del programa, acerca de la enseñanza y el aprendizaje del inglés en diferentes etapas de sus estudios. Los instrumentos utilizados fueron cuestionarios y entrevistas semiestructuradas. Los resultados demostraron que los estudiantes articularon la teoría con la práctica, lo cual incidió en sus creencias anteriores. El estudio también reveló que comprendieron mejor los complejos procesos involucrados en la enseñanza y el aprendizaje.
Full Text Available Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analysed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given.
He, Fei; Han, Ye; Wang, Han; Ji, Jinchao; Liu, Yuanning; Ma, Zhiqiang
Gabor filters are widely utilized to detect iris texture information in several state-of-the-art iris recognition systems. However, the proper Gabor kernels and the generative pattern of iris Gabor features need to be predetermined in application. The traditional empirical Gabor filters and shallow iris encoding ways are incapable of dealing with such complex variations in iris imaging including illumination, aging, deformation, and device variations. Thereby, an adaptive Gabor filter selection strategy and deep learning architecture are presented. We first employ particle swarm optimization approach and its binary version to define a set of data-driven Gabor kernels for fitting the most informative filtering bands, and then capture complex pattern from the optimal Gabor filtered coefficients by a trained deep belief network. A succession of comparative experiments validate that our optimal Gabor filters may produce more distinctive Gabor coefficients and our iris deep representations be more robust and stable than traditional iris Gabor codes. Furthermore, the depth and scales of the deep learning architecture are also discussed.
There is widespread agreement that the potential of gene therapy was oversold in the early 1990s. This study, however, comparing written material from the British, Danish and German gene therapy discourses of the period finds significant differences: Over-optimism was not equally strong everywhere; gene therapy was not universally hyped. Against that background, attention is directed towards another area of variation in the material: different basic assumptions about science and scientists. Exploring such culturally rooted assumptions and beliefs and their possible significance to science communication practices, it is argued that deep beliefs may constitute drivers of hype that are particularly difficult to deal with. To participants in science communication, the discouragement of hype, viewed as a practical-ethical challenge, can be seen as a learning exercise that includes critical attention to internalised beliefs. © The Author(s) 2014.
Teaching outdoors has been established as an important pedagogical strategy; however, science classes rarely take place outside. Previous research has identified characteristics of teachers who have integrated out-of-classroom opportunities into their teaching repertoire; yet little is understood as to why teachers make these different pedagogical decisions. This paper explores the relationship between secondary science teachers' beliefs and their pedagogical practice during a two-year professional development programme associated with the 'Thinking Beyond the Classroom' project. Using data from lesson observations, interviews, session questionnaires and field notes, six teacher case studies were developed from participants completing the programme. Data analysis reveals that teachers who successfully taught outside generally held social constructivist beliefs about learning and valued 'authentic' science opportunities. Conversely, teachers who were less successful in teaching outside generally held traditional learning beliefs and simply valued the outdoors for the novelty and potential for fun. All the case study teachers were concerned about managing student learning outside, and for the majority, their concerns influenced their subsequent pedagogical practice. The findings are discussed in detail, as are the implications for pre-service and in-service professional development programmes related to outdoor science learning.
Pepin, B.; Hudson, B.; Buchberger, F.; Kansanen, P.
This paper firstly explores the issues raised in the literature concerning epistemologies, beliefs and conceptions of mathematics and its teaching and learning. Secondly, it analyses the ways in which mathematics teachers’ classroom practices in England, France and Germany reflect teachers’ beliefs
Kao, Chia-Pin; Wu, Ying-Tien; Tsai, Chin-Chung
This study was conducted to explore the relationships between teachers' motivation toward web-based professional development, Internet self-efficacy, and beliefs about web-based learning. By gathering questionnaire data from 484 elementary school teachers, this study indicated that the teachers' Internet self-efficacy and behavioral beliefs about…
Wang, Cheng-Lung; Liou, Pey-Yan
The purpose of this study was to examine the pattern of the relationships among motivational beliefs and science achievement of 8th grade Taiwanese students, given that the students in Taiwan have high science academic achievement but low motivational beliefs in science learning on a series of international large-scale assessments. Three…
Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X
Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.
Ying, Jun; Dutta, Joyita; Guo, Ning; Hu, Chenhui; Zhou, Dan; Sitek, Arkadiusz; Li, Quanzheng
This study aims to develop an automatic classifier based on deep learning for exacerbation frequency in patients with chronic obstructive pulmonary disease (COPD). A threelayer deep belief network (DBN) with two hidden layers and one visible layer was employed to develop classification models and the models' robustness to exacerbation was analyzed. Subjects from the COPDGene cohort were labeled with exacerbation frequency, defined as the number of exacerbation events per year. 10,300 subjects with 361 features each were included in the analysis. After feature selection and parameter optimization, the proposed classification method achieved an accuracy of 91.99%, using a 10-fold cross validation experiment. The analysis of DBN weights showed that there was a good visual spatial relationship between the underlying critical features of different layers. Our findings show that the most sensitive features obtained from the DBN weights are consistent with the consensus showed by clinical rules and standards for COPD diagnostics. We thus demonstrate that DBN is a competitive tool for exacerbation risk assessment for patients suffering from COPD.
Zhang, Yan; Hawk, Skyler T.; Zhang, Xiaohui; Zhao, Hongyu
Professional identity is a key issue spanning the entirety of teachers’ career development. Despite the abundance of existing research examining professional identity, its link with occupation-related behavior at the primary career stage (i.e., GPA in preservice education) and the potential process that underlies this association is still not fully understood. This study explored the professional identity of Chinese preservice teachers, and its links with task value belief, intrinsic learning...
Serag, Ahmed; Blesa, Manuel; Moore, Emma J; Pataky, Rozalia; Sparrow, Sarah A; Wilkinson, A G; Macnaught, Gillian; Semple, Scott I; Boardman, James P
Accurate whole-brain segmentation, or brain extraction, of magnetic resonance imaging (MRI) is a critical first step in most neuroimage analysis pipelines. The majority of brain extraction algorithms have been developed and evaluated for adult data and their validity for neonatal brain extraction, which presents age-specific challenges for this task, has not been established. We developed a novel method for brain extraction of multi-modal neonatal brain MR images, named ALFA (Accurate Learning with Few Atlases). The method uses a new sparsity-based atlas selection strategy that requires a very limited number of atlases 'uniformly' distributed in the low-dimensional data space, combined with a machine learning based label fusion technique. The performance of the method for brain extraction from multi-modal data of 50 newborns is evaluated and compared with results obtained using eleven publicly available brain extraction methods. ALFA outperformed the eleven compared methods providing robust and accurate brain extraction results across different modalities. As ALFA can learn from partially labelled datasets, it can be used to segment large-scale datasets efficiently. ALFA could also be applied to other imaging modalities and other stages across the life course.
Seeberg, Henrik Bech; Slothuus, Rune; Stubager, Rune
A premise of the mass–elite linkage at the heart of representative democracy is that voters notice changes in political parties’ policy positions and update their party perceptions accordingly. However, recent studies question the ability of voters accurately to perceive changes in parties...... attention to parties when they visibly change policy position. Second, voters update their perceptions of the party positions much more accurately than would have been expected if they merely relied on a ‘coalition heuristic’ as a rule-of-thumb. These findings imply that under some conditions voters...
Schwieler, Elias; Ekecrantz, Stefan
The effects of teachers' normative values and emotive reactions on teaching in higher education have received relatively little research attention. The focus is often on descriptive beliefs such as conceptions of teaching and their inter-relations with practice. In this study, which is illustrated by a heuristic model, a belief system approach is…
Watson, Joshua C.
This study examined the relationship between enrollment in online counseling courses and students' counseling selfefficacy beliefs. Results indicate that students enrolled in online courses report statistically significant higher selfefficacy beliefs than students in traditional FTF courses. Online instructional method may increase counselor…
Luo, Wenshu; Lee, Kerry; Ng, Pak Tee; Ong, Joanne Xiao Wei
This study investigated the relationships of students' incremental beliefs of math ability to their achievement emotions, classroom engagement and math achievement. A sample of 273 secondary students in Singapore were administered measures of incremental beliefs of math ability, math enjoyment, pride, boredom and anxiety, as well as math classroom…
Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N
In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.
Ghazal Motazed Keyvani
Full Text Available Background Nowadays, one of the principal difficulties faced by educational systems worldwide is anxiety, a mental problem, which is evidently difficult to be endured by many students and leads to various types of mental and physical disorders or reduction of educational efficiency, and has gained attention of sociologists for its consequent psychological, social, and economical impacts. Objectives The current study aimed at predicting exam anxiety based on meta-cognitive beliefs and learning methods among high school students of Bandar Abbas. Methods The study population included 351 students (197 males and 154 females, who were selected randomly by the cluster approach and answered the research tools including Meta-Cognitive Beliefs Questionnaires (MCQ-30, Learning methods questionnaires of Marton and Saljoo (1996 and also test anxiety questionnaire of Alpert and Haber (1960. The study plan was correlative-descriptive. Pearson simple correlation coefficient, multi variable regression, and multi variable variance analysis were used to analyze the obtained data. Results The study results indicated that there was a positive significant relationship between meta-cognitive beliefs and exam anxiety, a negative significant relationship between profound learning and learning methods and exam anxiety, and a positive significant relationship between smattering learning method and exam anxiety. The regression exam results also revealed that meta-cognitive beliefs and smattering learning methods could positively predict and determine exam anxiety in students. A significant relationship was observed between meta-cognitive beliefs in females and males, and female students showed greater intention and interest toward meta-cognitive beliefs than males, however, no significant difference was observed between learning methods and exam anxiety in females and males. Conclusions It was concluded from the study results that profound learning methods lead to the
Aakerberg, Andreas; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund
of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...
Rouhani, Modjtaba; Javan, Dawood S
This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher efficiency is achieved by fewer numbers of neurons, while the learning algorithm remains fast and simple. To retain network size limited, neurons are added to network recursively until termination condition is met. Each neuron covers some of train data. The termination condition is to cover all training data or to reach the maximum number of neurons. In each step, the center and spread of the new neuron are selected based on maximization of its coverage. Maximization of coverage of the neurons leads to a network with fewer neurons and indeed lower VC dimension and better generalization property. Using power exponential distribution function as the activation function of hidden neurons, and in the light of new learning approaches, it is proved that all data became linearly separable in the space of hidden layer outputs which implies that there exist linear output layer weights with zero training error. The proposed methods are applied to some well-known datasets and the simulation results, compared with SVM and some other leading RBF learning methods, show their satisfactory and comparable performance. Copyright © 2015 Elsevier Ltd. All rights reserved.
Zhao, Xiaowei; Ning, Qiao; Chai, Haiting; Ma, Zhiqiang
As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimental approaches, computational predictions of succinylation sites are much desirable due to their convenient and fast speed. Currently, numerous computational models have been developed to identify PTMs sites through various types of two-class machine learning algorithms. These methods require both positive and negative samples for training. However, designation of the negative samples of PTMs was difficult and if it is not properly done can affect the performance of computational models dramatically. So that in this work, we implemented the first application of positive samples only learning (PSoL) algorithm to succinylation sites prediction problem, which was a special class of semi-supervised machine learning that used positive samples and unlabeled samples to train the model. Meanwhile, we proposed a novel succinylation sites computational predictor called SucPred (succinylation site predictor) by using multiple feature encoding schemes. Promising results were obtained by the SucPred predictor with an accuracy of 88.65% using 5-fold cross validation on the training dataset and an accuracy of 84.40% on the independent testing dataset, which demonstrated that the positive samples only learning algorithm presented here was particularly useful for identification of protein succinylation sites. Besides, the positive samples only learning algorithm can be applied to build predictors for other types of PTMs sites with ease. A web server for predicting succinylation sites was developed and was freely accessible at http://22.214.171.124:8088/SucPred/. Copyright © 2015 Elsevier Ltd. All rights reserved.
Sun, Baozhou; Lam, Dao; Yang, Deshan; Grantham, Kevin; Zhang, Tiezhi; Mutic, Sasa; Zhao, Tianyu
Clinical treatment planning systems for proton therapy currently do not calculate monitor units (MUs) in passive scatter proton therapy due to the complexity of the beam delivery systems. Physical phantom measurements are commonly employed to determine the field-specific output factors (OFs) but are often subject to limited machine time, measurement uncertainties and intensive labor. In this study, a machine learning-based approach was developed to predict output (cGy/MU) and derive MUs, incorporating the dependencies on gantry angle and field size for a single-room proton therapy system. The goal of this study was to develop a secondary check tool for OF measurements and eventually eliminate patient-specific OF measurements. The OFs of 1754 fields previously measured in a water phantom with calibrated ionization chambers and electrometers for patient-specific fields with various range and modulation width combinations for 23 options were included in this study. The training data sets for machine learning models in three different methods (Random Forest, XGBoost and Cubist) included 1431 (~81%) OFs. Ten-fold cross-validation was used to prevent "overfitting" and to validate each model. The remaining 323 (~19%) OFs were used to test the trained models. The difference between the measured and predicted values from machine learning models was analyzed. Model prediction accuracy was also compared with that of the semi-empirical model developed by Kooy (Phys. Med. Biol. 50, 2005). Additionally, gantry angle dependence of OFs was measured for three groups of options categorized on the selection of the second scatters. Field size dependence of OFs was investigated for the measurements with and without patient-specific apertures. All three machine learning methods showed higher accuracy than the semi-empirical model which shows considerably large discrepancy of up to 7.7% for the treatment fields with full range and full modulation width. The Cubist-based solution
Sato, Jo?o R.; Moll, Jorge; Green, Sophie; Deakin, John F.W.; Thomaz, Carlos E.; Zahn, Roland
Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to address this question. Using a recently identified neural signature of guilt-selective functional disconnection, the classification algorithm was able to distinguish remitted MD from control participants with 78.3% accuracy. This demonstrates the hi...
Spiva, LeeAnna; Johnson, Kimberly; Robertson, Bethany; Barrett, Darcy T; Jarrell, Nicole M; Hunter, Donna; Mendoza, Inocencia
Historically, the instructional method of choice has been traditional lecture or face-to-face education; however, changes in the health care environment, including resource constraints, have necessitated examination of this practice. A descriptive pre-/posttest method was used to determine the effectiveness of alternative teaching modalities on nurses' knowledge and confidence in electrocardiogram (EKG) interpretation. A convenience sample of 135 nurses was recruited in an integrated health care system in the Southeastern United States. Nurses attended an instructor-led course, an online learning (e-learning) platform with no study time or 1 week of study time, or an e-learning platform coupled with a 2-hour post-course instructor-facilitated debriefing with no study time or 1 week of study time. Instruments included a confidence scale, an online EKG test, and a course evaluation. Statistically significant differences in knowledge and confidence were found for individual groups after nurses participated in the intervention. Statistically significant differences were found in pre-knowledge and post-confidence when groups were compared. Organizations that use various instructional methods to educate nurses in EKG interpretation can use different teaching modalities without negatively affecting nurses' knowledge or confidence in this skill. Copyright 2012, SLACK Incorporated.
Sato, João R; Moll, Jorge; Green, Sophie; Deakin, John F W; Thomaz, Carlos E; Zahn, Roland
Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to address this question. Using a recently identified neural signature of guilt-selective functional disconnection, the classification algorithm was able to distinguish remitted MD from control participants with 78.3% accuracy. This demonstrates the high potential of our fMRI signature as a biomarker of MD vulnerability. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.
Heitmann, Patricia; Hecht, Martin; Scherer, Ronny; Schwanewedel, Julia
Argumentation is considered crucial in numerous disciplines in schools and universities because it constitutes an important proficiency in peoples' daily and professional lives. However, it is unclear whether argumentation is understood and practiced in comparable ways across disciplines. This study consequently examined empirically how students perceive argumentation in science and (first) language lessons. Specifically, we investigated students' beliefs about the relevance of discourse and the role of facts. Data from 3,258 high school students from 85 German secondary schools were analyzed with multigroup multilevel structural equation modeling in order to disentangle whether or not differences in argumentation across disciplines exist and the extent to which variation in students' beliefs can be explained by gender and school track. Results showed that students perceived the role of facts as highly relevant for science lessons, whereas discursive characteristics were considered significantly less important. In turn, discourse played a central role in language lessons, which was believed to require less knowledge of facts. These differences were independent of students' gender. In contrast, school track predicted the differences in beliefs significantly. Our findings lend evidence on the existence of disciplinary school cultures in argumentation that may be the result of differences in teachers' school-track-specific classroom practice and education. Implications in terms of a teacher's role in establishing norms for scientific argumentation as well as the impact of students' beliefs on their learning outcomes are discussed. PMID:28642727
Roya Nayebi Limoodehi
Full Text Available The purpose of the present study was to determine the relationship between five dimensions of the epistemological beliefs regarding structure of knowledge, stability of knowledge, source of knowledge, ability to learn and, speed of learning and six measures of the motivational components of self-regulated learning strategies (intrinsic goal orientation, extrinsic goal orientation, task value, self-efficacy, control of learning, and test anxiety among male and female EFL learners across years of study (freshman and sophomore students. The participants of this study were 101 EFL students studying English literature and English translation in the Islamic Azad University, Rasht Branch, Iran, during the spring semester of 2013. The participants completed Persian version of Motivated Strategies for Learning Questionnaire (MSLQ (Pintrich, Smith, Garcia & McKeachie, 1991 and Persian version of Epistemological Questionnaire (Schommer, 1990. Results showed that, in general, the more naïve the epistemological beliefs of students, the less likely they are to use motivational learning strategies. Moreover, there was no significant relationship between dimensions of epistemological beliefs and motivational components of self-regulated learning strategies among male and female students. On the other hand, a statistically significant relationship was found between dimensions of epistemological beliefs and motivational components of self-regulated learning strategies for both freshman and sophomore students.
Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting
Image segmentation plays an important role in medical science. One application is multimodality imaging, especially the fusion of structural imaging with functional imaging, which includes CT, MRI and new types of imaging technology such as optical imaging to obtain functional images. The fusion process require precisely extracted structural information, in order to register the image to it. Here we used image enhancement, morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in deep learning way. Such approach greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. The contours of the borders of different tissues on all images were accurately extracted and 3D visualized. This can be used in low-level light therapy and optical simulation software such as MCVM. We obtained a precise three-dimensional distribution of brain, which offered doctors and researchers quantitative volume data and detailed morphological characterization for personal precise medicine of Cerebral atrophy/expansion. We hope this technique can bring convenience to visualization medical and personalized medicine.
Full Text Available Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases.
Gala, Rohan; Chapeton, Julio; Jitesh, Jayant; Bhavsar, Chintan; Stepanyants, Armen
Automating the process of neurite tracing from light microscopy stacks of images is essential for large-scale or high-throughput quantitative studies of neural circuits. While the general layout of labeled neurites can be captured by many automated tracing algorithms, it is often not possible to differentiate reliably between the processes belonging to different cells. The reason is that some neurites in the stack may appear broken due to imperfect labeling, while others may appear fused due to the limited resolution of optical microscopy. Trained neuroanatomists routinely resolve such topological ambiguities during manual tracing tasks by combining information about distances between branches, branch orientations, intensities, calibers, tortuosities, colors, as well as the presence of spines or boutons. Likewise, to evaluate different topological scenarios automatically, we developed a machine learning approach that combines many of the above mentioned features. A specifically designed confidence measure was used to actively train the algorithm during user-assisted tracing procedure. Active learning significantly reduces the training time and makes it possible to obtain less than 1% generalization error rates by providing few training examples. To evaluate the overall performance of the algorithm a number of image stacks were reconstructed automatically, as well as manually by several trained users, making it possible to compare the automated traces to the baseline inter-user variability. Several geometrical and topological features of the traces were selected for the comparisons. These features include the total trace length, the total numbers of branch and terminal points, the affinity of corresponding traces, and the distances between corresponding branch and terminal points. Our results show that when the density of labeled neurites is sufficiently low, automated traces are not significantly different from manual reconstructions obtained by trained users. PMID
Full Text Available Automating the process of neurite tracing from light microscopy stacks of images is essential for large-scale or high-throughput quantitative studies of neural circuits. While the general layout of labeled neurites can be captured by many automated tracing algorithms, it is often not possible to differentiate reliably between the processes belonging to different cells. The reason is that some neurites in the stack may appear broken due to imperfect labeling, while others may appear fused due to the limited resolution of optical microscopy. Trained neuroanatomists routinely resolve such topological ambiguities during manual tracing tasks by combining information about distances between branches, branch orientations, intensities, calibers, tortuosities, colors, as well as the presence of spines or boutons. Likewise, to evaluate different topological scenarios automatically, we developed a machine learning approach that combines many of the above mentioned features. A specifically designed confidence measure was used to actively train the algorithm during user-assisted tracing procedure. Active learning significantly reduces the training time and makes it possible to obtain less than 1% generalization error rates by providing few training examples. To evaluate the overall performance of the algorithm a number of image stacks were reconstructed automatically, as well as manually by several trained users, making it possible to compare the automated traces to the baseline inter-user variability. Several geometrical and topological features of the traces were selected for the comparisons. These features include the total trace length, the total numbers of branch and terminal points, the affinity of corresponding traces, and the distances between corresponding branch and terminal points. Our results show that when the density of labeled neurites is sufficiently low, automated traces are not significantly different from manual reconstructions obtained by
Chang, P; Grinband, J; Weinberg, B D; Bardis, M; Khy, M; Cadena, G; Su, M-Y; Cha, S; Filippi, C G; Bota, D; Baldi, P; Poisson, L M; Jain, R; Chow, D
The World Health Organization has recently placed new emphasis on the integration of genetic information for gliomas. While tissue sampling remains the criterion standard, noninvasive imaging techniques may provide complimentary insight into clinically relevant genetic mutations. Our aim was to train a convolutional neural network to independently predict underlying molecular genetic mutation status in gliomas with high accuracy and identify the most predictive imaging features for each mutation. MR imaging data and molecular information were retrospectively obtained from The Cancer Imaging Archives for 259 patients with either low- or high-grade gliomas. A convolutional neural network was trained to classify isocitrate dehydrogenase 1 ( IDH1 ) mutation status, 1p/19q codeletion, and O6-methylguanine-DNA methyltransferase ( MGMT ) promotor methylation status. Principal component analysis of the final convolutional neural network layer was used to extract the key imaging features critical for successful classification. Classification had high accuracy: IDH1 mutation status, 94%; 1p/19q codeletion, 92%; and MGMT promotor methylation status, 83%. Each genetic category was also associated with distinctive imaging features such as definition of tumor margins, T1 and FLAIR suppression, extent of edema, extent of necrosis, and textural features. Our results indicate that for The Cancer Imaging Archives dataset, machine-learning approaches allow classification of individual genetic mutations of both low- and high-grade gliomas. We show that relevant MR imaging features acquired from an added dimensionality-reduction technique demonstrate that neural networks are capable of learning key imaging components without prior feature selection or human-directed training. © 2018 by American Journal of Neuroradiology.
Background Population stratification is a systematic difference in allele frequencies between subpopulations. This can lead to spurious association findings in the case–control genome wide association studies (GWASs) used to identify single nucleotide polymorphisms (SNPs) associated with disease-linked phenotypes. Methods such as self-declared ancestry, ancestry informative markers, genomic control, structured association, and principal component analysis are used to assess and correct population stratification but each has limitations. We provide an alternative technique to address population stratification. Results We propose a novel machine learning method, ETHNOPRED, which uses the genotype and ethnicity data from the HapMap project to learn ensembles of disjoint decision trees, capable of accurately predicting an individual’s continental and sub-continental ancestry. To predict an individual’s continental ancestry, ETHNOPRED produced an ensemble of 3 decision trees involving a total of 10 SNPs, with 10-fold cross validation accuracy of 100% using HapMap II dataset. We extended this model to involve 29 disjoint decision trees over 149 SNPs, and showed that this ensemble has an accuracy of ≥ 99.9%, even if some of those 149 SNP values were missing. On an independent dataset, predominantly of Caucasian origin, our continental classifier showed 96.8% accuracy and improved genomic control’s λ from 1.22 to 1.11. We next used the HapMap III dataset to learn classifiers to distinguish European subpopulations (North-Western vs. Southern), East Asian subpopulations (Chinese vs. Japanese), African subpopulations (Eastern vs. Western), North American subpopulations (European vs. Chinese vs. African vs. Mexican vs. Indian), and Kenyan subpopulations (Luhya vs. Maasai). In these cases, ETHNOPRED produced ensembles of 3, 39, 21, 11, and 25 disjoint decision trees, respectively involving 31, 502, 526, 242 and 271 SNPs, with 10-fold cross validation accuracy of
Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G
Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-time prediction of sepsis onset. We aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early prediction of sepsis. Observational cohort study. Academic medical center from January 2013 to December 2015. Over 31,000 admissions to the ICUs at two Emory University hospitals (development cohort), in addition to over 52,000 ICU patients from the publicly available Medical Information Mart for Intensive Care-III ICU database (validation cohort). Patients who met the Third International Consensus Definitions for Sepsis (Sepsis-3) prior to or within 4 hours of their ICU admission were excluded, resulting in roughly 27,000 and 42,000 patients within our development and validation cohorts, respectively. None. High-resolution vital signs time series and electronic medical record data were extracted. A set of 65 features (variables) were calculated on hourly basis and passed to the Artificial Intelligence Sepsis Expert algorithm to predict onset of sepsis in the proceeding T hours (where T = 12, 8, 6, or 4). Artificial Intelligence Sepsis Expert was used to predict onset of sepsis in the proceeding T hours and to produce a list of the most significant contributing factors. For the 12-, 8-, 6-, and 4-hour ahead prediction of sepsis, Artificial Intelligence Sepsis Expert achieved area under the receiver operating characteristic in the range of 0.83-0.85. Performance of the Artificial Intelligence Sepsis Expert on the development and validation cohorts was indistinguishable. Using data available in the ICU in real-time, Artificial Intelligence Sepsis Expert can accurately predict the onset of sepsis in an ICU patient 4-12 hours prior to clinical recognition. A prospective study is necessary to determine the
Versace, Amelia; Sharma, Vinod; Bertocci, Michele A; Bebko, Genna; Iyengar, Satish; Dwojak, Amanda; Bonar, Lisa; Perlman, Susan B; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Diwadkar, Vaibhav A; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Frazier, Thomas W; Arnold, L Eugene; Fristad, Mary A; Youngstrom, Eric A; Horwitz, Sarah M; Findling, Robert L; Phillips, Mary L
Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation in youth. Recent studies indicate that machine learning techniques can help elucidate the role of neuroimaging measures in classifying individual subjects by specific symptom trajectory. Cortical thickness measures were extracted in sixty-eight anatomical regions covering the entire brain in 115 participants from the Longitudinal Assessment of Manic Symptoms (LAMS) study and 31 healthy comparison youth (12.5 y/o;-Male/Female = 15/16;-IQ = 104;-Right/Left handedness = 24/5). Using a combination of trajectories analyses, surface reconstruction, and machine learning techniques, the present study aims to identify the extent to which measures of cortical thickness can accurately distinguish youth with higher (n = 18) from those with lower (n = 34) trajectories of manic-like behaviors in a large sample of LAMS youth (n = 115; 13.6 y/o; M/F = 68/47, IQ = 100.1, R/L = 108/7). Machine learning analyses revealed that widespread cortical thickening in portions of the left dorsolateral prefrontal cortex, right inferior and middle temporal gyrus, bilateral precuneus, and bilateral paracentral gyri and cortical thinning in portions of the right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, and right parahippocampal gyrus accurately differentiate (Area Under Curve = 0.89;p = 0.03) youth with different (higher vs lower) trajectories of positive mood and energy dysregulation over a period up to 5years, as measured by the Parent General Behavior Inventory-10 Item Mania Scale. Our findings suggest that specific patterns of cortical thickness may reflect transdiagnostic neural mechanisms associated with different temporal trajectories of positive mood and energy dysregulation in youth. This approach has
Dral, Pavlo O.; Owens, Alec; Yurchenko, Sergei N.; Thiel, Walter
We present an efficient approach for generating highly accurate molecular potential energy surfaces (PESs) using self-correcting, kernel ridge regression (KRR) based machine learning (ML). We introduce structure-based sampling to automatically assign nuclear configurations from a pre-defined grid to the training and prediction sets, respectively. Accurate high-level ab initio energies are required only for the points in the training set, while the energies for the remaining points are provided by the ML model with negligible computational cost. The proposed sampling procedure is shown to be superior to random sampling and also eliminates the need for training several ML models. Self-correcting machine learning has been implemented such that each additional layer corrects errors from the previous layer. The performance of our approach is demonstrated in a case study on a published high-level ab initio PES of methyl chloride with 44 819 points. The ML model is trained on sets of different sizes and then used to predict the energies for tens of thousands of nuclear configurations within seconds. The resulting datasets are utilized in variational calculations of the vibrational energy levels of CH3Cl. By using both structure-based sampling and self-correction, the size of the training set can be kept small (e.g., 10% of the points) without any significant loss of accuracy. In ab initio rovibrational spectroscopy, it is thus possible to reduce the number of computationally costly electronic structure calculations through structure-based sampling and self-correcting KRR-based machine learning by up to 90%.
Full Text Available Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation in youth. Recent studies indicate that machine learning techniques can help elucidate the role of neuroimaging measures in classifying individual subjects by specific symptom trajectory. Cortical thickness measures were extracted in sixty-eight anatomical regions covering the entire brain in 115 participants from the Longitudinal Assessment of Manic Symptoms (LAMS study and 31 healthy comparison youth (12.5 y/o;-Male/Female = 15/16;-IQ = 104;-Right/Left handedness = 24/5. Using a combination of trajectories analyses, surface reconstruction, and machine learning techniques, the present study aims to identify the extent to which measures of cortical thickness can accurately distinguish youth with higher (n = 18 from those with lower (n = 34 trajectories of manic-like behaviors in a large sample of LAMS youth (n = 115; 13.6 y/o; M/F = 68/47, IQ = 100.1, R/L = 108/7. Machine learning analyses revealed that widespread cortical thickening in portions of the left dorsolateral prefrontal cortex, right inferior and middle temporal gyrus, bilateral precuneus, and bilateral paracentral gyri and cortical thinning in portions of the right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, and right parahippocampal gyrus accurately differentiate (Area Under Curve = 0.89;p = 0.03 youth with different (higher vs lower trajectories of positive mood and energy dysregulation over a period up to 5years, as measured by the Parent General Behavior Inventory-10 Item Mania Scale. Our findings suggest that specific patterns of cortical thickness may reflect transdiagnostic neural mechanisms associated with different temporal trajectories of positive mood and energy dysregulation in youth. This
Dresselhaus-Cooper, Leora; Howard, Marylesa; Hock, Margaret C.; Meehan, B. T.; Ramos, Kyle J.; Bolme, Cindy A.; Sandberg, Richard L.; Nelson, Keith A.
A supervised machine learning algorithm, called locally adaptive discriminant analysis (LADA), has been developed to locate boundaries between identifiable image features that have varying intensities. LADA is an adaptation of image segmentation, which includes techniques that find the positions of image features (classes) using statistical intensity distributions for each class in the image. In order to place a pixel in the proper class, LADA considers the intensity at that pixel and the distribution of intensities in local (nearby) pixels. This paper presents the use of LADA to provide, with statistical uncertainties, the positions and shapes of features within ultrafast images of shock waves. We demonstrate the ability to locate image features including crystals, density changes associated with shock waves, and material jetting caused by shock waves. This algorithm can analyze images that exhibit a wide range of physical phenomena because it does not rely on comparison to a model. LADA enables analysis of images from shock physics with statistical rigor independent of underlying models or simulations.
In the era of digital technology, there is abundant information from various sources. This ease of access needs to be accompanied by the ability to engage with the information wisely. Thus, information and media literacy is required. From the results of preliminary observations, it was found that the students of Universitas Negeri Surabaya, whose major is Indonesian Literature, and they take journalistic course lack of the skill of media and information literacy (MIL). Therefore, they need to be equipped with MIL. The method used is descriptive qualitative, which includes data collection, data analysis, and presentation of data analysis. Observation and documentation techniques were used to obtain data of MIL’s impact on journalistic learning for students. This study aims at describing the important role of MIL for students of journalistic and its impact on journalistic learning for students of Indonesian literature batch 2014. The results of this research indicate that journalistic is a science that is essential for students because it affects how a person perceives news report. Through the reinforcement of the course, students can avoid a hoax. MIL-based journalistic learning makes students will be more skillful at absorbing, processing, and presenting information accurately. The subject influences students in engaging with information so that they can report news credibly.
Carlson, Joel N. K.; Park, Jong Min; Park, So-Yeon; In Park, Jong; Choi, Yunseok; Ye, Sung-Joon
Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD = 1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be
Collins, Christopher R.; Gordon, Geoffrey J.; von Lilienfeld, O. Anatole; Yaron, David J.
Two different classes of molecular representations for use in machine learning of thermodynamic and electronic properties are studied. The representations are evaluated by monitoring the performance of linear and kernel ridge regression models on well-studied data sets of small organic molecules. One class of representations studied here counts the occurrence of bonding patterns in the molecule. These require only the connectivity of atoms in the molecule as may be obtained from a line diagram or a SMILES string. The second class utilizes the three-dimensional structure of the molecule. These include the Coulomb matrix and Bag of Bonds, which list the inter-atomic distances present in the molecule, and Encoded Bonds, which encode such lists into a feature vector whose length is independent of molecular size. Encoded Bonds' features introduced here have the advantage of leading to models that may be trained on smaller molecules and then used successfully on larger molecules. A wide range of feature sets are constructed by selecting, at each rank, either a graph or geometry-based feature. Here, rank refers to the number of atoms involved in the feature, e.g., atom counts are rank 1, while Encoded Bonds are rank 2. For atomization energies in the QM7 data set, the best graph-based feature set gives a mean absolute error of 3.4 kcal/mol. Inclusion of 3D geometry substantially enhances the performance, with Encoded Bonds giving 2.4 kcal/mol, when used alone, and 1.19 kcal/mol, when combined with graph features.
Kaymakamoglu, Sibel Ersel
Since contemporary views of learning and teaching place learners in the center of learning process, most of the researchers and practitioners have directed their attention to understanding what goes on in the mind of the learners during the process of learning and teaching. In the area of English language learning and teaching this perspective…
An, Song A.; Ma, Tingting; Capraro, Mary Margaret
This article presents exploratory research investigating the integration of music and a mathematics lesson as an intervention to promote preservice teachers' attitude and confidence and to extend their beliefs toward teaching mathematics integrated with music. Thirty students were randomly selected from 64 preservice teachers in a southern…
Sullivan, Florence R.; Moriarty, Mary A.
Much educational software is designed from a specific pedagogical stance. How teachers conceive of the pedagogical stance underlying the design will affect how they utilize the technology; these conceptions may vary from teacher to teacher and from teacher to designer. There may be a conflict between the designer's pedagogical beliefs inscribed in…
Wang, Cheng-Lung; Liou, Pey-Yan
Taiwanese students are featured as having high academic achievement but low motivational beliefs according to the serial results of the Trends in Mathematics and Science Study (TIMSS). Moreover, given that the role of context has become more important in the development of academic motivation theory, this study aimed to examine the relationship…
Martin, Ron Reuel
This study was an investigation of student beliefs about their EFL education, and it was based upon the subjective task value component of the expectancy-value theory, a prominent theory of achievement motivation. The participants were three cohorts of Japanese public elementary school students (Cohort 1 from 2008; Cohort 2 from 2009; and Cohort 3…
In this study of 16 teachers in two primary schools in the Netherlands, researchers built on findings from previous studies to demonstrate that a thoughtfully designed professional development program can be "effective and sustainable, if certain conditions are met" (p. 772) in changing teachers' knowledge, beliefs, perceived problems,…
Walter, Tony; Waterhouse, Helen
A sizeable minority of Westerners who have no particular connection with Eastern or New Age religions nevertheless claim to believe in reincarnation. Does this belief affect their practical morality and how they think about suffering and injustice? An interview study conducted in England mapped the range of meanings such people give to reincarnation, and found: 1) Karma was widely referred to, but in the context of Western notions of self-improvement; there was little recognition of the possi...
KARAMAN, Ayhan; KARAMAN, Pınar
Turkey following the footsteps of western education system is nowadays struggling to implement constructivist paradigm in its schools. The success of the integration of constructivist elements into the schools is heavily contingent upon the support of teachers. This necessitates that the ideas advocated in constructivist reform movements should be promoted adequately in the preparation of teacher candidates. Therefore, investigating the beliefs of prospective teachers regarding reformed scien...
Noroozi, Omid; Hatami, Javad
Although the importance of students’ argumentative peer feedback for learning is undeniable, there is a need for further empirical evidence on whether and how it is related to various aspects of argumentation-based learning namely argumentative essay writing, domain-specific learning, and
Ali, Liaqat; Asadi, Mohsen; Gasevic, Dragan; Jovanovic, Jelena; Hatala, Marek
Present research and development offer various learning analytics tools providing insights into different aspects of learning processes. Adoption of a specific tool for practice is based on how its learning analytics are perceived by educators to support their pedagogical and organizational goals. In this paper, we propose and empirically validate…
Masso, Majid; Vaisman, Iosif I
Accurate predictive models for the impact of single amino acid substitutions on protein stability provide insight into protein structure and function. Such models are also valuable for the design and engineering of new proteins. Previously described methods have utilized properties of protein sequence or structure to predict the free energy change of mutants due to thermal (DeltaDeltaG) and denaturant (DeltaDeltaG(H2O)) denaturations, as well as mutant thermal stability (DeltaT(m)), through the application of either computational energy-based approaches or machine learning techniques. However, accuracy associated with applying these methods separately is frequently far from optimal. We detail a computational mutagenesis technique based on a four-body, knowledge-based, statistical contact potential. For any mutation due to a single amino acid replacement in a protein, the method provides an empirical normalized measure of the ensuing environmental perturbation occurring at every residue position. A feature vector is generated for the mutant by considering perturbations at the mutated position and it's ordered six nearest neighbors in the 3-dimensional (3D) protein structure. These predictors of stability change are evaluated by applying machine learning tools to large training sets of mutants derived from diverse proteins that have been experimentally studied and described. Predictive models based on our combined approach are either comparable to, or in many cases significantly outperform, previously published results. A web server with supporting documentation is available at http://proteins.gmu.edu/automute.
Liang, Liang; Liu, Minliang; Martin, Caitlin; Sun, Wei
Structural finite-element analysis (FEA) has been widely used to study the biomechanics of human tissues and organs, as well as tissue-medical device interactions, and treatment strategies. However, patient-specific FEA models usually require complex procedures to set up and long computing times to obtain final simulation results, preventing prompt feedback to clinicians in time-sensitive clinical applications. In this study, by using machine learning techniques, we developed a deep learning (DL) model to directly estimate the stress distributions of the aorta. The DL model was designed and trained to take the input of FEA and directly output the aortic wall stress distributions, bypassing the FEA calculation process. The trained DL model is capable of predicting the stress distributions with average errors of 0.492% and 0.891% in the Von Mises stress distribution and peak Von Mises stress, respectively. This study marks, to our knowledge, the first study that demonstrates the feasibility and great potential of using the DL technique as a fast and accurate surrogate of FEA for stress analysis. © 2018 The Author(s).
Scott, Karen M.
As universities invest in the development of e-learning resources, e-learning sustainability has come under consideration. This has largely focused on the challenges and facilitators of organisational and technological sustainability and scalability, and professional development. Little research has examined the experience of a teacher dealing with e-learning sustainability when taking over a course with an e-learning resource and associated assessment. This research focuses on a teacher who ...
Full Text Available Amid growing concerns about the future of the U.S. economy and workforce, educators and policymakers alike have increasingly emphasized the need to expand the number of students interested in, qualified for and actually pursuing careers in science, technology, engineering and mathematics (STEM. The current study draws on survey responses from a sample of 3852 high school students at inclusive STEM schools across the U.S. to investigate how project- and problem-based learning (PBL may work to address this need. Multivariate regression results indicate that student ratings of PBL are associated with interest in pursuing a career in STEM, as well as with intrinsic motivation for science and students’ ability beliefs for both science and math. Further, mediation analysis using Hayes’ (2014 MEDIATE macro suggests that science intrinsic motivation and ability beliefs mediate the relationship between perceived PBL experiences and student interest in a future STEM career (IFSC. Our results highlight the important potential of PBL for increasing student STEM attitudes and interest in future STEM careers. As one of the only large-scale quantitative analyses of its kind, this study provides critical information for educators, school administrators and policymakers as they continue to seek effective ways of encouraging students to pursue STEM careers.
Thapelo L. Mamiala
Full Text Available The paper documents beliefs that manifest themselves through newspaper items and elaborates on their potential to enhance a sustainable learning environment in a school science lesson. “Learning environment” is depicted from different angles and includes virtual and real learning environments, school environments and classroom environments. Descriptive and item analyses were conducted on sixty-eight newspaper items that were identified. The nature of problems and prescriptions/solutions was categorised for each item and the paper further provides elaboration on the types of problems and recommended solutions. The results show that the “believed” structure contents in their newspaper items to catch the attention of the “believer”. Lessons on the power of belief must be learnt by school science teachers if they are to succeed in creating a sustainable learning environment with improved performance in school science.
Mayberry, L J; Affonso, D D; Shibuya, J; Clemmens, D
Determining the elements of culturally competent health care is an important goal for nurses. This goal is particularly integral in efforts to design better preventive health care strategies for pregnant and postpartum women from multiple cultural and ethnic backgrounds. Learning about the values, beliefs, and customs surrounding health among the targeted groups is essential, but integrating this knowledge into the actual health care services delivery system is more difficult. The success of a prenatal and postpartum program developed for native Hawaiian, Filipino, and Japanese women in Hawaii has been attributed to the attention on training, direct care giving, and program monitoring participation by local cultural and ethnic healers and neighborhood leaders living in the community, with coordination by public health nurses. This article profiles central design elements with examples of specific interventions used in the Malama Na Wahine or Caring for Pregnant Women program to illustrate a unique approach to the delivery of culturally competent care.
Kim, ChanMin; Kim, Min Kyu; Lee, Chiajung; Spector, J. Michael; DeMeester, Karen
The purpose of this exploratory mixed methods study was to investigate how teacher beliefs were related to technology integration practices. We were interested in how and to what extent teachers' (a) beliefs about the nature of knowledge and learning, (b) beliefs about effective ways of teaching, and (c) technology integration practices were…
This article reports on research which aimed to examine academic staff attitudes to, and beliefs regarding the role and efficacy of, support for students' broader learning needs once engaged in degree study. It is contended here that the perspective of teachers represents a gap in current pedagogical research. The study has two complementary aims:…
Viholainen, Antti; Asikainen, Mervi; Hirvonen, Pekka E.
This article examines Finnish mathematics student teachers' epistemological beliefs concerning the nature of mathematics and the goals of mathematics teaching and learning solely in the beginning of their studies at university. A total of 18 students participated in a study consisting of a short questionnaire and interviews. The data was analyzed…
Smith, Derick Graham
This study sought to answer the question: "To what extent do prior beliefs about and experiences of teaching and learning influence the instructional practices of new independent school teachers," who are generally not required to have any formal pedagogical training or hold teacher certification prior to beginning full-time employment.…
Kao, Chia-Pin; Tsai, Chin-Chung
This study was conducted to explore the relationships between teachers' Internet self-efficacy, beliefs about web-based learning and attitudes toward web-based professional development. The sample of this study included 421 teachers, coming from 20 elementary schools in Taiwan. The three instruments used to assess teachers' Internet self-efficacy…
Burch, Sharlee Shirley
The purpose of this non-experimental causal-comparative study was to determine if service-learning teaching experience affects dental hygiene faculty perceptions of service-learning benefits and barriers in the United States. Dental hygiene educators from entry-level dental hygiene education programs in the United States completed the Web-based…
Boschman, Ferry; McKenney, Susan; Pieters, Jules; Voogt, Joke
Teacher engagement in the design of technology-rich learning material is beneficial to teacher learning and may create a sense of ownership, both of which are conducive to bringing about innovation with technology. During collaborative design, teachers draw on various types of knowledge and
Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping
The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
Scott, Karen M.
As universities invest in the development of e-learning resources, e-learning sustainability has come under consideration. This has largely focused on the challenges and facilitators of organisational and technological sustainability and scalability, and professional development. Little research has examined the experience of a teacher dealing…
Rosman, Tom; Peter, Johannes; Mayer, Anne-Kathrin; Krampen, Günter
The present article investigates the effects of epistemic beliefs (i.e. beliefs about the nature of knowledge and knowing) on the effectiveness of information literacy instruction (i.e. instruction on how to search for scholarly information in academic settings). We expected psychology students with less sophisticated beliefs (especially…
Silverman, Arielle M; Pitonyak, Jennifer S; Nelson, Ian K; Matsuda, Patricia N; Kartin, Deborah; Molton, Ivan R
To develop and test a novel impairment simulation activity to teach beginning rehabilitation students how people adapt to physical impairments. Masters of Occupational Therapy students (n = 14) and Doctor of Physical Therapy students (n = 18) completed the study during the first month of their program. Students were randomized to the experimental or control learning activity. Experimental students learned to perform simple tasks while simulating paraplegia and hemiplegia. Control students viewed videos of others completing tasks with these impairments. Before and after the learning activities, all students estimated average self-perceived health, life satisfaction, and depression ratings among people with paraplegia and hemiplegia. Experimental students increased their estimates of self-perceived health, and decreased their estimates of depression rates, among people with paraplegia and hemiplegia after the learning activity. The control activity had no effect on these estimates. Impairment simulation can be an effective way to teach rehabilitation students about the adaptations that people make to physical impairments. Positive impairment simulations should allow students to experience success in completing activities of daily living with impairments. Impairment simulation is complementary to other pedagogical methods, such as simulated clinical encounters using standardized patients. Implication of Rehabilitation It is important for rehabilitation students to learn how people live well with disabilities. Impairment simulations can improve students' assessments of quality of life with disabilities. To be beneficial, impairment simulations must include guided exposure to effective methods for completing daily tasks with disabilities.
Conclusions: This study showed that the intensity of perceived threats, perceived barriers and self-efficacy structures, and observational learning are some of the factors related to physical activity among adolescent girls, and it is possible that by focusing on improving these variables through interventional programs physical activity among adolescent girls can be improved.
Kuntz, Patricia S.
A study investigated the attitudes toward language learning held by early secondary school students (ages 11-13) on the island of Saint Lucia who are studying French and Spanish simultaneously, as required in the first two years of secondary school. Subjects were students at two schools, and included 121 boys and 72 girls. The survey consisted of…
The purpose of this study was to determine the impact of an Science-Technology-Society (STS) course for preservice science teachers. The course was designed to change not only preservice science teachers' attitudes toward science, scientists and science courses, but also the awareness and use of STS/Constructivist approaches in teaching. It also focuses on changes in preservice science teachers regarding the effectiveness of an STS/Constructivist learning environment. Both qualitative and quantitative research methods were used with and a one-group pretest-posttest design. The instruments were administered to the preservice science teachers at the beginning of the semester as pre-tests and again at the end of the semester as post-tests. Data gathered from pre- and post-administration were analyzed for each of the instruments that provide answers to the research questions. The sample consists of forty-one pre-service science teachers who were enrolled in the Societal & Educational Applications of Biological Concepts course during the spring semester of the 2004 and 2005 academic years at the University of Iowa. The major findings for the study include the following: (1) Preservice science teachers showed significantly growth over the semester in their perceptions concerning STS/Constructivism, beliefs about science teaching and learning, and attitudes toward science and technology, and their implications for society. These significant changes were not affected by gender nor grade (elementary vs secondary) level. (2) Preservice science teachers gain in understanding of how students learn with STS/Constructivist approaches. They also increased their use of STS/Constructivist approaches which were developed and applied to teaching science for all students. (3) Preservice science teachers showed statistically significant growth toward an STS/Constructivist philosophy of science teaching and learning in terms of student actions in the classroom, as well as their
Franco, Gina M.
The purpose of this study was to investigate the role of epistemic beliefs and knowledge representations in cognitive and metacognitive processing and conceptual change when learning about physics concepts through text. Specifically, I manipulated the representation of physics concepts in texts about Newtonian mechanics and explored how these texts interacted with individuals' epistemic beliefs to facilitate or constrain learning. In accordance with definitions from Royce's (1983) framework of psychological epistemology, texts were developed to present Newtonian concepts in either a rational or a metaphorical format. Seventy-five undergraduate students completed questionnaires designed to measure their epistemic beliefs and their misconceptions about Newton's laws of motion. Participants then read the first of two instructional texts (in either a rational or metaphorical format), and were asked to think aloud while reading. After reading the text, participants completed a recall task and a post-test of selected items regarding Newtonian concepts. These steps were repeated with a second instructional text (in either a rational or metaphorical format, depending on which format was assigned previously). Participants' think-aloud sessions were audio-recorded, transcribed, and then blindly coded, and their recalls were scored for total number of correctly recalled ideas from the text. Changes in misconceptions were analyzed by examining changes in participants' responses to selected questions about Newtonian concepts from pretest to posttest. Results revealed that when individuals' epistemic beliefs were congruent with the knowledge representations in their assigned texts, they performed better on both online measures of learning (e.g., use of processing strategies) and offline products of learning (e.g., text recall, changes in misconceptions) than when their epistemic beliefs were incongruent with the knowledge representations. These results have implications for how
Chauke, Helani Elisa
The aims of this research were to determine, by means of both the literature review and the empirical research, the experiences secondary school learners have in the compilation of their learning portfolios and the influence this compilation of the portfolios has on their perceptions of their efficacy; and to make suggestions for the continued use of the portfolio in developing interests of learners. The sample for this study consisted of 744 learners studying Mathematics and Science. The stu...
Damien Le Gal
Full Text Available English as Foreign Language (EFL in East Asia involves major sociocultural issues. Modern, Western-based methodologies such as Communicative Language Learning (CLL, Communicative Language Teaching, CLT in this paper and its further development Task-Based Language Learning and Teaching (TBLLT, Ellis, 2003, feature principles which can conflict with some of the fundamental values of Confucian Heritage Cultures (CHC education and hinder their adoption in Korea, Taiwan, Japan, Singapore, Hong-Kong and Vietnam. This article introduces a sociocultural, ethnographic perspective on EFL in East Asia which contextualizes language teaching in its broader educational and cultural environment. Teacher-centeredness, book and writing focuses, memorization strategies within a grammar-translation approach are in contradiction with modern language teaching methodologies' focuses on learner-centeredness and teachers' facilitating roles, student participation and interactions, communication competence and learner autonomy. The text advocates for a mean between Western and Eastern learning cultures through a context-based, culturally-sensitive approach and introduces classroom's strategies for the implementation of CLL and TBLLT in China and East Asia.
Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M
Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in  and .
Devising a Structural Equation Model of Relationships between Preservice Teachers' Time and Study Environment Management, Effort Regulation, Self-Efficacy, Control of Learning Beliefs, and Metacognitive Self-Regulation
Sen, Senol; Yilmaz, Ayhan
The objective of this study is to analyze the relationship between preservice teachers' time and study environment management, effort regulation, self-efficacy beliefs, control of learning beliefs and metacognitive self-regulation. This study also investigates the direct and indirect effects of metacognitive self-regulation on time and study…
Full Text Available Moran’s revised conception of conscious belief requires us to reconceptualise suppressed belief. The work of Merleau-Ponty offers a way to do this. His account of motor-skills allows us to understand suppressed beliefs as pre-reflective ways of dealing with the world.
Richardson, Greer M.; Byrne, Laurel L.; Liang, Ling L.
Recognizing that teaching efficacy beliefs influence pedagogical content knowledge, this study assesses the impact of a general methods course on preservice teachers' efficacy beliefs and instructional planning of environmental education content. The course used explicit and visible strategies to support pedagogical and content knowledge…
Lynch, Jacqueline; Owston, Ron
Given the limited research on preschool teachers' beliefs about teaching language and literacy in the preschool years, as well as on their conceptual understanding of children's language and literacy development, this study examined the beliefs of 79 preschool teachers who had at least a 2-year diploma in early childhood education. All were…
Atar, Hakan Yavuz
teachers NOS conceptions. Developing desired understanding of nature of science conceptions and having an adequate experience with inquiry learning is especially important for science teachers because science education literature suggests that the development of teachers' nature of science conceptions is influenced by their experiences with inquiry science (Akerson et. al. 2000) and implementation of science lessons reflect teachers' NOS conceptions (Abd-EL-Khalick & Boujaoude, 1997; Matson & Parsons, 1998; Rosenthal, 1993; Trowbridge, Bybee & Powell, 2000; Turner & Sullenger, 1999). Furthermore, the impediments to successful integration of inquiry based science instruction from teachers' perspective are particularly important, as they are the implementers of inquiry based science education reform. The purpose of this study is to understand the relationship between the teachers' NOS conceptions and their inquiry beliefs and practices in their classrooms and how this relationship impedes or contributes to the implementation of inquiry based science education reform efforts. The participants of this study were in-service teachers who were accepted into the online Masters Program in science education program at a southern university. Three online courses offered in the summer semester of 2005 constituted the research setting of this study: (1) Special Problems in the Teaching of Secondary School Science: Nature of Science & Science Teaching, (2) Curriculum in Science Education, and (3) Colloquium. Multiple data sources were used for data triangulation (Miles & Huberman, 1984; Yin, 1994) in order to understand the relationship between participants' NOS views and their conceptions and beliefs about inquiry-based science teaching. The study revealed that the relationship between the teachers' NOS conceptions and their inquiry beliefs and practices is far from being simple and linear. Data suggests that the teachers' sophistication of NOS conceptions influence their perception of
Meyvis, Tom; Ratner, Rebecca K.; Levav, Jonathan
Why do affective forecasting errors persist in the face of repeated disconfirming evidence? Five studies demonstrate that people misremember their forecasts as consistent with their experience and thus fail to perceive the extent of their forecasting error. As a result, people do not learn from past forecasting errors and fail to adjust subsequent…
Ritter, Jennifer M.
The purpose of this study was to develop, validate and establish the reliability of an instrument to assess the self-efficacy beliefs of prospective elementary teachers with regards to science teaching and learning for diverse learners. The study used Bandura's theoretical framework, in that the instrument would use the self-efficacy construct to explore the beliefs of prospective elementary science teachers with regards to science teaching and learning to diverse learners: specifically the two dimensions of self-efficacy beliefs defined by Bandura (1977): personal self-efficacy and outcome expectancy. A seven step plan was designed and followed in the process of developing the instrument, which was titled the Self-Efficacy Beliefs about Equitable Science Teaching or SEBEST. Diverse learners as recognized by Science for All Americans (1989) are "those who in the past who have largely been bypassed in science and mathematics education: ethnic and language minorities and girls" (p. xviii). That definition was extended by this researcher to include children from low socioeconomic backgrounds based on the research by Gomez and Tabachnick (1992). The SEBEST was administered to 226 prospective elementary teachers at The Pennsylvania State University. Using the results from factor analyses, Coefficient Alpha, and Chi-Square a 34 item instrument was found to achieve the greatest balance across the construct validity, reliability and item balance with the content matrix. The 34 item SEBEST was found to load purely on four factors across the content matrix thus providing evidence construct validity. The Coefficient Alpha reliability for the 34 item SEBEST was .90 and .82 for the PSE sub-scale and .78 for the OE sub-scale. A Chi-Square test (X2 = 2.7 1, df = 7, p > .05) was used to confirm that the 34 items were balanced across the Personal Self-Efficacy/Outcome Expectancy and Ethnicity/LanguageMinority/Gender Socioeconomic Status/dimensions of the content matrix. Based on
Full Text Available Bayesian network classifiers (BNCs have demonstrated competitive classification accuracy in a variety of real-world applications. However, it is error-prone for BNCs to discriminate among high-confidence labels. To address this issue, we propose the label-driven learning framework, which incorporates instance-based learning and ensemble learning. For each testing instance, high-confidence labels are first selected by a generalist classifier, e.g., the tree-augmented naive Bayes (TAN classifier. Then, by focusing on these labels, conditional mutual information is redefined to more precisely measure mutual dependence between attributes, thus leading to a refined generalist with a more reasonable network structure. To enable finer discrimination, an expert classifier is tailored for each high-confidence label. Finally, the predictions of the refined generalist and the experts are aggregated. We extend TAN to LTAN (Label-driven TAN by applying the proposed framework. Extensive experimental results demonstrate that LTAN delivers superior classification accuracy to not only several state-of-the-art single-structure BNCs but also some established ensemble BNCs at the expense of reasonable computation overhead.
During the past decade, research on the constructive learning process has been conducted mainly from two perspectives: student approaches to learning (SAL) and self-regulated learning (SRL). The SAL perspective has highlighted the role of learning conceptions with respect to other topics involved in constructive learning processes, whereas…
Full Text Available Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN, viz. Residual Network (ResNet and its improved version named ResNeXt, are used to detect internal mechanical damage of blueberries using hyperspectral transmittance data. The original structure and size of hypercubes are adapted for the deep CNN training. To ensure that the models are applicable to hypercube, we adjust the number of filters in the convolutional layers. Moreover, a total of 5 traditional machine learning algorithms, viz. Sequential Minimal Optimization (SMO, Linear Regression (LR, Random Forest (RF, Bagging and Multilayer Perceptron (MLP, are performed as the comparison experiments. In terms of model assessment, k-fold cross validation is used to indicate that the model performance does not vary with the different combination of dataset. In real-world application, selling damaged berries will lead to greater interest loss than discarding the sound ones. Thus, precision, recall, and F1-score are also used as the evaluation indicators alongside accuracy to quantify the false positive rate. The first three indicators are seldom used by investigators in the agricultural engineering domain. Furthermore, ROC curves and Precision-Recall curves are plotted to visualize the performance of classifiers. The fine-tuned ResNet/ResNeXt achieve average accuracy and F1-score of 0.8844/0.8784 and 0.8952/0.8905, respectively. Classifiers SMO/ LR/RF/Bagging/MLP obtain average accuracy and F1-score of 0.8082/0.7606/0.7314/0.7113/0.7827 and 0.8268/0.7796/0.7529/0.7339/0.7971, respectively. Two deep learning models achieve better classification performance than the traditional machine learning methods. Classification for each testing sample only takes 5.2 ms and 6.5 ms respectively for ResNet and ResNeXt, indicating that the deep learning framework has great
Wang, Zhaodi; Hu, Menghan; Zhai, Guangtao
Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version named ResNeXt, are used to detect internal mechanical damage of blueberries using hyperspectral transmittance data. The original structure and size of hypercubes are adapted for the deep CNN training. To ensure that the models are applicable to hypercube, we adjust the number of filters in the convolutional layers. Moreover, a total of 5 traditional machine learning algorithms, viz. Sequential Minimal Optimization (SMO), Linear Regression (LR), Random Forest (RF), Bagging and Multilayer Perceptron (MLP), are performed as the comparison experiments. In terms of model assessment, k-fold cross validation is used to indicate that the model performance does not vary with the different combination of dataset. In real-world application, selling damaged berries will lead to greater interest loss than discarding the sound ones. Thus, precision, recall, and F1-score are also used as the evaluation indicators alongside accuracy to quantify the false positive rate. The first three indicators are seldom used by investigators in the agricultural engineering domain. Furthermore, ROC curves and Precision-Recall curves are plotted to visualize the performance of classifiers. The fine-tuned ResNet/ResNeXt achieve average accuracy and F1-score of 0.8844/0.8784 and 0.8952/0.8905, respectively. Classifiers SMO/ LR/RF/Bagging/MLP obtain average accuracy and F1-score of 0.8082/0.7606/0.7314/0.7113/0.7827 and 0.8268/0.7796/0.7529/0.7339/0.7971, respectively. Two deep learning models achieve better classification performance than the traditional machine learning methods. Classification for each testing sample only takes 5.2 ms and 6.5 ms respectively for ResNet and ResNeXt, indicating that the deep learning framework has great potential for
Hu, Menghan; Zhai, Guangtao
Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version named ResNeXt, are used to detect internal mechanical damage of blueberries using hyperspectral transmittance data. The original structure and size of hypercubes are adapted for the deep CNN training. To ensure that the models are applicable to hypercube, we adjust the number of filters in the convolutional layers. Moreover, a total of 5 traditional machine learning algorithms, viz. Sequential Minimal Optimization (SMO), Linear Regression (LR), Random Forest (RF), Bagging and Multilayer Perceptron (MLP), are performed as the comparison experiments. In terms of model assessment, k-fold cross validation is used to indicate that the model performance does not vary with the different combination of dataset. In real-world application, selling damaged berries will lead to greater interest loss than discarding the sound ones. Thus, precision, recall, and F1-score are also used as the evaluation indicators alongside accuracy to quantify the false positive rate. The first three indicators are seldom used by investigators in the agricultural engineering domain. Furthermore, ROC curves and Precision-Recall curves are plotted to visualize the performance of classifiers. The fine-tuned ResNet/ResNeXt achieve average accuracy and F1-score of 0.8844/0.8784 and 0.8952/0.8905, respectively. Classifiers SMO/ LR/RF/Bagging/MLP obtain average accuracy and F1-score of 0.8082/0.7606/0.7314/0.7113/0.7827 and 0.8268/0.7796/0.7529/0.7339/0.7971, respectively. Two deep learning models achieve better classification performance than the traditional machine learning methods. Classification for each testing sample only takes 5.2 ms and 6.5 ms respectively for ResNet and ResNeXt, indicating that the deep learning framework has great potential for
Full Text Available Tim Crane maintains that beliefs cannot be conscious because they persist in the absence of consciousness. Conscious judgments can share their contents with beliefs, and their occurrence can be evidence for what one believes; but they cannot be beliefs, because they don’t persist. I challenge Crane’s premise that belief attributions to the temporarily unconscious are literally true. To say of an unconscious agent that she believes that p is like saying that she sings well. To say she sings well is to say that when she sings, her singing is good. To say that she believes that p is (roughly to say that when she consciously considers the content that p she consciously affirms (believes it. I also argue that the phenomenal view of intentional content Crane appears to endorse prima facie commits him to the view, at least controversial, perhaps incoherent, that there is unconscious phenomenology (the intentional contents of unconscious beliefs.
Peterson, Sarah; Schreiber, Jim; Moss, Connie
We examined the effects of an educational psychology course on students' beliefs about motivating students. After providing opportunities to engage in systematic intentional inquiry of their beliefs about teaching and learning, we expected that students' beliefs would become more soundly based in theory and research. Following several classes on…
Andrews, Paul; Diego-Mantecón, Jose
Much comparative research into education-related beliefs has exploited questionnaires developed in one culture for use in another. This has been particularly the case in mathematics education, the focus of this paper. In so doing, researchers have tended to assume that translation alone is sufficient to warrant a reliable and valid instrument for…
Sikko, S.A.; Lyngved, R.; Pepin, B.
This paper reports on mathematics and science teachers’ beliefs concerning the use of inquiry-based teaching strategies. Two different surveys were conducted: one with 24 teachers who were to become future instructional leaders; and one with 75 teachers as part of an international baseline study. We
Magogwe, Joel Mokuedi; Oliver, Rhonda
This research seeks to extend our current knowledge by exploring the relationship between preferred language strategies, age, proficiency, and self-efficacy beliefs. Responding to the call for more replication of strategy research and for research in different cultural contexts, this research was undertaken in Botswana between 2002 and 2005. The…
Smit, Karin; De Brabander, Cornelis; Boekaerts, Monique; Martens, Rob
In this research we studied students´ motivational self-regulation as mediator between motivational beliefs and motivational outcomes. Dutch students in pre-vocational secondary education (N=3602, mean age 14) completed a questionnaire on five motivational strategies (Environmental Control,
O sistema de crenças do aprendiz brasileiro de inglês: fatores que influenciam na construção de crenças Belief systems of Brazilians learning English: factors that influence in the building of beliefs
Full Text Available As crenças sobre aprendizagem de línguas têm sido tópico de interesse entre autores em pesquisadores na área de ensino de línguas. Este trabalho traz uma discussão sobre os fatores que atuam na formação das crenças de alunos e professores de Língua Inglesa. Inicialmente, comento sobre o interesse pela investigação do sistema de crenças do aprendiz de inglês como língua estrangeira. Mostro a influência que as crenças que compõem o imaginário dos professores e aprendizes exercem na maneira como abordam o processo de ensino/aprendizagem. Passo então para a discussão dos principais fatores responsáveis pela formação das crenças, entre os quais alguns estão intimamente relacionados ao contexto brasileiro de ensino/aprendizagem da língua inglesa.Language learning beliefs has been a frequently discussed topic of Applied Linguistics in the area of language learning and teaching. This paper discusses the beliefs learners and teachers of English as a second language hold about the learning/teaching process. I will start the discussion exposing the reason why more and more researchers are interested in investigating the beliefs system of those involved in the task of learning the English language to show the influence that the beliefs that compose this system have in the way they approach the process of learning a new language. I will next present and discuss some of the main factors that act in the construction of students and teachers´ beliefs and some of the beliefs they hold, not all of which beneficial for the good performance in that process.
Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.
Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is
Full Text Available For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD outcomes (four NCDs and two major clinical risk factors, based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88 and those excluded from the development for use as a completely separated validation sample (median correlation 0.85, demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.
Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve
For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.
Cruz-Roa, Angel; Gilmore, Hannah; Basavanhally, Ajay; Feldman, Michael; Ganesan, Shridar; Shih, Natalie N. C.; Tomaszewski, John; González, Fabio A.; Madabhushi, Anant
With the increasing ability to routinely and rapidly digitize whole slide images with slide scanners, there has been interest in developing computerized image analysis algorithms for automated detection of disease extent from digital pathology images. The manual identification of presence and extent of breast cancer by a pathologist is critical for patient management for tumor staging and assessing treatment response. However, this process is tedious and subject to inter- and intra-reader variability. For computerized methods to be useful as decision support tools, they need to be resilient to data acquired from different sources, different staining and cutting protocols and different scanners. The objective of this study was to evaluate the accuracy and robustness of a deep learning-based method to automatically identify the extent of invasive tumor on digitized images. Here, we present a new method that employs a convolutional neural network for detecting presence of invasive tumor on whole slide images. Our approach involves training the classifier on nearly 400 exemplars from multiple different sites, and scanners, and then independently validating on almost 200 cases from The Cancer Genome Atlas. Our approach yielded a Dice coefficient of 75.86%, a positive predictive value of 71.62% and a negative predictive value of 96.77% in terms of pixel-by-pixel evaluation compared to manually annotated regions of invasive ductal carcinoma.
Mark D McDonnell
Full Text Available Recent advances in training deep (multi-layer architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the 'Extreme Learning Machine' (ELM approach, which also enables a very rapid training time (∼ 10 minutes. Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random 'receptive field' sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems.
Keywords: academic emotion; belief; causal attribution; statistical validation; students' conceptions of learning ... Sadi & Lee, 2015), through their effect on motivation and learning strategies .... to understand why they may or may not be doing.
Renee Michelle Goertzen
Full Text Available As part of a long-term program to develop effective, research-based professional development programs for physics graduate student teaching assistants (TAs, we first identify their current classroom practices and why they engage in these practices. In this paper, we identify a set of teaching practices we call “focusing on indicators,” which occurs when TAs use signs such as key words or diagrams as evidence that students understand the target idea; these indicators are more superficial than a detailed explanation. Our primary finding is that although the three TAs discussed here share a common behavior, the beliefs and motivations that underlie this behavior vary. We argue that TA professional development focused on changing these TAs’ focus-on-indicator behavior is unlikely to be effective. Instead, responsive TA professional development will need to address the TAs’ beliefs that guide the observed classroom behavior.
Kardash, CarolAnne M.; Howell, Karen L.
Investigates effects of epistemological beliefs and topic-specific beliefs on undergraduates' (N=40) cognitive and strategic processing of a dual-positional text. Findings reveal that epistemological beliefs about the speed of learning affected the overall number of cognitive processes exhibited, whereas topic-specific beliefs interacted with the…
Douglas, P K; Harris, Sam; Yuille, Alan; Cohen, Mark S
Machine learning (ML) has become a popular tool for mining functional neuroimaging data, and there are now hopes of performing such analyses efficiently in real-time. Towards this goal, we compared accuracy of six different ML algorithms applied to neuroimaging data of persons engaged in a bivariate task, asserting their belief or disbelief of a variety of propositional statements. We performed unsupervised dimension reduction and automated feature extraction using independent component (IC) analysis and extracted IC time courses. Optimization of classification hyperparameters across each classifier occurred prior to assessment. Maximum accuracy was achieved at 92% for Random Forest, followed by 91% for AdaBoost, 89% for Naïve Bayes, 87% for a J48 decision tree, 86% for K*, and 84% for support vector machine. For real-time decoding applications, finding a parsimonious subset of diagnostic ICs might be useful. We used a forward search technique to sequentially add ranked ICs to the feature subspace. For the current data set, we determined that approximately six ICs represented a meaningful basis set for classification. We then projected these six IC spatial maps forward onto a later scanning session within subject. We then applied the optimized ML algorithms to these new data instances, and found that classification accuracy results were reproducible. Additionally, we compared our classification method to our previously published general linear model results on this same data set. The highest ranked IC spatial maps show similarity to brain regions associated with contrasts for belief > disbelief, and disbelief < belief. Copyright © 2010 Elsevier Inc. All rights reserved.
Full Text Available Current transformer (CT saturation is one of the significant problems for protection engineers. If CT saturation is not tackled properly, it can cause a disastrous effect on the stability of the power system, and may even create a complete blackout. To cope with CT saturation properly, an accurate detection or classification should be preceded. Recently, deep learning (DL methods have brought a subversive revolution in the field of artificial intelligence (AI. This paper presents a new DL classification method based on unsupervised feature extraction and supervised fine-tuning strategy to classify the saturated and unsaturated regions in case of CT saturation. In other words, if protection system is subjected to a CT saturation, proposed method will correctly classify the different levels of saturation with a high accuracy. Traditional AI methods are mostly based on supervised learning and rely heavily on human crafted features. This paper contributes to an unsupervised feature extraction, using autoencoders and deep neural networks (DNNs to extract features automatically without prior knowledge of optimal features. To validate the effectiveness of proposed method, a variety of simulation tests are conducted, and classification results are analyzed using standard classification metrics. Simulation results confirm that proposed method classifies the different levels of CT saturation with a remarkable accuracy and has unique feature extraction capabilities. Lastly, we provided a potential future research direction to conclude this paper.
Full Text Available In this paper the authors present a brief overview of belief change, a research area concerned with the question of how a rational agent ought to change its mind in the face of new, possibly conflicting, information. The authors limit themselves...
This mixed-methods study investigates language learners' intention to attend a class and learn a foreign language in face-to-face and online settings using Ajzen's theory of planned behavior (TPB). The data were collected using interviews, questionnaires, and treatments with participants in two groups: a face-to-face language learning (FLL) group…
Kakew, Jiraporn; Damnet, Anamai
This classroom based research of a learning strategies model was designed to investigate its application in a mixed-ability classroom. The study built on Oxford's language learning strategies model (1990, 2001) and fulfilled it with rhetorical strategies to accommodate challenges encountered in the paradigm of English as an international language…
Chen, Charlie C.; Vannoy, Sandra
Voice over Internet Protocol- (VoIP) enabled online learning service providers struggling with high attrition rates and low customer loyalty issues despite VoIP's high degree of system fit for online global learning applications. Effective solutions to this prevalent problem rely on the understanding of system quality, information quality, and…
When speaking about the appropriate age for the beginning of L2 learning, experts' opinions slightly differ, but mostly they specify the time to start learning L2 from the age of 4 to the age of 8 (Marjanovič Umek, 2009). In the literature we can find many reasons for starting to learn a foreign language at an early age, but most popular is the critical period hypothesis that claims that there is an ideal time window to acquire language in a linguistically rich environment, after which furth...
Extreme overvalued beliefs (EOB) are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry) refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People's Temple, Heaven's Gate, Aum Shinrikyo, and Islamic State (ISIS) and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience.
Educators around the world participate in virtual communities, social media sites, and online networks in order to gain support and ideas for improving their practice. Many researchers have explored how and why teachers participate in these online spaces; however, there is limited research on how participation might impact teaching and learning.…
With the rapid development of information and technology, language learners have more ways to acquire the target language. Recently, WILL has gained popularity, for informal web-based learning of English has been depicted as a process driven by the purpose of communication. Thus, teachers have many challenges when teaching learners who have…
de Caso, Ana Maria; Garcia, Jesus Nicasio; Diez, Carmen; Robledo, Patricia; Alvarez, Maria Lourdes
Introduction: The use of self efficacy has been suggested as an effective classroom intervention procedure. The present research examined the use of self-efficacy training on the writing of Spanish elementary student with learning disabilities. Objectives: We present a research study focused on the improvement of the writing product and the…
Ong, Caroline C.; Dodds, Agnes; Nestel, Debra
Surgeons require advanced psychomotor skills, critical decision-making and teamwork skills. Much of surgical skills training involve progressive trainee participation in supervised operations where case variability, operating team interaction and environment affect learning, while surgical teachers face the key challenge of ensuring patient…
Full Text Available in the presence of Vacuity. 3.2 Partial meet theory contraction The preceding construction works equally well when B is taken to be a theory K. But in this case, since the input to contraction is a theory, we should expect the output to be a theory too... that is analogous to that of a belief set K in theory change. Intuitively, E is the ?current? set of expectations of the agent, and the plausible consequences of a sentence ? are those sentences ? for which ? |?? holds. The set of expectations E is not explicitly...
Kraker - de Pauw, Emmy; van Wesel, F.; Verwijmeren, Thijs; Denessen, Eddie; Krabbendam, Lydia
Teacher beliefs influence student behaviour and learning outcomes. Little is known about the role of specific teacher characteristics (e.g., gender and teaching domain) in the formation of these beliefs. In the current study, three versions of the Implicit Association Test (IAT) were used to assess
Kraker-Pauw, E. de; Wesel, F. van; Verwijmeren, T.; Denessen, E.J.P.G.; Krabbendam, L.
Teacher beliefs influence student behaviour and learning outcomes. Little is known about the role of specific teacher characteristics (e.g., gender and teaching domain) in the formation of these beliefs. In the current study, three versions of the Implicit Association Test (IAT) were used to assess
Levin, Scott; Toerper, Matthew; Hamrock, Eric; Hinson, Jeremiah S; Barnes, Sean; Gardner, Heather; Dugas, Andrea; Linton, Bob; Kirsch, Tom; Kelen, Gabor
Standards for emergency department (ED) triage in the United States rely heavily on subjective assessment and are limited in their ability to risk-stratify patients. This study seeks to evaluate an electronic triage system (e-triage) based on machine learning that predicts likelihood of acute outcomes enabling improved patient differentiation. A multisite, retrospective, cross-sectional study of 172,726 ED visits from urban and community EDs was conducted. E-triage is composed of a random forest model applied to triage data (vital signs, chief complaint, and active medical history) that predicts the need for critical care, an emergency procedure, and inpatient hospitalization in parallel and translates risk to triage level designations. Predicted outcomes and secondary outcomes of elevated troponin and lactate levels were evaluated and compared with the Emergency Severity Index (ESI). E-triage predictions had an area under the curve ranging from 0.73 to 0.92 and demonstrated equivalent or improved identification of clinical patient outcomes compared with ESI at both EDs. E-triage provided rationale for risk-based differentiation of the more than 65% of ED visits triaged to ESI level 3. Matching the ESI patient distribution for comparisons, e-triage identified more than 10% (14,326 patients) of ESI level 3 patients requiring up triage who had substantially increased risk of critical care or emergency procedure (1.7% ESI level 3 versus 6.2% up triaged) and hospitalization (18.9% versus 45.4%) across EDs. E-triage more accurately classifies ESI level 3 patients and highlights opportunities to use predictive analytics to support triage decisionmaking. Further prospective validation is needed. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.
Lindsay R. Owings
Full Text Available Accurate measurement of key constructs is essential to the continued development of Rational-Emotive Behavior Therapy (REBT. The General Attitude and Belief Scale (GABS, a contemporary inventory of rational and irrational beliefs based on current REBT theory, is one of the most valid and widely used instruments available, and recent research has continued to improve its psychometric standing. In this study of 544 students, item response theory (IRT methods were used (a to identify the most informative item in each irrational subscale of the GABS, (b to determine the level of irrationality represented by each of those items, and (c to suggest a condensed form of the GABS for further study with clinical populations. Administering only the most psychometrically informative items to clients could result in economies of time and effort. Further research based on the scaling of items could clarify the specific patterns of irrational beliefs associated with particular clinical syndromes.
International audience; This qualitative study, aimed to analyze eight French-speaking learners' beliefs about English and English language learning. The data were obtained via semi-structured interviews. The study drew on Weiner's attribution theory of achievement motivation and Bandura's self-efficacy theory. The novelty about this research is the employment of an attributional analysis framework to study and explain the learners' stated beliefs about English and English language learning.
Kouritzin, Sandra; Nakagawa, Satoru
We report on international research that compares linguistic ecosystems, that is, socially constructed public attitudes and ideologies concerned with foreign-language (FL) learning, in Canada and Japan. Analyzing responses to three interview questions from 125 interviews with five categories of respondent in each country, we suggest that there are…
Baratta Posada, Ana Elisa
Semiotic paradigm and Carspecken's (1996) critical ethnography were used in a qualitative research study of elementary teachers' beliefs about minority and Latino/a immigrant students and the role of life experiences, culture and Umwelt in the formation and influence of beliefs. The participants were a kindergarten, first grade, and second grade…
Palmer, John; Mohr, Christine; Krummenacher, Peter; Brugger, Peter
Previous research suggests that implicit sequence learning (ISL) is superior for believers in the paranormal and individuals with increased cerebral dopamine. Thirty-five healthy participants performed feedback-guided anticipations of four arrow directions. A 100-trial random sequence preceded two 100-trial biased sequences in which visual targets (arrows) on trial t tended to be displaced 90 degrees clockwise (CW) or counter-clockwise (CCW) from those on t - 1. ISL was defined as a positive change during the course of the biased run in the difference between pro-bias and counter-bias responses. It was hypothesized that this difference would be greater for believers in the paranormal than for skeptics, for those who received dopamine than for those who received placebo, and for believers who received dopamine than for the other groups. None of the hypotheses were supported by the data. It is suggested that a simple binary guessing task with a focus on prediction accuracy during early trials should be considered for future explorations.
for educators. Within each of these areas there are specific explorations that examine important areas such as, the roles of beliefs in teaching and learning, the impact of beliefs on student achievement, and ways in which beliefs are connected to teacher actions in the classroom. Throughout all...... of these discussions, there is a focus on international perspectives. Those reading this book can use the research presented to consider how to confront, challenge, and cultivate beliefs during the teacher professional development process....
Blanco, Mariana; Engelmann, Dirk; Koch, Alexander
Belief elicitation in economics experiments usually relies on paying subjects according to the accuracy of stated beliefs in addition to payments for other decisions. Such incentives, however, allow risk-averse subjects to hedge with their stated beliefs against adverse outcomes of other decisions......-belief elicitation treatment using a financial investment frame, where hedging arguably would be most natural....
Humans may be distinguished from all other animals in having beliefs about the causal interaction of physical objects. Causal beliefs are a developmental primitive in human children; animals, by contrast, have very few causal beliefs. The origin of human causal beliefs comes from the evolutionary advantage it gave in relation to complex tool making and use. Causal beliefs gave rise religion and mystical thinking as our ancestors wanted to know the causes of events that affected their lives.
Sheehy, Kieron; Budiyanto; Kaye, Helen; Rofiah, Khofidotur
A growing number of children with intellectual disabilities attend inclusive schools in Indonesia. Previous research has suggested that teachers' type of school and experience influences their beliefs about inclusive education. This research collected questionnaire data from 267 Indonesian teachers and compared the responses from those working in inclusive, special and regular schools regarding their epistemological and pedagogical beliefs. The results showed that teachers in inclusive schools expressed stronger social constructivist beliefs than those in other schools. However, it was teachers' epistemological beliefs, rather than their type of school or experience, which were the significant predictor of their beliefs about inclusive education. The findings suggest that international epistemological research needs to have a more nuanced view of constructivist models of learning to better understand and inform how inclusive pedagogy is being enacted in different contexts.
Exploring Conceptions about Writing and Learning: Undergraduates' Patterns of Beliefs and the Quality of Academic Writing (Acercamiento a las concepciones sobre la escritura y el aprendizaje: patrones de creencias de los universitarios y la calidad de su redacción académica)
Martínez-Fernández, J. R.; Corcelles, M.; Bañales, G.; Castelló, M.; Gutiérrez-Braojos, C.
Introduction: In this study, the conceptions of learning and writing of a group of undergraduates enrolled in a teacher education programme were identified. The relationship between them were analysed, and a set of patterns of beliefs about learning and writing were defined. Finally, the relation between these patterns and the quality of a text…
Lodewyk, Ken R.
Students with differing profiles of epistemological beliefs--their beliefs about personal epistemology, intelligence, and learning--vary in thinking, reasoning, motivation, and use of strategies while working on academic tasks, each of which affect learning. This study examined students' epistemological beliefs according to gender, school…
Martin, Anita; Park, Soonhye; Hand, Brian
This qualitative case study examined the process of change in an experienced elementary teacher's belief structure during implementation of an inquiry-based science program. Difficulties generally associated with ascertaining beliefs were minimized by using Leatham's (Journal of Mathematics Teacher Education, 9, 91-102 (2006) Sensible System Framework, enabling researchers to obtain rich descriptions of the teacher's belief structure by focusing on words (professed beliefs), intentions (intended beliefs), and actions (enacted beliefs). Models were constructed of the teacher's belief structure before and after implementation of the Science Writing Heuristic (SWH) approach (Hand et al. International Journal of Science Education, 26(2), 131-149, 2004), an inquiry-based approach to teaching science. Key beliefs for this teacher were related to how students learn, goals for teaching science, focus of instruction, and roles of teacher and student. Ultimately, the teacher shifted her professed, intended, and enacted beliefs resulting in a shift from a teacher-centered to a student-centered classroom. Findings support Thagard's Coherence Theory of Justification (2002), positing that change in one belief creates a state of disequilibrium that must be alleviated by changing/realigning other beliefs in order to re-establish coherence in the overall belief structure. This research focus is distinct from the general trend in teacher beliefs research in important ways. Most significant is that this study was not focused on the traditional two lists—those beliefs that were consistent with practice and those that were inconsistent with practice—but instead focused on the entwined nature of beliefs and practice and have shown that a teacher's practice can be viewed as their enacted beliefs, an integral part of the teacher's overall belief structure.
This study examines the effect of three different computer integration models on pre-service mathematics teachers' beliefs about using computers in mathematics education. Participants included 104 pre-service mathematics teachers (36 second-year students in the Computer Oriented Model group, 35 fourth-year students in the Integrated Model (IM)…
Goddard, Roger; Goddard, Yvonne; Kim, Eun Sook; Miller, Robert
Principals' instructional leadership may support the degree to which teachers work together to improve instruction, and together leadership and teacher collaboration may contribute to school effectiveness by strengthening collective efficacy beliefs. We found a significant direct effect of leadership on teacher collaboration. Further, leadership…
Foss, Nicolai Juul
While (managerial) beliefs are central to many aspects of strategic organization, interactive beliefs are almost entirely neglected, save for some game theory treatments. In an increasingly connected and networked economy, firms confront coordination problems that arise because of network effects....... The capability to manage beliefs will increasingly be a strategic one, a key source of wealth creation, and a key research area for strategic organization scholars.......While (managerial) beliefs are central to many aspects of strategic organization, interactive beliefs are almost entirely neglected, save for some game theory treatments. In an increasingly connected and networked economy, firms confront coordination problems that arise because of network effects...
Tobacyk, Jerome J.; Tobacyk, Zofia Socha
Uses Social Learning Theory to compare 149 university students from Poland with 136 university students from the southern United States for belief-based personality constructs and personality correlates of paranormal beliefs. As hypothesized, Poles reported a more external locus of control and significantly greater endorsement of irrational…
Determine the Effectiveness of Learning of Coping Strategies with Irrational Beliefs Based on the Theory of Rational-Emotional Alice on Attitudes to Communicate Before Married Female High School Students in Yazd- Iran
Maryam Forat Yazdi
Full Text Available Introduction This research was done with the objective of "Determine the effectiveness of learning coping strategies with Irrational Beliefs based on the theory of rational-emotional Alice on students’ attitude toward premarital relations in Yazd city". Materials and Methods In this semi experimental research 60 female students of Yazd-Iran, selected by using of Cochran’s formula and divided in two groups of control (30 persons and experiment (30 persons randomly. Learning of coping strategies with Irrational beliefs based on the theory of rational-emotional Alice during the 8 sessions of 90 minutes was conducted on experiment group, and the control group did not training; then post-test was conducted in two groups. Also, analysis of covariance (ANCOVA used in order to data analysis in descriptive statistics and inferential statistics. Results The adjusted mean attitude scores of the relationship with the opposite sex in control group, on the pre-test and post-test was 51.27+12.16, 50.30+14.46 and in experimental group was 69.53+8.91, 43.63+10.96 respectively. The result Alice rational-emotional treatment method is effective on attitude to relationship before marriage of high school girls (P
Sheila M Reynolds
Full Text Available DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence-301 base pairs, centered at the position to be scored-with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the
Reynolds, Sheila M; Bilmes, Jeff A; Noble, William Stafford
DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence-301 base pairs, centered at the position to be scored-with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the bulk of the
Reynolds, Sheila M.; Bilmes, Jeff A.; Noble, William Stafford
DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence—301 base pairs, centered at the position to be scored—with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the bulk of the
Combining research in physical chemistry and chemical education: Part A. The femtosecond molecular dynamics of small gas-phase anion clusters. Part B. Surveying student beliefs about chemistry and the development of physical chemistry learning tutorials
This dissertation combines work in the areas of experimental physical chemistry and chemical education. In the area of physical chemistry, femtosecond pump-probe spectroscopy is used to interrogate the time-dependence for energy redistribution, solvent reorientation, and dissociation dynamics in small gas-phase anion clusters. The chemical education research addressed in this manuscript include the development and validation of a survey to measure students' beliefs about chemistry and the learning of chemistry and the development and testing of learning tutorials for use in undergraduate physical chemistry courses in thermodynamics and kinetics. In the first part of this dissertation, the Cu(CD3OD) dynamics are investigated using a combination of femtosecond pump-probe experiments and ab initio calculations. Dissociation of this complex into Cu and CD3OD occurs on two distinct time scales: 3 and 30 ps, which arise, respectively, from the coupling of intermolecular solvent rotations and excited methyl rotor rotation into the Cu-O dissociation component upon electron photodetachment of the precursor anion. In the second part of this dissertation, the time-resolved recombination of photodissociated IBr-(CO2)n (n = 5 - 10) cluster anions is investigated. Upon excitation to the A' 2pi 1/2 state of the chromophore, the bare anion results in I- and Br products, upon solvation with CO2, the IBr- chromophore regains near-IR absorption after recombination and vibrational relaxation on the ground electronic state. The recombination times vary with the number of solvent molecules from 12 ps for n = 5 to 900 ps for n = 10. Extensive electronic structure and non-adiabatic molecular dynamic simulations provide a framework to understand this behavior. In the third part of this dissertation, the modification and validation of the Colorado Learning Attitudes about Science Survey (CLASS) for use in chemistry is presented in detail. The CLASS survey is designed to measure student
Full Text Available The “least absolute shrinkage and selection operator” (Lasso method has been adapted recently for network-structured datasets. In particular, this network Lasso method allows to learn graph signals from a small number of noisy signal samples by using the total variation of a graph signal for regularization. While efficient and scalable implementations of the network Lasso are available, only little is known about the conditions on the underlying network structure which ensure network Lasso to be accurate. By leveraging concepts of compressed sensing, we address this gap and derive precise conditions on the underlying network topology and sampling set which guarantee the network Lasso for a particular loss function to deliver an accurate estimate of the entire underlying graph signal. We also quantify the error incurred by network Lasso in terms of two constants which reflect the connectivity of the sampled nodes.
Full Text Available Studies show that human resources development through workplace training is one of the major investments in the workforce in today’s globalized and challenging market. As training motivation influences employees’ preparation for the workplace training, their respond to the programme, their learning outcome, their performance levels, and use of acquired knowledge and skills in their workplace it seems logical to investigate and determine antecedents of training motivation. The aim of this study was to examine the relationship between the concepts of epistemological beliefs, training motivation and the actual participation in the workplace training. We predicted that epistemological beliefs would have an effect on training motivation and actual participation on the workplace training and that there would be a positive relationship between the concepts, meaning that the more sophisticated epistemological beliefs would lead to higher motivation and participation. To test the epistemological beliefs, the Epistemic Belief Inventory (Schraw, Bendixen & Dunkle, 2002 was used and adjusted to the workplace setting. Then the results were compared to employees’ training motivation, which was measured with a questionnaire made by authors of the present study, and employees’ actual number of training hours annually. The results confirmed the relationship between the concepts as well as a significant predicting value of epistemological beliefs on motivation and actual participation. Epistemic Belief Inventory did not yield expected results reported by the authors of the instrument therefore the limitations, possible other interpretations and suggested further exploration are discussed.
Perkins, Katherine K.; Gratny, Mindy
In this paper, we examine the correlation between students' beliefs upon entering college and their likelihood of continuing on to become a physics major. Since 2004, we have collected CLASS survey and self-reported level-of-interest responses from students in the first-term, introductory calculus-based physics course (N>2500). Here, we conduct a retrospective analysis of students' incoming CLASS scores and level of interest, comparing those students who go on to become physics majors with those who do not. We find the incoming CLASS scores and reported interest of these future physics majors to be substantially higher than the class average, indicating that these students enter their first college course already having quite expert-like beliefs. The comparative differences are much smaller for grades, SAT score, and university predicted-GPA.
Rottman, Benjamin Margolin; Marcum, Zachary A; Thorpe, Carolyn T; Gellad, Walid F
Non-adherence to medications is one of the largest contributors to sub-optimal health outcomes. Many theories of adherence include a 'value-expectancy' component in which a patient decides to take a medication partly based on expectations about whether it is effective, necessary, and tolerable. We propose reconceptualising this common theme as a kind of 'causal learning' - the patient learns whether a medication is effective, necessary, and tolerable, from experience with the medication. We apply cognitive psychology theories of how people learn cause-effect relations to elaborate this causal-learning challenge. First, expectations and impressions about a medication and beliefs about how a medication works, such as delay of onset, can shape a patient's perceived experience with the medication. Second, beliefs about medications propagate both 'top-down' and 'bottom-up', from experiences with specific medications to general beliefs about medications and vice versa. Third, non-adherence can interfere with learning about a medication, because beliefs, adherence, and experience with a medication are connected in a cyclic learning problem. We propose that by conceptualising non-adherence as a causal-learning process, clinicians can more effectively address a patient's misconceptions and biases, helping the patient develop more accurate impressions of the medication.
Palis, Leila Ann
It was not known if and to what extent there was a relationship between the degree to which community college students believed that learning was enhanced when teachers tailored instruction to individual learning styles and student perceived academic locus of control (PAC). Learning styles theory and locus of control theory formed the theoretical…
Yang, Xinrong; Leung, Frederick K. S.
This paper investigated pre-service mathematics teachers' mathematics beliefs, beliefs about information and communication technology (ICT), and their relationships. 787 pre-service mathematics teachers in China completed a survey questionnaire measuring their beliefs about the nature of mathematics, beliefs about mathematics learning and…
I defend the view that we act “under the guise of the good.” More specifically, I argue that an intention to do something is a belief that one ought to do it. I show how conflicts in intention and belief, as well as more complex impairments in these states, account for the central problem cases: akrasia in belief and intention, apparently unintelligible choices, and lack of motivation or accidie.
Rationality of a player is determined by comparing her actual expected payoff to her expected payoff when her strategy is changed , while her beliefs —and...reduced strategies, and it is possible that under such conditions, beliefs about other players’ reduced strategies change as well. Thus, independence...assumptions, whether they concern observability of moves or subjective beliefs of any other kind, can be all accommodated by changing the informational
Bandura, Albert; And Others
Analyzed the psychosocial influences through which efficacy beliefs affect academic achievement. Found that parents' sense of academic efficacy and aspirations for their children, children's beliefs in their efficacy to regulate their own learning and academic attainments, children's perceived social efficacy and ability to manage peer pressure,…
Palraj, Shalini; DeWitt, Dorothy; Alias, Norlidah
Problem solving is the highest level of cognitive skill. However, this skill seems to be lacking among secondary school students. Teachers' beliefs influence the instructional strategies used for students' learning. Hence, it is important to understand teachers' beliefs so as to improve the processes for teaching problem solving. The purpose of…
Berkowski, Monisha; MacDonald, Douglas A
Belief in the paranormal is fairly prevalent in the general population. Previous research has shown a link between several personological characteristics and paranormal beliefs. The current study attempted to further investigate this link by replicating previous models that have shown a link between childhood trauma, fantasy proneness, and paranormal beliefs. In addition, the study attempted to expand on this model by including other variables such as stigma, resiliency, and coping style. The study used a sample of 198 undergraduate students. A significant correlation between trauma and paranormal beliefs was found. Partial correlations and path analyses revealed that fantasy proneness and avoidant coping style fully mediate the relationship between trauma and paranormal beliefs. The results imply that researchers need to take into account how a person responds to trauma via the development of coping strategies to accurately understand any observed relationship between trauma and paranormal beliefs.
Van Buskirk, R.D.; Marcus, P.S.
We present an exponentially accurate boundary integral method for calculation the equilibria and dynamics of piece-wise constant distributions of potential vorticity. The method represents contours of potential vorticity as a spectral sum and solves the Biot-Savart equation for the velocity by spectrally evaluating a desingularized contour integral. We use the technique in both an initial-value code and a newton continuation method. Our methods are tested by comparing the numerical solutions with known analytic results, and it is shown that for the same amount of computational work our spectral methods are more accurate than other contour dynamics methods currently in use
Rauff, James V.
Discusses errors made by remedial intermediate algebra students in factoring polynomials in light of student definitions of factoring. Found certain beliefs about factoring to logically imply many of the errors made. Suggests that belief-based teaching can be successful in teaching factoring. (16 references) (Author/MKR)
Full Text Available In point of principle, Christianity does not give room for any belief in fate. Astrology, horoscopes, divination, etc., are strictly rejected. Belief in fate never disappeared in Christian countries, nor did it in Scandinavia in Christian times. Especially in folklore we can find it at any period: People believed in an implacable fate. All folklore is filled up with this belief in destiny. Nobody can escape his fate. The future lies in the hands of fate, and the time to come takes its form according to inscrutable laws. The pre-Christian period in Scandinavia, dominated by pagan Norse religion, and the secularized epoch of the 20th century, however, show more distinctive and more widespread beliefs in fate than does the Christian period. The present paper makes a comparison between these forms of belief.
Shanina Sharatol Ahmad Shah
Full Text Available Research has shown that teachers’ beliefs on teaching and learning exert an influence on their actual classroom practices. In the teaching of English pronunciation, teachers’ beliefs play a crucial role in the choice of pronunciation components taught in the ESL classrooms. This paper explores teachers’ beliefs about teaching English pronunciation in Malaysian classrooms and the extent to which these beliefs influenced the teachers’ classroom instructions. Employing a multiple case study of five ESL teachers in secondary schools, this study investigated the beliefs the teachers have formed about pronunciation focused areas and classroom practices in teaching English pronunciation. Data were collected through actual classroom observations and semi-structured interviews with the teachers and students. The findings of the study found that ESL teachers seem to believe that pronunciation skills are to be taught integratedly with other English language skills. Results also indicate a discrepancy between these teachers’ beliefs on the focused areas of pronunciation and the stated curriculum specifications. Additionally, the ESL teachers seem to have vague and contradictory beliefs about pronunciation focused areas. These beliefs are based on their previous language learning and professional experience as well as other contextual factors such as examination demands and time constraints. As a result, these beliefs lead to the pronunciation component being neglected despite it being stipulated by the curriculum.
Schumann, Scott; Sibthorp, Jim
Accuracy in emerging outdoor educators' teaching self-efficacy beliefs is critical to student safety and learning. Overinflated self-efficacy beliefs can result in delayed skilled development or inappropriate acceptance of risk. In an outdoor education context, neglecting the accuracy of teaching self-efficacy beliefs early in an educator's…
Nix, John-Michael L.; Tseng, Wen-Ta
The present research aims to identify the underlying English listening belief structure of English-as-a-foreign-language (EFL) learners, thereby informing methodologies for subsequent analysis of beliefs with respect to listening achievement. Development of a measurement model of English listening learning beliefs entailed the creation of an…
Evans, Brian R.; Leonard, Jacqueline; Krier, Kathleen; Ryan, Steve
Beliefs about teaching mathematics and urban students' ability to learn mathematics are often overlooked in the discourse on highly qualified teachers. Altering teacher experiences has the potential to change their beliefs. It was found in this qualitative case study that preservice teachers' beliefs about teaching mathematics to urban students…
Full Text Available People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates with trials with bad news (worse-than-expected base rates. After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on
communication practices, it is argued that deep beliefs may constitute drivers of hype that are particularly difficult to deal with. To participants in science communication, the discouragement of hype, viewed as a practical–ethical challenge, can be seen as a learning exercise that includes critical attention......; gene therapy was not universally hyped. Against that background, attention is directed towards another area of variation in the material: different basic assumptions about science and scientists. Exploring such culturally rooted assumptions and beliefs and their possible significance to science...
Full Text Available Extreme overvalued beliefs (EOB are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People’s Temple, Heaven’s Gate, Aum Shinrikyo, and Islamic State (ISIS and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience.
Extreme overvalued beliefs (EOB) are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry) refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People’s Temple, Heaven’s Gate, Aum Shinrikyo, and Islamic State (ISIS) and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience. PMID:29329259
Henry, Alastair; Cliffordson, Christina
English is today learnt in multitudes of settings worldwide, making it difficult to characterize relationships between motivation and context in generalized terms (Ushioda 2013). In settings where students have extensive encounters with English outside school, a reluctance to invest effort in formal learning has been observed. To investigate ways…
Sandoval Brotons, Alfonso Victor
Bilingualism and its reference methodology: CLIL are spreading at a very fast pace all through educative systems from some years on. The young status of bilingual programmes leads to little research about how bilingualism is influencing real learning contexts and which factors play important roles in that influence. In this way, this study aims to…
Armstrong, Ann W.
The purpose of this study was to gain an understanding of what e-Learning executives believe are the critical success factors for companies to successfully deliver training and education over the world-wide web. The study was a qualitative, multiple-case study design including in-depth, semi-structured interviews that incorporated verbal critical…
The capability of changing beliefs upon new information in a rational and efficient way is crucial for an intelligent agent. Belief change therefore is one of the central research fields in Artificial Intelligence (AI) for over two decades. In the AI literature, two different kinds of belief change operations have been intensively investigated: belief update, which deal with situations where the new information describes changes of the world; and belief revision, which assumes the world is st...
Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.
An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.
Al-Maadadi, Fatima; Ihmeideh, Fathi
Writing often begins during the very early years of childhood; however, some children first learn writing when they begin attending school. Teachers' beliefs about early writing development can influence when and how children learn to write. The purpose of this study was to determine kindergarten teachers' beliefs about the development of…
Kienhues, Dorothe; Bromme, Rainer; Stahl, Elmar
Background: Previous research has shown that sophisticated epistemological beliefs exert a positive influence on students' learning strategies and learning outcomes. This gives a clear educational relevance to studies on the development of methods for promoting a change in epistemological beliefs and making them more sophisticated. Aims: To…
Zhao, Ke; Zhang, Jie; Du, Xiangyun
This study adopted a longitudinal retrospective case study approach to investigate Chinese business students’ transitional learning experience in a problem-based learning (PBL) course with innovative assessment practices. The study focused on students’ beliefs and strategy use in a constructively...... that align social constructivist learning principles with students’ beliefs and strategies. The results also highlight the importance of developing appropriate assessment rubrics to enhance student engagement with PBL learning for improved outcomes....
The article will argue that Charles Sanders Peirce's concepts of the "Dynamics of Belief and Doubt", the "Fixation of Belief" as well as "habits of belief" taken together comprise a theory of learning. The "dynamics of belief and doubt" are Peirce's explanation for the process of changing from one belief to another. Teaching, then, would be an…
Figueiredo, Luis Claudio
A case of hysteria is presented in order to create a frame of reference for the author's approach to the concepts of hope, belief and faith. A difference between hope as a 'sad passion' (which is here called regressive hope) and hope as a principle of mental functioning is established. The concept of hope will at first always be based on beliefs--either beliefs organised in the paranoid-schizoid position (called here fragmented and delusional beliefs)--or those organised from the depressive position (complex systems of beliefs, which end up being dogmatic); the latter typically occur in neurotics. It is suggested here that there is another possibility for hope, which is based on faith. The meaning of faith is considered here externally to the religious sense. The solid establishment of hope as a principle--based on faith--can be viewed as responsible for the opening up of creative potentials and as one of the main aims of analysis. Such an aim, however requires the establishment of a deep relationship, both in theory and in clinical practice, between the Kleinian question of the depressive position and the Freudian question of the Oedipus complex.
Searing, Donald D.; And Others
Assesses the significance of data on childhood political learning to political theory by testing the structuring principle,'' considered one of the central assumptions of political socialization research. This principle asserts that basic orientations acquired during childhood structure the later learning of specific issue beliefs.'' The…
Calvin S. Kalman
Full Text Available This study was based on the hypothesis that students’ epistemological beliefs could become more expertlike with a combination of appropriate instructional activities: (i preclass reading with metacognitive reflection, and (ii in-class active learning that produces cognitive dissonance. This hypothesis was tested through a five-year study involving close to 1000 students at two institutions, in four physics courses. Using an experimental design, data from student interviews, writing product assessments, and the Discipline-Focused Epistemological Beliefs Questionnaire (DFEBQ we demonstrate that the beliefs of novice science learners became more expertlike on 2 of the 4 DFEBQ factors. We conclude that a combination of an activity that gets students to examine textual material metacognitively (Reflective Writing with one or more types of in-class active learning interventions can promote positive change in students’ epistemological beliefs.
Full Text Available Optimists hold positive a priori beliefs about the future. In Bayesian statistical theory, a priori beliefs can be overcome by experience. However, optimistic beliefs can at times appear surprisingly resistant to evidence, suggesting that optimism might also influence how new information is selected and learned. Here, we use a novel Pavlovian conditioning task, embedded in a normative framework, to directly assess how trait optimism, as classically measured using self-report questionnaires, influences choices between visual targets, by learning about their association with reward progresses. We find that trait optimism relates to an a priori belief about the likelihood of rewards, but not losses, in our task. Critically, this positive belief behaves like a probabilistic prior, i.e. its influence reduces with increasing experience. Contrary to findings in the literature related to unrealistic optimism and self-beliefs, it does not appear to influence the iterative learning process directly.
Kalra, Aditi; Seriès, Peggy
Optimists hold positive a priori beliefs about the future. In Bayesian statistical theory, a priori beliefs can be overcome by experience. However, optimistic beliefs can at times appear surprisingly resistant to evidence, suggesting that optimism might also influence how new information is selected and learned. Here, we use a novel Pavlovian conditioning task, embedded in a normative framework, to directly assess how trait optimism, as classically measured using self-report questionnaires, influences choices between visual targets, by learning about their association with reward progresses. We find that trait optimism relates to an a priori belief about the likelihood of rewards, but not losses, in our task. Critically, this positive belief behaves like a probabilistic prior, i.e. its influence reduces with increasing experience. Contrary to findings in the literature related to unrealistic optimism and self-beliefs, it does not appear to influence the iterative learning process directly. PMID:24853098
Vincent, Catherine Van Hulle; Wilkie, Diana J.; Wang, Edward
We evaluated feasibility of the Internet-based Relieve Children's Pain (RCP) protocol to improve nurses’ management of children's pain. RCP is an interactive, content-focused, and Kolb's Experiential Learning Theory-based intervention. Using a one-group, pre/posttest design, we evaluated feasibility of RCP and pre/post difference in scores for nurses’ beliefs, and simulated and actual pain management practices. Twenty-four RNs completed an Internet-based Pain Beliefs and Practices Questionnai...
Tardif, Twila; Wellman, Henry M; Cheung, Kar Man
The present study investigates the performance of 96 Cantonese-speaking three- to five-year-old preschoolers on three false belief tasks - a deceptive object, a change of location, and an unexpected contents task encompassing a variety of task factors. Most importantly, the research examines the possibility that false belief performance depends on specific linguistic factors such as the type of verb used in the test question--an explicitly false vs. a neutral belief verb. Cantonese was chosen as particularly useful for examining this question because it explicitly codes belief status as either neutral (nam5) or false (ji5wai4), and because it offers additional linguistic and cultural contrasts to research conducted on false belief with children learning English and other Indo-European languages. As expected, a strong age effect was found, as well as a significant advantage for children who received the explicit false belief (ji5wai4) wording and for those who were asked to explain rather than predict the protagonist's actions. Interestingly, there was also a strong task difference with children performing better on the deceptive object task than on the other two false belief tasks. We argue that these results point both to universal trajectories in theory of mind development and to interesting, but localized, effects of language and culture on children's false belief understanding.
Sefein, Naim A.
To help social studies classroom teachers present a realistic picture of the Middle Eastern religion of Islam, this article presents an overview of major beliefs and religious practices of Moslems. Information is presented on religious fundamentals, Islam's relationship to Judaism and Christianity, the development of Islam, the role of women, and…
Jost, John T.
People are influenced by second-order beliefs — beliefs about the beliefs of others. New research finds that citizens in the US and China systematically underestimate popular support for taking action to curb climate change. Fortunately, they seem willing and able to correct their misperceptions.
Beliefs of Chilean University English Teachers: Uncovering Their Role in the Teaching and Learning Process (Creencias de profesores universitarios de inglés: descubriendo su papel en el proceso de enseñanza y aprendizaje)
Díaz Larenas, Claudio; Alarcón Hernández, Paola; Vásquez Neira, Andrea; Pradel Suárez, Boris; Ortiz Navarrete, Mabel
Beliefs continue to be an important source to get to know teachers' thinking processes and pedagogical decisions. Research in teachers' beliefs has traditionally come from English-speaking contexts; however, a great deal of scientific work has been written lately in Brazil, Mexico, Colombia, and Argentina. This study elicits 30 Chilean university…
Tripti K. Karekatti
Full Text Available This paper is a part of an ongoing doctoral research on ‘Teacher Talk in ESL Classrooms’. The idea for this was gained through the hypothesis that teachers’ beliefs about English teaching may also mould their talk. The researcher intends here to analyse and comment on teachers’ English teaching beliefs. It is generally accepted that teaching is greatly affected by the belief systems of its practitioners-teachers. Teachers’ beliefs influence their consciousness, teaching attitude, teaching methods and teaching policies, and finally, learners’ development. Horwitz (1987 also states rightly that the formation of teachers’ educational beliefs in language teaching/ learning process will influence, though indirectly, on forming effective teaching methods and will bring about the improvement of learners’ language learning abilities. In Indian context, there is dearth of research evaluating teachers’ beliefs about English teaching. This study explores teachers’ beliefs regarding teaching English to children and tries to explore whether medium of instruction makes any difference in their beliefs. It also intends to determine what similar and different beliefs might be held by in-service teachers from two different mediums. A total of 100 pre-service teachers are the subjects of this study. In order to recognize these teachers’ specific beliefs in a more systematic way, a research instrument, The Questionnaire of Primary School Pre-service English Teachers’ Teaching Beliefs was developed. Almost all of these pre-service teachers expected to have training regarding how to make their talk effective and relevant in classrooms.
Baldridge, Mary Caufield
The overall purpose of this study was to examine the effects of a "growth mindset" intervention on the beliefs about intelligence, effort beliefs, achievement goals, and academic self-efficacy of learning disabled (LD) students with reading difficulties. The treatment group consisted of 12 high school LD students with reading difficulties. This…
Qi, Xin; Zaroff, Charles M.; Bernardo, Allan B. I.
Recent research examining the explanations given by the public (i.e. lay beliefs) for autism spectrum disorder often reveals a reasonably accurate understanding of the biogenetic basis of the disorder. However, lay beliefs often manifest aspects of culture, and much of this work has been conducted in western cultures. In this study, 215…
Page, Randy M; Huong, Nguyen Thanh; Chi, Hoang Khanh; Tien, Truong Quang
Tobacco-related deaths in Vietnam are forecast to climb from 40 000 annually to 70 000 by 2030. Previous research in Western nations has found social factors to be important determinants of adolescent smoking. Because these factors remain unexplored in Vietnamese youth, the purpose of this study was to examine social normative beliefs regarding smoking in a school-based sample of North Vietnamese adolescents and the association of these factors with smoking behavior and susceptibility to smoking. Three measures of normative beliefs regarding smoking were evaluated in cross-sectional surveys of secondary students. Of the 3 measures, parent/peer disapproval was the most consistent normative belief associated with smoking behavior and susceptibility to smoking. Youth smoking prevention programs should consider assessing and taking into account normative beliefs and develop strategies that provide accurate information about the actual prevalence of smoking, the types of individuals who smoke, and approval/disapproval of smoking by parents and peers.
R Kelly Garrett
Full Text Available Widespread misperceptions undermine citizens' decision-making ability. Conclusions based on falsehoods and conspiracy theories are by definition flawed. This article demonstrates that individuals' epistemic beliefs-beliefs about the nature of knowledge and how one comes to know-have important implications for perception accuracy. The present study uses a series of large, nationally representative surveys of the U.S. population to produce valid and reliable measures of three aspects of epistemic beliefs: reliance on intuition for factual beliefs (Faith in Intuition for facts, importance of consistency between empirical evidence and beliefs (Need for evidence, and conviction that "facts" are politically constructed (Truth is political. Analyses confirm that these factors complement established predictors of misperception, substantively increasing our ability to explain both individuals' propensity to engage in conspiracist ideation, and their willingness to embrace falsehoods about high-profile scientific and political issues. Individuals who view reality as a political construct are significantly more likely to embrace falsehoods, whereas those who believe that their conclusions must hew to available evidence tend to hold more accurate beliefs. Confidence in the ability to intuitively recognize truth is a uniquely important predictor of conspiracist ideation. Results suggest that efforts to counter misperceptions may be helped by promoting epistemic beliefs emphasizing the importance of evidence, cautious use of feelings, and trust that rigorous assessment by knowledgeable specialists is an effective guard against political manipulation.
Brauer, Heike; Wilde, Matthias
Learning beliefs influence learning and teaching. For this reason, teachers and teacher educators need to be aware of them. To support students' knowledge construction, teachers must develop appropriate learning and teaching beliefs. Teachers appear to have difficulties when analysing students' learning. This seems to be due to the inability to differentiate the beliefs about their students' learning from those about their own learning. Both types of beliefs seem to be intertwined. This study focuses on whether pre-service teachers' beliefs about their own learning are identical to those about their students' learning. Using a sample of pre-service teachers, we measured general beliefs about "constructivist" and "transmissive" learning and science-specific beliefs about "connectivity" and "taking pre-concepts into account". We also analysed the development of these four beliefs during teacher professionalisation by comparing beginning and advanced pre-service teachers. Our results show that although pre-service teachers make the distinction between their own learning and the learning of their students for the general tenets of constructivist and transmissive learning, there is no significant difference for science-specific beliefs. The beliefs pre-service teachers hold about their students' science learning remain closely tied to their own.
Christensen, Peter Ove; Qin, Zhenjiang
In an incomplete market with heterogeneous prior beliefs, we show public information can have a substantial impact on the ex ante cost of capital, trading volume, and investor welfare. The Pareto effcient public information system is the system enjoying the maximum ex ante cost of capital...... and the maximum expected abnormal trading volume. Imperfect public information increases the gains-to-trade based on heterogeneously updated posterior beliefs. In an exchange economy, this leads to higher growth in the investors' certainty equivalents and, thus, a higher equilibrium interest rate, whereas the ex...... ante risk premium is unaffected by the informativeness of the public information system. Similar results are obtained in a production economy, but the impact on the ex ante cost of capital is dampened compared to the exchange economy due to welfare improving reductions in real investments to smooth...
Heinzle, J Mark; Uggla, Claes
We consider the dynamics towards the initial singularity of Bianchi type IX vacuum and orthogonal perfect fluid models with a linear equation of state. Surprisingly few facts are known about the 'Mixmaster' dynamics of these models, while at the same time most of the commonly held beliefs are rather vague. In this paper, we use Mixmaster facts as a base to build an infrastructure that makes it possible to sharpen the main Mixmaster beliefs. We formulate explicit conjectures concerning (i) the past asymptotic states of type IX solutions and (ii) the relevance of the Mixmaster/Kasner map for generic past asymptotic dynamics. The evidence for the conjectures is based on a study of the stochastic properties of this map in conjunction with dynamical systems techniques. We use a dynamical systems formulation, since this approach has so far been the only successful path to obtain theorems, but we also make comparisons with the 'metric' and Hamiltonian 'billiard' approaches.
Cromer, Lisa DeMarni; Goldsmith, Rachel E.
Child sexual abuse myths comprise incorrect beliefs regarding sexual abuse, victims, and perpetrators. Relations among myth acceptance, responses to disclosure, legal decisions, and victims' subsequent psychological and health outcomes underscore the importance of understanding child sexual abuse myths. Despite accurate knowledge regarding child…
Borgerding, Lisa A.; Deniz, Hasan; Anderson, Elizabeth Shevock
Evolutionary theory is central to biology, and scientifically accurate evolution instruction is promoted within national and state standards documents. Previous literature has identified students' epistemological beliefs as potential predictors of evolution acceptance. The present work seeks to explore more directly how student views of evolution…
Misfeldt, Morten; Thomas Jankvist, Uffe; Sánchez Arguilar, Mario
In the article, three Danish secondary level mathematics teachers’ beliefs about the use of technological tools in the teaching of mathematics and their beliefs about mathematics as a scientific discipline are identified and classified - and the process also aspects of their beliefs about...... the teaching and learning of mathematics. The potential relationships between these sets of beliefs are also explored. Results show that the teachers not only manifest different beliefs about the use of technology and mathematics as a discipline, but that one set of beliefs can influence the other set...... of beliefs. The article concludes with a discussion of the research findings and their validity as well as their implications for both practice and research in mathematics education....
Full Text Available The article presents results of a study on teachers’ views, beliefs, and experience on school-based informal collaboration for professional improvement. It explores the relationship of teacher beliefs in the collective efficacy of their colleagues and school’s capital and culture with their beliefs and experience in school-based collaborative learning. The key source of evidence used is a survey of 1025 primary and secondary teachers in three geographical regions of Chile. Main results show that teachers hold positive beliefs about the collective efficacy of their colleagues and students in their schools but more negative ones regarding the contribution of parents. In terms of collaboration, teachers hold positive beliefs in general about its role for professional learning but indeed engage more in the “weaker” types of collaboration such as “sharing ideas” and “talking about teaching problems” and less in the more demanding ones such as “mutual lesson observation” and “team teaching.” Differences in teachers’ views, beliefs, and experience were examined in terms of level of teaching (primary/secondary, urban/rural location, school type (public and private, and school size.
Full Text Available Sentiment analysis is a computational research of opinion sentiment and emotion which is expressed in textual mode. Twitter becomes the most popular communication device among internet users. Deep Learning is a new area of machine learning research. It aims to move machine learning closer to its main goal, artificial intelligence. The purpose of deep learning is to change the manual of engineering with learning. At its growth, deep learning has algorithms arrangement that focus on non-linear data representation. One of the machine learning methods is Deep Belief Network (DBN. Deep Belief Network (DBN, which is included in Deep Learning method, is a stack of several algorithms with some extraction features that optimally utilize all resources. This study has two points. First, it aims to classify positive, negative, and neutral sentiments towards the test data. Second, it determines the classification model accuracy by using Deep Belief Network method so it would be able to be applied into the tweet classification, to highlight the sentiment class of training data tweet in Bahasa Indonesia. Based on the experimental result, it can be concluded that the best method in managing tweet data is the DBN method with an accuracy of 93.31%, compared with Naive Bayes method which has an accuracy of 79.10%, and SVM (Support Vector Machine method with an accuracy of 92.18%.
Lindeman, Marjaana; Svedholm-Häkkinen, Annika M; Lipsanen, Jari
The current research tested the hypothesis that the abilities for understanding other people's minds give rise to the cognitive biases that underlie supernatural beliefs. We used structural equation modeling (N=2789) to determine the roles of various mentalizing tendencies, namely self-reported affective and cognitive empathy (i.e., mind reading), actual cognitive and affective empathic abilities, hyper-empathizing, and two cognitive biases (core ontological confusions and promiscuous teleology) in giving rise to supernatural beliefs. Support for a path from mentalizing abilities through cognitive biases to supernatural beliefs was weak. The relationships of mentalizing abilities with supernatural beliefs were also weak, and these relationships were not substantially mediated by cognitive biases. Core ontological confusions emerged as the best predictor, while promiscuous teleology predicted only a small proportion of variance. The results were similar for religious beliefs, paranormal beliefs, and for belief in supernatural purpose. Copyright © 2014 Elsevier B.V. All rights reserved.
Full Text Available This study aims to reveal personal beliefs of prospective science teachers about assessment. The study involved 46 prospective science teachers who have passed the 7th semester the course evaluation. Personal beliefs of prospective science teachers about assessment revealed using Personal Beliefs about Assessment Scale (SKDA. SKDA developed based on standards of assessment literacy and construct validity is done using Rasch models, with a Cronbach Alpha value of 0.93. Analysis and classification level of personal beliefs of prospective science teacher about assessment is done using the Rasch model is based on the logit ability of prospective science teachers based on the separation. The results showed that personal beliefs of prospective science teachers about assessment varies between two or three levels, depending on the standard of assessment literacy. There are still some aspects of the assessment of each standard that is trusted or considered less important by prospective teachers of science, namely: 1 consider the learning targets, learning experiences, and learning decision in choosing methods of assessment; 2 using the existing assessment and available in developing assessment methods; 3 interpret summary score; 4 use the assessment results to decision-making about the school and curriculum development; 5 consider extracurricular activities when developing procedures for judging; 6 report the result to another level with appropriate means and methods; and 7 to know when the assessment results are used inappropriately/inappropriate by others. Abstrak Studi ini bertujuan mengungkap kepercayaan calon guru sains tentang asesmen. Studi melibatkan 46 mahasiswa calon guru sains semester 7 yang telah lulus perkuliahan evaluasi pembelajaran. Kepercayaan calon guru sains tentang asesmen diungkap dengan menggunakan Skala Kepercayaan Diri Asesmen (SKDA. SKDA dikembangkan mengacu pada standar literasi asesmen dan validitas konstruk dilakukan dengan
Karatas, Ilhan; Guven, Bulent; Öztürk, Yasin; Arslan, Selahattin; Gürsöy, Kadir
The aim of this study was to determine pre-school teachers' beliefs about teaching mathematics to young learners. In this context, we compared preschool teachers' beliefs with mathematical learning, talent-development-age appropriateness for mathematical learning, the nature of mathematics, the curriculum, teacher efficacy, and the teacher's role…
Brauer, Heike; Wilde, Matthias
Learning beliefs influence learning and teaching. For this reason, teachers and teacher educators need to be aware of them. To support students' knowledge construction, teachers must develop appropriate learning and teaching beliefs. Teachers appear to have difficulties when analysing students' learning. This seems to be due to the inability to…
Prentow, Thor Siiger; Blunck, Henrik; Stisen, Allan
The ability to accurately estimate indoor travel times is crucial for enabling improvements within application areas such as indoor navigation, logistics for mobile workers, and facility management. In this paper, we study the challenges inherent in indoor travel time estimation, and we propose...... the InTraTime method for accurately estimating indoor travel times via mining of historical and real-time indoor position traces. The method learns during operation both travel routes, travel times and their respective likelihood---both for routes traveled as well as for sub-routes thereof. InTraTime...... allows to specify temporal and other query parameters, such as time-of-day, day-of-week or the identity of the traveling individual. As input the method is designed to take generic position traces and is thus interoperable with a variety of indoor positioning systems. The method's advantages include...
Michael W.M. Roos; Andreas Orland
This paper reports the results of a questionnaire study used to explore the economic understanding, normative positions along the egalitarian-libertarian spectrum, and the party preferences of a large student sample. The aim of the study is both to find socio-economic determinants of normative and positive beliefs and to explore how beliefs about the economy influence party support. We find that positive beliefs of lay people differ systematically from those of economic experts. Positive beli...
Bent, Gert Jan; Bakx, Anouke; den Brok, Perry
This study was carried out to investigate the primary education teachers' self-efficacy regarding geography education, their beliefs regarding the classroom learning environment, and how these beliefs were related to each other and to teachers' background characteristics. Questionnaire data were collected from 489 Dutch primary school teachers.…
Bent, G.J.W.; Bakx, A.W.E.A.; den Brok, P.J.
This study was carried out to investigate the primary education teachers' self-efficacy regarding geography education, their beliefs regarding the classroom learning environment, and how these beliefs were related to each other and to teachers' background characteristics. Questionnaire data were
Hart, Lynn Cecilia; Memnun, Dilek Sezgin
The purpose of this study was to examine the metacognitive awareness and the beliefs about mathematics teaching and learning of preservice elementary mathematics teachers and to explore the relationship between the two. The Metacognitive Awareness Instrument (MAI) and the Mathematics Beliefs Instrument (MBI) were implemented with 118 elementary…
Tapia Carlín, Rebeca Elena
Trainee beliefs about the roles of thesis supervisors can exert an important influence on timely and successful completion of theses. This research article explores pre-service teacher beliefs about the roles of thesis supervisors through the analysis of their learning diaries. The aim of this study is to identify ways to improve supervisory…
Thompson, Amy S.; Aslan, Erhan
This study explores the interface between learner beliefs and multilingualism in the under-researched English as a Foreign Language (EFL) context of Turkey. The study investigates the underlying constructs of a modified Beliefs about Language Learning Inventory (BALLI) completed by 168 EFL learners in Turkey using an exploratory factor analysis…
Farrell, Thomas S. C.
Preservice teachers come to any teacher education course with prior experiences, knowledge and beliefs about learning and teaching. Additionally, the belief systems of preservice teachers often serve as a lens through which they view the content of the teacher education program. Consequently, it is essential that teacher educators take these prior…
This study examines the developing beliefs and practices of six beginning primary teachers. Their accounts reveal practices indicative of contemporary approaches to teaching and learning in mathematics. Additionally, a consistency appears to exist between the beliefs and practices of the beginning teachers, and the ideals for mathematics teaching…
Heil, Martin; Jansen, Petra; Quaiser-Pohl, Claudia; Neuburger, Sarah
Men outperform women in the Mental Rotation Test (MRT) by about one standard deviation. The present study replicated a gender belief account [Moe, A., & Pazzaglia, F. (2006). Following the instructions! Effects of gender beliefs in mental rotation. Learning and Individual Differences, 16, 369-377.] for (part of) this effect. A sample of 300…
Teng, Lin Sophie
A plethora of research has found that teachers' beliefs directly influence their classroom practices and teaching outcomes. While numerous studies in second/foreign language writing have examined the effectiveness of different innovative approaches on students' learning to write, there is a paucity of research on writing teachers' beliefs about…
Full Text Available As a foundational concept in economics, the homo economicus assumption regards humans as rational and self-interested actors. In contrast, trust requires individuals to believe partners' benevolence and unselfishness. Thus, the homo economicus belief may inhibit trust. The present three experiments demonstrated that the direct exposure to homo economicus belief can weaken trust. And economic situations like profit calculation can also activate individuals' homo economicus belief and inhibit their trust. It seems that people's increasing homo economicus belief may serve as one cause of the worldwide decline of trust.
Xin, Ziqiang; Liu, Guofang
As a foundational concept in economics, the homo economicus assumption regards humans as rational and self-interested actors. In contrast, trust requires individuals to believe partners’ benevolence and unselfishness. Thus, the homo economicus belief may inhibit trust. The present three experiments demonstrated that the direct exposure to homo economicus belief can weaken trust. And economic situations like profit calculation can also activate individuals’ homo economicus belief and inhibit their trust. It seems that people’s increasing homo economicus belief may serve as one cause of the worldwide decline of trust. PMID:24146907
Patrícia Santos Ferreira
first and second investigation goals: discern pre-service 1st and 2nd cycles teachers’ beliefs on grammar teaching and learning; and characterise those teachers’ knowledge of the content in this field. Data were collected in the school year 2013-2014, in the beginning of the program. Data analysis led to the identification of the motivation for learning and teaching grammar and the prevalence of an instrumental, prescriptive and regulatory conception of this competency. On the other hand, the participants evinced serious deficiencies regarding scientific knowledge and its explicitation.
Tariyal, Snigdha; Majumdar, Angshul; Singh, Richa; Vatsa, Mayank
In this work we propose a new deep learning tool called deep dictionary learning. Multi-level dictionaries are learnt in a greedy fashion, one layer at a time. This requires solving a simple (shallow) dictionary learning problem, the solution to this is well known. We apply the proposed technique on some benchmark deep learning datasets. We compare our results with other deep learning tools like stacked autoencoder and deep belief network; and state of the art supervised dictionary learning t...
K V Petrides
Full Text Available Belief-importance (belimp theory hypothesizes that personality traits confer a propensity to perceive convergences or divergences between the belief that we can attain certain goals and the importance that we place on these goals. Belief and importance are conceptualized as two coordinates, together defining the belimp plane. We tested fundamental aspects of the theory using four different planes based on the life domains of appearance, family, financial security, and friendship as well as a global plane combining these four domains. The criteria were from the areas of personality (Big Five and trait emotional intelligence and learning styles. Two hundred and fifty eight participants were allocated into the four quadrants of the belimp plane (Hubris, Motivation, Depression, and Apathy according to their scores on four reliable instruments. Most hypotheses were supported by the data. Results are discussed with reference to the stability of the belimp classifications under different life domains and the relationship of the quadrants with the personality traits that are hypothesized to underpin them.
This qualitative study addresses the link between urban high school science teachers' beliefs about essential teaching dispositions and student learning outcomes. The findings suggest that in order to help students to do well in science in urban school settings, science teachers should possess essential teaching dispositions which include…
Knight, Wanda B.
Art educators, like many other educators born or socialized within the main-stream culture of a society, seldom have an opportunity to identify, question, and challenge their cultural values, beliefs, assumptions, and perspectives because school culture typically reinforces those they learn at home and in their communities (Bush & Simmons, 1990).…
Young, Tony Johnstone; Sachdev, Itesh
This paper reports on an investigation into the beliefs and practices of experienced teachers in the USA, UK and France relating to the application of a model of intercultural communicative competence (ICC) to English language programmes. Broadly, "intercultural" approaches to language learning and teaching are strongly advocated in both the…
Chen, Jie-Hao; Zhao, Zi-Qian; Shi, Ji-Yun; Zhao, Chong
In recent years, with the rapid development of mobile Internet and its business applications, mobile advertising Click-Through Rate (CTR) estimation has become a hot research direction in the field of computational advertising, which is used to achieve accurate advertisement delivery for the best benefits in the three-side game between media, advertisers, and audiences. Current research on the estimation of CTR mainly uses the methods and models of machine learning, such as linear model or recommendation algorithms. However, most of these methods are insufficient to extract the data features and cannot reflect the nonlinear relationship between different features. In order to solve these problems, we propose a new model based on Deep Belief Nets to predict the CTR of mobile advertising, which combines together the powerful data representation and feature extraction capability of Deep Belief Nets, with the advantage of simplicity of traditional Logistic Regression models. Based on the training dataset with the information of over 40 million mobile advertisements during a period of 10 days, our experiments show that our new model has better estimation accuracy than the classic Logistic Regression (LR) model by 5.57% and Support Vector Regression (SVR) model by 5.80%.
Full Text Available In recent years, with the rapid development of mobile Internet and its business applications, mobile advertising Click-Through Rate (CTR estimation has become a hot research direction in the field of computational advertising, which is used to achieve accurate advertisement delivery for the best benefits in the three-side game between media, advertisers, and audiences. Current research on the estimation of CTR mainly uses the methods and models of machine learning, such as linear model or recommendation algorithms. However, most of these methods are insufficient to extract the data features and cannot reflect the nonlinear relationship between different features. In order to solve these problems, we propose a new model based on Deep Belief Nets to predict the CTR of mobile advertising, which combines together the powerful data representation and feature extraction capability of Deep Belief Nets, with the advantage of simplicity of traditional Logistic Regression models. Based on the training dataset with the information of over 40 million mobile advertisements during a period of 10 days, our experiments show that our new model has better estimation accuracy than the classic Logistic Regression (LR model by 5.57% and Support Vector Regression (SVR model by 5.80%.
Zhao, Zi-Qian; Shi, Ji-Yun; Zhao, Chong
In recent years, with the rapid development of mobile Internet and its business applications, mobile advertising Click-Through Rate (CTR) estimation has become a hot research direction in the field of computational advertising, which is used to achieve accurate advertisement delivery for the best benefits in the three-side game between media, advertisers, and audiences. Current research on the estimation of CTR mainly uses the methods and models of machine learning, such as linear model or recommendation algorithms. However, most of these methods are insufficient to extract the data features and cannot reflect the nonlinear relationship between different features. In order to solve these problems, we propose a new model based on Deep Belief Nets to predict the CTR of mobile advertising, which combines together the powerful data representation and feature extraction capability of Deep Belief Nets, with the advantage of simplicity of traditional Logistic Regression models. Based on the training dataset with the information of over 40 million mobile advertisements during a period of 10 days, our experiments show that our new model has better estimation accuracy than the classic Logistic Regression (LR) model by 5.57% and Support Vector Regression (SVR) model by 5.80%. PMID:29209363
Galant, D. C.; Goorvitch, D.; Witteborn, Fred C. (Technical Monitor)
Combining an appropriate finite difference method with Richardson's extrapolation results in a simple, highly accurate numerical method for solving a Schrodinger's equation. Important results are that error estimates are provided, and that one can extrapolate expectation values rather than the wavefunctions to obtain highly accurate expectation values. We discuss the eigenvalues, the error growth in repeated Richardson's extrapolation, and show that the expectation values calculated on a crude mesh can be extrapolated to obtain expectation values of high accuracy.
Kang, Jung Jin
This study investigated how three instructors developed their professional learning of beliefs, knowledge, and practice by examining their professional learning processes using constructive, social constructive, and transformative theoretical perspectives on learning. It also focused on their challenges and supports in developing their…
van Benthem, J.; Girard, P.; Roy, O.; Marion, M.
Dynamic epistemic-doxastic logics describe the new knowledge or new beliefs indexBelief of agents after some informational event has happened. Technically, this requires an update rule that turns a doxastic-epistemic modelM(recording the current information state of the agents) and a dynamic ‘event
Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions) constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi). Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders) were conducted, which revealed significant positive correlations between belief in free will (theory and practice) and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker) difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs.
Faiver, Christopher M.; O'Brien, Eugene M.
Notes that religion may be source of spiritual strength or source of conflict and guilt. Outlines importance of assessing religious beliefs of clients for treatment purposes and provides format for counselor to use. Says that, because counselors may be unaware of clients' individual perspectives, it is important to evaluate client's belief system…
This thesis contributes to the development of Soft Dynamic Epistemic Logic (Soft DEL). Soft DEL has been introduced to deal with a number of informational phenomena, including belief revision. The work in this thesis extends the scope of Soft DEL to belief contraction, providing as such a framework
Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions) constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi). Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders) were conducted, which revealed significant positive correlations between belief in free will (theory and practice) and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker) difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs. PMID:24765084
Ghosh, S.; de Jongh, D.
Inspired by a similar use in provability logic, formulas p > B q and p ≥ B q are introduced in the existing logical framework for discussing beliefs to express that the strength of belief in p is greater than (or equal to) that in q. Besides its usefulness in studying the properties of the concept
Full Text Available Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi. Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders were conducted, which revealed significant positive correlations between belief in free will (theory and practice and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs.
Full Text Available In studies of multi-agent interaction, especially in game theory, the notion of equilibrium often plays a prominent role. A typical scenario for the belief merging problem is one in which several agents pool their beliefs together to form a...
Donald Trump's actions during the election and his first weeks as US president-elect send a strong message about his belief in climate change, or lack thereof. However, these actions may reflect polarization of climate change beliefs, not climate mitigation behaviour.
Ammar Abdullah Mahmoud Ismail
Full Text Available Epistemological beliefs—beliefs about the nature of knowledge, where it resides, and how knowledge is constructed and evaluated—have been the target of increased research interest lately. Heretofore, emphasis has been directed to language teaching/learning aspects and strategies. Language assessment practices have not yet received due attention in epistemic research literature. The current study examined the relationship between pre-service EFL teachers’ epistemological beliefs and their assessment orientations. Dimensions of epistemological beliefs were assessed via a questionnaire designed and validated by the researcher based on Schommer’s work. Two assessment orientations were examined including: (a transmissive surface- processing orientation and (b constructive deep-processing orientation. The study involved 114 preservice EFL teachers enrolled in the Professional Diploma in Teaching Program in the Abu Dhabi University, the United Arab Emirates. Results of the study showed that EFL teachers’ epistemological beliefs have a direct bearing on their assessment orientations and practices. EFL teachers with naive epistemological beliefs tended more to adopt surface-level assessment orientations whereas those with sophisticated epistemological beliefs showed more tendency to adopt deeper level approaches to assessment in language settings. Results are discussed in terms of backwash effects on foreign language instruction, curriculum development, and teacher education. Suggestions for further research are also discussed.
Antonella Del Rosso
Twenty years of designing, building and testing a number of innovative technologies, with the strong belief that the endeavour would lead to a historic breakthrough. The Bulletin publishes an abstract of the Courier’s interview with Barry Barish, one of the founding fathers of LIGO. The plots show the signals of gravitational waves detected by the twin LIGO observatories at Livingston, Louisiana, and Hanford, Washington. (Image: Caltech/MIT/LIGO Lab) On 11 February, the Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo collaborations published a historic paper in which they showed a gravitational signal emitted by the merger of two black holes. These results come after 20 years of hard work by a large collaboration of scientists operating the two LIGO observatories in the US. Barry Barish, Linde Professor of Physics, Emeritus at the California Institute of Technology and former Director of the Global Design Effort for the Internat...
Full Text Available Danielle Bromwich (2010 argues that a belief is motivationally efficacious in that, other things being equal, it disposes an agent to answer a question in accordance with that belief. I reply that what we are disposed to do is largely determined by our genes, whereas what we believe is largely determined by stimuli from the environment. We have a standing and default disposition to answer questions honestly, ceteris paribus, even before we are exposed to environmental stimuli. Since this standing and default disposition is innate, and our beliefs have their source in environmental stimuli, our beliefs cannot be the source of the disposition. Moreover, a recent finding in neuroscience suggests that motivation is extrinsic to belief.
Belo, Nelleke; Belo, N.; van Driel, J.H.; van Veen, Klaas; Verloop, Nico
This study explored the content and structure of physics teachers' beliefs on teaching and learning in general in relation to their domain-specific beliefs. A questionnaire was administered to secondary school teachers in physics (N = 126) in the Netherlands. The results showed that beliefs about
Belo, Nelleke A. H.; van Driel, Jan H.; van Veen, Klaas; Verloop, Nico
This study explored the content and structure of physics teachers' beliefs on teaching and learning in general in relation to their domain-specific beliefs. A questionnaire was administered to secondary school teachers in physics (N = 126) in the Netherlands. The results showed that beliefs about
Willard, Aiyana K; Norenzayan, Ara
Cognitive theories of religion have postulated several cognitive biases that predispose human minds towards religious belief. However, to date, these hypotheses have not been tested simultaneously and in relation to each other, using an individual difference approach. We used a path model to assess the extent to which several interacting cognitive tendencies, namely mentalizing, mind body dualism, teleological thinking, and anthropomorphism, as well as cultural exposure to religion, predict belief in God, paranormal beliefs and belief in life's purpose. Our model, based on two independent samples (N=492 and N=920) found that the previously known relationship between mentalizing and belief is mediated by individual differences in dualism, and to a lesser extent by teleological thinking. Anthropomorphism was unrelated to religious belief, but was related to paranormal belief. Cultural exposure to religion (mostly Christianity) was negatively related to anthropomorphism, and was unrelated to any of the other cognitive tendencies. These patterns were robust for both men and women, and across at least two ethnic identifications. The data were most consistent with a path model suggesting that mentalizing comes first, which leads to dualism and teleology, which in turn lead to religious, paranormal, and life's-purpose beliefs. Alternative theoretical models were tested but did not find empirical support. Copyright © 2013 Elsevier B.V. All rights reserved.
Ali Bagheri, Mohammad; Gao, Qigang; Guerrero, Sergio Escalera
the performance of an ensemble of action learning techniques, each performing the recognition task from a different per- spective. The underlying idea is that instead of aiming a very sophisticated and powerful representation/learning technique, we can learn action categories using a set of relatively simple...... to improve the recognition perfor- mance, a powerful combination strategy is utilized based on the Dempster-Shafer theory, which can effectively make use of diversity of base learners trained on different sources of information. The recognition results of the individual clas- sifiers are compared with those...... obtained from fusing the classifiers’ output, showing enhanced performance of the proposed methodology....
Braüner, Torben; Blackburn, Patrick Rowan; Polyanskaya, Irina
it indicate that a more fundamental *conceptual change* has taken place? In this paper we extend Braüner's hybrid-logical analysis of first-order false-belief tasks to the second-order case, and argue that our analysis supports a version of the conceptual change position.......The literature on first-order false-belief is extensive, but less is known about the second-order case. The ability to handle second-order false-beliefs correctly seems to mark a cognitively significant step, but what is its status? Is it an example of *complexity only* development, or does...
Nuclear reactor operator emergency response behavior has persisted as a training problem through lack of information. The industry needs an accurate definition of operator behavior in adverse stress conditions, and training methods which will produce the desired behavior. Newly assembled information from fifty years of research into human behavior in both high and low stress provides a more accurate definition of appropriate operator response, and supports training methods which will produce the needed control room behavior. The research indicates that operator response in emergencies is divided into two modes, conditioned behavior and knowledge based behavior. Methods which assure accurate conditioned behavior, and provide for the recovery of knowledge based behavior, are described in detail
E Siswono, T. Y.; Kohar, A. W.; Hartono, S.
This study investigates secondary teachers’ belief about the three mathematics-related beliefs, i.e. nature of mathematics, teaching mathematics, learning mathematics, and knowledge about mathematical problem solving. Data were gathered through a set of task-based semi-structured interviews of three selected teachers with different philosophical views of teaching mathematics, i.e. instrumental, platonist, and problem solving. Those teachers were selected from an interview using a belief-related task from purposively selected teachers in Surabaya and Sidoarjo. While the interviews about knowledge examine teachers’ problem solving content and pedagogical knowledge, the interviews about beliefs examine their views on several cases extracted from each of such mathematics-related beliefs. Analysis included the categorization and comparison on each of beliefs and knowledge as well as their interaction. Results indicate that all the teachers did not show a high consistency in responding views of their mathematics-related beliefs, while they showed weaknesses primarily on problem solving content knowledge. Findings also point out that teachers’ beliefs have a strong relationship with teachers’ knowledge about problem solving. In particular, the instrumental teacher’s beliefs were consistent with his insufficient knowledge about problem-solving, while both platonist and problem-solving teacher’s beliefs were consistent with their sufficient knowledge of either content or pedagogical problem solving.
Markic, Silvija; Eilks, Ingo
The study presented in this paper integrates data from four combined research studies, which are both qualitative and quantitative in nature. The studies describe freshman science student teachers' beliefs about teaching and learning. These freshmen intend to become teachers in Germany in one of four science teaching domains (secondary biology, chemistry, and physics, respectively, as well as primary school science). The qualitative data from the first study are based on student teachers' drawings of themselves in teaching situations. It was formulated using Grounded Theory to test three scales: Beliefs about Classroom Organisation, Beliefs about Teaching Objectives, and Epistemological Beliefs. Three further quantitative studies give insight into student teachers' curricular beliefs, their beliefs about the nature of science itself, and about the student- and/or teacher-centredness of science teaching. This paper describes a design to integrate all these data within a mixed methods framework. The aim of the current study is to describe a broad, triangulated picture of freshman science student teachers' beliefs about teaching and learning within their respective science teaching domain. The study reveals clear tendencies between the sub-groups. The results suggest that freshman chemistry and-even more pronouncedly-freshman physics student teachers profess quite traditional beliefs about science teaching and learning. Biology and primary school student teachers express beliefs about their subjects which are more in line with modern educational theory. The mixed methods approach towards the student teachers' beliefs is reflected upon and implications for science education and science teacher education are discussed.
Full Text Available The Emotional Perception Model of moral judgment intends to account for experientialism about morality and moral reasoning. In explaining how moral beliefs are formed and applied in practical reasoning, the model attempts to overcome the mismatch between reason and action/desire: morality isn’t about reason for actions, yet moral beliefs, if caused by desires, may play a motivational role in (moral agency. The account allows for two kinds of moral beliefs: genuine moral beliefs, which enjoy a relation to desire, and motivationally inert moral beliefs acquired in ways other than experience. Such etiology-based dichotomy of concepts, I will argue, leads to the undesirable view of cognition as a non-homogeneous phenomenon. Moreover, the distinction between moral beliefs and moral beliefs would entail a further dichotomy encompassing the domain of moral agency: one and the same action might possibly be either genuine moral, or not moral, if acted by individuals lacking the capacity for moral feelings, such as psychopaths.
Forgeot d'Arc, Baudouin; Ramus, Franck
False-belief (FB) tasks have been widely used to study the ability of individuals to represent the content of their conspecifics' mental states (theory of mind). However, the cognitive processes involved are still poorly understood, and it remains particularly debated whether language and inner speech are necessary for the attribution of beliefs to other agents. We present a completely nonverbal paradigm consisting of silent animated cartoons in five closely related conditions, systematically teasing apart different aspects of scene analysis and allowing the assessment of the attribution of beliefs, goals, and physical causation. In order to test the role of language in belief attribution, we used verbal shadowing as a dual task to inhibit inner speech. Data on 58 healthy adults indicate that verbal interference decreases overall performance, but has no specific effect on belief attribution. Participants remained able to attribute beliefs despite heavy concurrent demands on their verbal abilities. Our results are most consistent with the hypothesis that belief attribution is independent from inner speech.
Pre-Service Teachers' Beliefs about Language Teaching and Learning: A Longitudinal Study (Creencias de profesores principiantes acerca de la enseñanza y aprendizaje de lengua: un estudio longitudinal)
Cota Grijalva, Sofía D.; Ruiz-Esparza Barajas, Elizabeth
This paper contains the description of a research project that was carried out in the Bachelor of Arts in English Language Teaching program at a Mexican university. The study was longitudinal and it tracked fourteen students for four semesters of the eight semester program. The aim was to identify pre-service teachers' beliefs about English…
Hooker, Carol E.
Learned helplessness--the belief that a person's actions have no influence on the outcome of an event--is similar in many respects to the crisis state and depression. The author shows how this impaired social and psychological functioning occurs and identifies techniques that the social worker can use to prevent it. (Author)
In spring 2012, Sherry Kaufman, a consultant at Francis W. Parker School in Chicago, was asked to support kindergarten teachers in deepening their practice of constructivism and exploring the Reggio Emilia approach to early childhood education. Central to such an approach is the belief that all learning is socially constructed through interaction…
Page, Randy M; Piko, Bettina F; Balazs, Mate A; Struk, Tamara
Hungary will continue to experience a high burden of disease and death from lung cancer and other tobacco-induced disease unless there is a significant reduction in youth smoking. Social factors have been found to be among the most important determinants of adolescent smoking, yet few studies have investigated social normative beliefs in Hungarian youth. The purpose of the current study was to investigate three measures of smoking normative beliefs thought to influence adolescent smoking: perceived prevalence of smoking; perceived popularity of smoking among successful/elite elements of society; and perceived disapproval by friends and family. A cross-sectional school-based survey of eighth grade (n = 258) and 12th grade (n = 288) students in Mako, Hungary was conducted to assess social normative beliefs about smoking, current smoking, ever smoking, and susceptibility to smoking. The association of the normative beliefs with the smoking behavior variables was examined through logistic regression analysis, and the underlying factor structure of the normative belief items in the current sample was determined through factor analysis. The percent of boys reporting current smoking was 40.5% in 12th grade and 27.0% in eighth grade. Among girls, the percent was 44.0% of 12th graders and 29.1% of eighth graders. Parent/peer disapproval was the most consistently associated normative belief with smoking behavior and susceptibility to smoking across both samples. Youth smoking prevention programs should consider assessing and taking into account normative beliefs and develop strategies that provide accurate information about the actual prevalence of smoking, the types of individuals who smoke, and approval/disapproval of smoking by parents and peers. © 2011 The Authors. Pediatrics International © 2011 Japan Pediatric Society.
Park, Subin; Lee, Minji; Furnham, Adrian; Jeon, Mina; Ko, Young-Mi
Lay beliefs about schizophrenia are an important factor associated with treatment-seeking behavior. This study was conducted to investigate the lay beliefs about the causes and treatments of schizophrenia in South Korea. A total of 654 adults (mean age, 35.96 ± 11.33 years) completed two questionnaires assessing their views on the causes and cures of schizophrenia. The factor structures of lay beliefs about the causes and treatments of schizophrenia were then analyzed and the correlations between the resultant factors investigated. From the cause items, four factors were extracted: Health/Lifestyle, God/Fate, Social/Environmental and Biological. Four factors were also extracted from the treatment items: Self-Help/Stress Management, Physical Treatment/Health Management, Religious Help and Mental Health Service Utilization. Notably, most participants believed that items in the Social/Environmental and Biological factors were the causes of schizophrenia, while they believed that items in the Mental Health Service Utilization and Self-Help/Stress Management factors were the treatments. Participants' beliefs about the causes and treatments of schizophrenia were systematically correlated. Overall, laypeople have reasonably accurate beliefs and a multidimensional view of the causes and treatments of schizophrenia. Nevertheless, our results suggest that public education about the etiology and treatment of schizophrenia are necessary to increase actual usage of mental health services and treatments for schizophrenia.
Lannin, John K.; Chval, Kathryn B.
As beginning teachers start to recognize the complexity of teaching mathematics in elementary school classrooms and how their new vision for teaching mathematics creates new challenges, they experience discomfort--a healthy awareness that much is to be learned. Brousseau (1997) notes that changes in the roles that are implicitly assigned to the…
Movahedi, Faezeh; Coyle, James L; Sejdic, Ervin
Deep learning, a relatively new branch of machine learning, has been investigated for use in a variety of biomedical applications. Deep learning algorithms have been used to analyze different physiological signals and gain a better understanding of human physiology for automated diagnosis of abnormal conditions. In this paper, we provide an overview of deep learning approaches with a focus on deep belief networks in electroencephalography applications. We investigate the state-of-the-art algorithms for deep belief networks and then cover the application of these algorithms and their performances in electroencephalographic applications. We covered various applications of electroencephalography in medicine, including emotion recognition, sleep stage classification, and seizure detection, in order to understand how deep learning algorithms could be modified to better suit the tasks desired. This review is intended to provide researchers with a broad overview of the currently existing deep belief network methodology for electroencephalography signals, as well as to highlight potential challenges for future research.
Dudley, R T; Whisnand, E A
52 college students completed Tobacyk's 1988 Revised Paranormal Belief Scale and Peterson, Semmel, von Baeyer, Abramson, Metalsky, and Seligman's 1982 Attributional Style Questionnaire. Analysis showed significantly higher depressive attributional styles among high scorers on paranormal phenomena than low scorers.
.... The hypothesis underlying this research is that a breast health promotion approach that is based in specific belief systems among three disparate African American rural populations of low socioeconomic status (SES...
Clarke, Anne E.; Ruble, Diane N.
A sample of 54 young adolescent girls (both pre- and postmenarcheal) and boys responded to a questionnaire assessing evaluative attitudes toward menstruation, expected symptomatology, perceived effects on moods and activities, and sources of information for these beliefs. (Author/JMB)
Tanaka, Kazuyuki; Kataoka, Shun; Yasuda, Muneki; Waizumi, Yuji; Hsu, Chiou-Ting
This paper presents a Bayesian image segmentation model based on Potts prior and loopy belief propagation. The proposed Bayesian model involves several terms, including the pairwise interactions of Potts models, and the average vectors and covariant matrices of Gauss distributions in color image modeling. These terms are often referred to as hyperparameters in statistical machine learning theory. In order to determine these hyperparameters, we propose a new scheme for hyperparameter estimation based on conditional maximization of entropy in the Potts prior. The algorithm is given based on loopy belief propagation. In addition, we compare our conditional maximum entropy framework with the conventional maximum likelihood framework, and also clarify how the first order phase transitions in loopy belief propagations for Potts models influence our hyperparameter estimation procedures.
This article investigates children's beliefs about parental divorce and attitudes toward environment and people. Children's believes about parental divorce is evaluated in a sample 8 through 10-year children whose parents had been separated for about 3 years. Attitudes toward environment and people between children of separated as well as intact families are compared. We also examined the relation of children's beliefs about parental divorce and attitudes toward environment and people. The me...
Wang, Yulei; Liu, Jian; Qin, Hong; Yu, Zhi
The Accurate Particle Tracer (APT) code is designed for large-scale particle simulations on dynamical systems. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and non-linear problems. Under the well-designed integrated and modularized framework, APT serves as a universal platform for researchers from different fields, such as plasma physics, accelerator physics, space science, fusio...
Heavy ion accelerators are the most flexible and readily accessible sources of highly charged ions. These having only one or two remaining electrons have spectra whose accurate measurement is of considerable theoretical significance. Certain features of ion production by accelerators tend to limit the accuracy which can be realized in measurement of these spectra. This report aims to provide background about spectroscopic limitations and discuss how accelerator operations may be selected to permit attaining intrinsically limited data
Artino, Anthony R; La Rochelle, Jeffery S; Durning, Steven J
A challenge for medical educators is to better understand the personal factors that lead to individual success in medical school and beyond. Recently, educational researchers in fields outside medicine have acknowledged the importance of motivation and emotion in students' learning and performance. These affective factors have received less emphasis in the medical education literature. This longitudinal study examined the relations between medical students' motivational beliefs (task value and self-efficacy), achievement emotions (enjoyment, anxiety and boredom) and academic achievement. Second-year medical students (n=136) completed motivational beliefs and achievement emotions surveys following their first and second trimesters, respectively. Academic achievement was operationalised as students' average course examination grades and national board shelf examination scores. The results largely confirmed the hypothesised relations between beliefs, emotions and achievement. Structural equation modelling revealed that task value beliefs were positively associated with course-related enjoyment (standardised regression coefficient [β] = 0.59) and were negatively related to boredom (β= -0.25), whereas self-efficacy beliefs were negatively associated with course-related anxiety only (β = -0.47). Furthermore, student enjoyment was positively associated with national board shelf examination score (β = 0.31), whereas anxiety and boredom were both negatively related to course examination grade (β= -0.36 and -0.27, respectively). The overall structural model accounted for considerable variance in each of the achievement outcomes: R(2) = 0.20 and 0.14 for the course examination grade and national board shelf examination score, respectively. This study suggests that medical students' motivational beliefs and achievement emotions are important contributors to their academic achievement. These results have implications for medical educators striving to understand the
Full Text Available Learning as a retrospective phenomenon can make learners transmit their past as an ingredient while they are (restructuring their present and future. Previous and present experiences can form a basis for cognitive, behavioral and motivational factors which can create a cognitive load for learners and affect their learning process. In this regard, current study aims to investigate first-year undergraduates’ beliefs about writing and relation of these beliefs to writing performance in essay writing. A total of 147 students studying in ELT department of a Turkish university participated in the research. Their domain-specific beliefs about writing were determined through the Beliefs about Writing Survey (BAWS. Writing performance was measured on an essay writing task by calculating both overall grade and six component grades. As a result, multiple regression analysis affirmed that beliefs about writing accounted for writing performance independently. Pearson correlation values showed that some beliefs about writing were adaptive and associated with higher writing scores (e.g. “Adapt to the Audience”. Also, some belief subcategories were associated with each other. The results of the present study have been discussed along with the related literature on beliefs about writing and writing performance. Implications/suggestions related to the coursework, writing practices and future research have been presented.
Novia Tri Febriani
Full Text Available Language learning belief and language learning strategies are two essential predictors that have significant effect toward students’ language proficiency. Learners’ belief is dealing with what comes from inside the learners in learning the language, such as foreign language aptitude; difficulty of language learning; nature of language learning; learning and communication strategies; and motivation. Meanwhile, language learning strategies are learners’ plan in achieving certain goals or mastering the target language. A preliminary research was conducted in order to find what strategy mostly used by the learners. It turned out that the strategy mostly used by them was metacognitive strategies. Thus, this study aims to investigate about the correlation between metacognitive strategies and certain belief’ variables in students’ language learning which are foreign language aptitude and motivation. Moreover, twenty postgraduate students of English education department participated in this study. This study used correlational research, in which the BALLI (Beliefs about Language Learning Inventory and SILL (Strategies Inventory for Language Learners questionnaires were adopted as the instruments in collecting the data. The findings of this study indicated that there is negative linear correlation between metacognitive strategy and foreign language aptitude (rXY = -0,049 while there is significant positive linear correlation between metacognitive and motivation (rXY =+0,79 in students’ language learning. Furthermore, this study also provide some recommendations, which is it is expected that there will be more researches use studies using different respondents with various contexts. Secondly, the further research will use both of quantitative and qualitative data relating to this issue in order to make a more accurate data.
Vergel P. Mirana
Full Text Available The study evaluated the effects of a developed lesson exemplars in electricity integrating computer simulations and constructivist approach on students' Epistemological Beliefs. Specifically, it sought to determine how computer simulations, constructivist approach and Formativ e Assessment Classroom Technique (FACT can be integrated in the lesson exemplars in electricity; and evaluate the effects of the developed lesson exemplars in the students’ Epistemological Beliefs. The investigation employed the pre - experimental single - gr oup pretest and posttest study using the Epistemological Beliefs Assessment in Physical Sciences (EBAPS questionnaire. The study was conducted among seventy - two (72 Grade 10 students of a laboratory high school from a state university in the Philippines. They were taught using Physics Educational Technology (PhET and other web - based simulations, constructivist approach, and formative assessment classroom technique. The results revealed that the over - all Epistemological Beliefs of the students did not cha nge significantly; only along Nature of Knowing and Learning and Real - Life Applicability. Generally, utilizing computer simulations and applying constructivist approach did not alter students' epistemological beliefs in its entirety. However, it can be en gaging and effective in promoting students’ understanding of Physics.
Lloyd, Sharon Henry
In the United States, a current initiative, Advancing Active STEM Education for Our Youngest Learners, aims to advance science, technology, engineering, and math (STEM) education in early childhood. The purpose of this study was to understand preschool teachers' proficiency with science and address the problem of whether or not science learning opportunities are provided to young children based on teachers' attitudes and beliefs. A theoretical framework for establishing teachers' attitudes toward science developed by van Aalderen-Smeets, van der Molen, and Asma, along with Bandura's theory of self-efficacy were the foundations for this research. Research questions explored preschool teachers' attitudes and beliefs toward science in general and how they differed based on education level and years of preschool teaching experience. Descriptive comparative data were collected from 48 preschool teacher participants using an online format with a self-reported measure and were analyzed using nonparametric tests to describe differences between groups based on identified factors of teacher comfort, child benefit, and challenges. Results indicated that the participants believed that early childhood science is developmentally appropriate and that young children benefit from science instruction through improved school-readiness skills. Preschool teachers with a state credential or an associate's degree and more teaching experience had more teacher comfort toward science based on attitudes and beliefs surveyed. The data indicated participating preschool teachers experienced few challenges in teaching science. The study may support positive social change through increased awareness of strengths and weaknesses of preschool teachers for the development of effective science professional development. Science is a crucial component of school-readiness skills, laying a foundation for success in later grades.
Attitudes and beliefs are analyzed as verbal behavior. It is argued that shaping by a verbal community is an essential part of the formation and maintenance of both attitudes and beliefs, and it is suggested that verbal communities mediate the important shift in control from events in the environment (attitudes and beliefs as tacts) to control by other words (attitudes and beliefs as intraverbals). It appears that both attitudes and beliefs are constantly being socially negotiated through aut...
Full Text Available Mathematics beliefs play an important role in enhancing the quality and the effectiveness of teaching and learning. This study analyzes the mathematics beliefs of 317 pre-service teachers from six Higher Education Institutions (HEIs (Government Public Universities who were randomly selected to participate in this study. Questionnaires consisting of twenty three items were given to the respondents during the data collection process. The validation of the items was done by using confirmatory factor analysis (CFA. In order to obtain a model fit for the measurement model of mathematics beliefs, several fit index tests such as CMINDF, GFI, AGFI, IFI, NFI, CFI, TLI and RMSEA were used. Constructivist beliefs and traditional beliefs were identified as the contributing factors in the model. The analysis also revealed that mathematics beliefs consist of structures of two hidden variables. The correlation between the two variables (constructivist beliefs and traditional beliefs is at a moderate level. Hence, pre-service teachers should be able to recognize their type of mathematics beliefs in order to become effective mathematics teachers.
De novo genome assemblers designed for short k-mer length or using short raw reads are unlikely to recover complex features of the underlying genome, such as repeats hundreds of bases long. We implement a stochastic machine-learning method which obtains accurate assemblies with repeats and
The derivation of a formula for accurate estimation of the total radiated power from a transmitting antenna for which the radiated power density is known in a finite number of points on the far-field sphere is presented. The main application of the formula is determination of directivity from power......-pattern measurements. The derivation is based on the theory of spherical wave expansion of electromagnetic fields, which also establishes a simple criterion for the required number of samples of the power density. An array antenna consisting of Hertzian dipoles is used to test the accuracy and rate of convergence...
Bissiri, P G; Holmes, C C; Walker, S G
We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to observations through a loss function rather than the traditional likelihood function, which is recovered as a special case. Modern application areas make it increasingly challenging for Bayesians to attempt to model the true data-generating mechanism. For instance, when the object of interest is low dimensional, such as a mean or median, it is cumbersome to have to achieve this via a complete model for the whole data distribution. More importantly, there are settings where the parameter of interest does not directly index a family of density functions and thus the Bayesian approach to learning about such parameters is currently regarded as problematic. Our framework uses loss functions to connect information in the data to functionals of interest. The updating of beliefs then follows from a decision theoretic approach involving cumulative loss functions. Importantly, the procedure coincides with Bayesian updating when a true likelihood is known yet provides coherent subjective inference in much more general settings. Connections to other inference frameworks are highlighted.
Caleon, Imelda S.; Tan, Yuen Sze Michelle; Cho, Young Hoan
This study utilized multiple data sources to examine the beliefs about learning and teaching physics and the instructional practices of five beginning teachers and seven experienced teachers from Singapore. Our study was implemented in the unique context of teachers teaching the topic of electricity to students grouped according to academic abilities. The topic of electricity is one of the most difficult physics topics for students to understand and for teachers to teach. It was found that the experienced teachers, compared to the beginning teachers, tended to have beliefs about teaching and learning physics that are closer to constructivist views. The majority of the teachers, particularly the beginning teachers, espoused beliefs about learning physics that were incongruent with their beliefs about teaching physics. Although transmission-oriented and teacher-directed practices dominated the classroom lessons of both groups of teachers, more elements of constructivist instruction were found in the classroom lessons of the experienced teachers. It was also found that the classroom practices of the teachers, especially those in their inductive years of teaching, were more aligned with their beliefs about learning physics than their beliefs about teaching physics.
Lodewyk, Ken R.; Gao, Zan
Epistemic beliefs are deeply held convictions about the nature of knowledge, knowing, and learning. In this study, approximately 500 ninth and tenth-grade physical education (PE) students completed fitness-specific measures assessing their epistemic beliefs in the simplicity and stability of knowledge and the speed of its acquisition along with…
Hos, Rabia; Kekec, Mustafa
Learner and teacher beliefs play an important role in second language (L2) learning. Furthermore, the role of grammar instruction and error correction in the L2 classroom is a topic that is still debated in the literature. This study explored the beliefs of EFL learners and teachers regarding the controversial role of grammar instruction and error…
Hur, Eunhye; Jeon, Lieny; Buettner, Cynthia K.
Background: Early childhood teachers' child-centered beliefs, defined as teachers' attitudes about how children learn, have been associated with teachers' developmentally appropriate practices and positive child outcomes. The predictors of teachers' child-centered beliefs, however, are less frequently explored. Objective: This study tested whether…
Tzuo, Pei-Wen; Tan, Liang See; Yang, Chien-Hui
In the age of globalisation, it has been understood that teachers' beliefs revolve between old--new and local--foreign ideas of teaching and learning. The purpose of this study is to identify the domains of the various ideas that influence teachers' beliefs in globalisation, compare them to the strengths of influence, and explore the meanings of…
Kaymak, Ercan; Ogan-Bekiroglu, Feral
The purposes of this study were to determine high school students' epistemological beliefs in the domain of physics and to explore and explain the possible relationship between their beliefs and their conceptual change in physics by taking the students' learning strategies into account. A multi-case study design was used for the research…
Botero, Carlos A.; Gardner, Beth; Kirby, Kathryn R.; Bulbulia, Joseph; Gavin, Michael C.; Gray, Russell D.
Although ecological forces are known to shape the expression of sociality across a broad range of biological taxa, their role in shaping human behavior is currently disputed. Both comparative and experimental evidence indicate that beliefs in moralizing high gods promote cooperation among humans, a behavioral attribute known to correlate with environmental harshness in nonhuman animals. Here we combine fine-grained bioclimatic data with the latest statistical tools from ecology and the social sciences to evaluate the potential effects of environmental forces, language history, and culture on the global distribution of belief in moralizing high gods (n = 583 societies). After simultaneously accounting for potential nonindependence among societies because of shared ancestry and cultural diffusion, we find that these beliefs are more prevalent among societies that inhabit poorer environments and are more prone to ecological duress. In addition, we find that these beliefs are more likely in politically complex societies that recognize rights to movable property. Overall, our multimodel inference approach predicts the global distribution of beliefs in moralizing high gods with an accuracy of 91%, and estimates the relative importance of different potential mechanisms by which this spatial pattern may have arisen. The emerging picture is neither one of pure cultural transmission nor of simple ecological determinism, but rather a complex mixture of social, cultural, and environmental influences. Our methods and findings provide a blueprint for how the increasing wealth of ecological, linguistic, and historical data can be leveraged to understand the forces that have shaped the behavior of our own species. PMID:25385605
Karnezou, Maria; Avgitidou, Sofia; Kariotoglou, Petros
There is a growing body of research examining the impact of science field trips on pupils' learning in science education and the factors that influence their success. However, there is a limited number of studies that focus on the way teachers' beliefs influence their practices in an informal science-learning venue. This research aimed to…
U.S. schools teach predominately to the analytical, left-brain, which has foundations in behaviorism, and uses a mechanistic paradigm that influences epistemic beliefs of how learning takes place. This result is that learning is impeded. Using discourse analysis of a set of Piagetian children, this study re-analyzed Piaget's work. This study found…
Nesbit, Susan E.; Sianchuk, Robert; Aleksejuniene, Jolanta; Kindiak, Rebecca
This study suggests that community service learning experiences facilitate the reconstruction of civil engineering student beliefs about both the type of work performed by civil engineers and the broad impact of civil engineering knowledge. Further, the service learning experiences highlight for students 1) the importance of relationships between…
Stone, Teresa E; Kang, Sook Jung; Cha, Chiyoung; Turale, Sue; Murakami, Kyoko; Shimizu, Akihiko
Many health beliefs do not have supporting scientific evidence, and are influenced by culture, gender, religion, social circumstance and popular media. Nurses may also hold non-evidenced-based beliefs that affect their own health behaviours and their practices. Using Q-methodology, pilot Q-cards representing a concourse of health beliefs for Japanese and South Korean nurses and explain the content and sources of health beliefs. Qualitative. Two university campuses, one each in Japan and Korea. A convenience sample of 30 was obtained, 14 clinical nurses and 16 academic nurses. Literature reviews and expert informants were used to develop two sets of 65 Q-cards which listed culturally appropriate health beliefs in both Japan and Korea. These beliefs were examined in four structured groups and five individual interviews in Japan, and five groups and two individual interviews in Korea. Our unique study revealed six categories regarding sources of health beliefs that provide rich insights about how participants accessed, processed and transmitted health information. They were more certain about knowledge from their specialty area such as that from medical or nursing resources, but derived and distributed many general health beliefs from personal experience, family and mass media. They did not always pass on accurate information to students or those in their care, and often beliefs were not based on scientific evidence. Findings highlight the dangers of clinical and academic nurses relying on health belief advice of others and passing this on to patients, students or others, without mindfully examining the basis of their beliefs through scientific evidence. Copyright © 2015 Elsevier Ltd. All rights reserved.
Full Text Available Neuromyths are misconceptions about brain research and its application to education and learning. Previous research has shown that these myths may be quite pervasive among educators, but less is known about how these rates compare to the general public or to individuals who have more exposure to neuroscience. This study is the first to use a large sample from the United States to compare the prevalence and predictors of neuromyths among educators, the general public, and individuals with high neuroscience exposure. Neuromyth survey responses and demographics were gathered via an online survey hosted at TestMyBrain.org. We compared performance among the three groups of interest: educators (N = 598, high neuroscience exposure (N = 234, and the general public (N = 3,045 and analyzed predictors of individual differences in neuromyths performance. In an exploratory factor analysis, we found that a core group of 7 “classic” neuromyths factored together (items related to learning styles, dyslexia, the Mozart effect, the impact of sugar on attention, right-brain/left-brain learners, and using 10% of the brain. The general public endorsed the greatest number of neuromyths (M = 68%, with significantly fewer endorsed by educators (M = 56%, and still fewer endorsed by the high neuroscience exposure group (M = 46%. The two most commonly endorsed neuromyths across all groups were related to learning styles and dyslexia. More accurate performance on neuromyths was predicted by age (being younger, education (having a graduate degree, exposure to neuroscience courses, and exposure to peer-reviewed science. These findings suggest that training in education and neuroscience can help reduce but does not eliminate belief in neuromyths. We discuss the possible underlying roots of the most prevalent neuromyths and implications for classroom practice. These empirical results can be useful for developing comprehensive training modules for educators that target
Macdonald, Kelly; Germine, Laura; Anderson, Alida; Christodoulou, Joanna; McGrath, Lauren M
Neuromyths are misconceptions about brain research and its application to education and learning. Previous research has shown that these myths may be quite pervasive among educators, but less is known about how these rates compare to the general public or to individuals who have more exposure to neuroscience. This study is the first to use a large sample from the United States to compare the prevalence and predictors of neuromyths among educators, the general public, and individuals with high neuroscience exposure. Neuromyth survey responses and demographics were gathered via an online survey hosted at TestMyBrain.org. We compared performance among the three groups of interest: educators ( N = 598), high neuroscience exposure ( N = 234), and the general public ( N = 3,045) and analyzed predictors of individual differences in neuromyths performance. In an exploratory factor analysis, we found that a core group of 7 "classic" neuromyths factored together (items related to learning styles, dyslexia, the Mozart effect, the impact of sugar on attention, right-brain/left-brain learners, and using 10% of the brain). The general public endorsed the greatest number of neuromyths ( M = 68%), with significantly fewer endorsed by educators ( M = 56%), and still fewer endorsed by the high neuroscience exposure group ( M = 46%). The two most commonly endorsed neuromyths across all groups were related to learning styles and dyslexia. More accurate performance on neuromyths was predicted by age (being younger), education (having a graduate degree), exposure to neuroscience courses, and exposure to peer-reviewed science. These findings suggest that training in education and neuroscience can help reduce but does not eliminate belief in neuromyths. We discuss the possible underlying roots of the most prevalent neuromyths and implications for classroom practice. These empirical results can be useful for developing comprehensive training modules for educators that target general
Yang, Hao; Zhang, Junran; Jiang, Xiaomei; Liu, Fei
In recent years, with the rapid development of machine learning techniques,the deep learning algorithm has been widely used in one-dimensional physiological signal processing. In this paper we used electroencephalography (EEG) signals based on deep belief network (DBN) model in open source frameworks of deep learning to identify emotional state (positive, negative and neutrals), then the results of DBN were compared with support vector machine (SVM). The EEG signals were collected from the subjects who were under different emotional stimuli, and DBN and SVM were adopted to identify the EEG signals with changes of different characteristics and different frequency bands. We found that the average accuracy of differential entropy (DE) feature by DBN is 89.12%±6.54%, which has a better performance than previous research based on the same data set. At the same time, the classification effects of DBN are better than the results from traditional SVM (the average classification accuracy of 84.2%±9.24%) and its accuracy and stability have a better trend. In three experiments with different time points, single subject can achieve the consistent results of classification by using DBN (the mean standard deviation is1.44%), and the experimental results show that the system has steady performance and good repeatability. According to our research, the characteristic of DE has a better classification result than other characteristics. Furthermore, the Beta band and the Gamma band in the emotional recognition model have higher classification accuracy. To sum up, the performances of classifiers have a promotion by using the deep learning algorithm, which has a reference for establishing a more accurate system of emotional recognition. Meanwhile, we can trace through the results of recognition to find out the brain regions and frequency band that are related to the emotions, which can help us to understand the emotional mechanism better. This study has a high academic value and
Macdonald, Kelly; Germine, Laura; Anderson, Alida; Christodoulou, Joanna; McGrath, Lauren M.
Neuromyths are misconceptions about brain research and its application to education and learning. Previous research has shown that these myths may be quite pervasive among educators, but less is known about how these rates compare to the general public or to individuals who have more exposure to neuroscience. This study is the first to use a large sample from the United States to compare the prevalence and predictors of neuromyths among educators, the general public, and individuals with high neuroscience exposure. Neuromyth survey responses and demographics were gathered via an online survey hosted at TestMyBrain.org. We compared performance among the three groups of interest: educators (N = 598), high neuroscience exposure (N = 234), and the general public (N = 3,045) and analyzed predictors of individual differences in neuromyths performance. In an exploratory factor analysis, we found that a core group of 7 “classic” neuromyths factored together (items related to learning styles, dyslexia, the Mozart effect, the impact of sugar on attention, right-brain/left-brain learners, and using 10% of the brain). The general public endorsed the greatest number of neuromyths (M = 68%), with significantly fewer endorsed by educators (M = 56%), and still fewer endorsed by the high neuroscience exposure group (M = 46%). The two most commonly endorsed neuromyths across all groups were related to learning styles and dyslexia. More accurate performance on neuromyths was predicted by age (being younger), education (having a graduate degree), exposure to neuroscience courses, and exposure to peer-reviewed science. These findings suggest that training in education and neuroscience can help reduce but does not eliminate belief in neuromyths. We discuss the possible underlying roots of the most prevalent neuromyths and implications for classroom practice. These empirical results can be useful for developing comprehensive training modules for educators that target general
Segal, R; Smith, D P
Pharmacists' beliefs about the utility of advertising sources and values for advertising outcomes were studied to learn about the decision-making process for advertising patient oriented pharmacy services in the ambulatory setting. The data suggest that pharmacists in the sample believe advertising through word-of-mouth communication is more likely to result in positive outcomes than either yellow pages or local newspaper advertising.
to the conventional phase-only optimization technique (POT), the geometrical parameters of the array elements are directly optimized to fulfill the far-field requirements, thus maintaining a direct relation between optimization goals and optimization variables. As a result, better designs can be obtained compared...... of the incident field, the choice of basis functions, and the technique to calculate the far-field. Based on accurate reference measurements of two offset reflectarrays carried out at the DTU-ESA Spherical NearField Antenna Test Facility, it was concluded that the three latter factors are particularly important...... using the GDOT to demonstrate its capabilities. To verify the accuracy of the GDOT, two offset contoured beam reflectarrays that radiate a high-gain beam on a European coverage have been designed and manufactured, and subsequently measured at the DTU-ESA Spherical Near-Field Antenna Test Facility...
This study employed a mixed methods and mixed model research design to explore secondary science teachers' beliefs. Specifically, this study focused on factors that secondary science teachers believe affect student achievement in science, and the extent to which teacher beliefs transfer to teacher practice. This study is significant because the outcomes may inform professional development and policy decisions at the school, district, and provincial level. Results from self-reporting data of 82 secondary science teachers indicate that teacher beliefs in each of the fourteen topics surveyed (Classroom Management, Learning Styles, Inclusion, Equity, Science-Technology-Society (STS), Formative Assessment, Summative Assessment, Constructivism, Thematic Approach, Hands-On/Minds-On Activities, The Nature of Science, Science Subject Matter, Electronic Learning and Cooperative Learning) are positive for most Prince Edward Island (P.E.I.) secondary science teachers. Furthermore, secondary science teachers reported having strong beliefs in their ability to affect student learning (self-efficacy beliefs). However, it is apparent from the survey and interview data that teachers believe there are other influential factors that are preventing some students from learning despite the teachers' best efforts and ability. Regarding implementation, this study indicates that beliefs and the enactment of beliefs in classroom practice are positively correlated. The data also shows that at least seventy percent of teachers reported that they implement practices consistent with all but two topics -- The Nature of Science and Electronic Learning -- at least once a week. The findings of this study are discussed in the context of the P.E.I. secondary science setting. Limitations and implications of this study are also addressed.
Shearer, Cameron J; Slattery, Ashley D; Stapleton, Andrew J; Shapter, Joseph G; Gibson, Christopher T
Graphene has emerged as a material with a vast variety of applications. The electronic, optical and mechanical properties of graphene are strongly influenced by the number of layers present in a sample. As a result, the dimensional characterization of graphene films is crucial, especially with the continued development of new synthesis methods and applications. A number of techniques exist to determine the thickness of graphene films including optical contrast, Raman scattering and scanning probe microscopy techniques. Atomic force microscopy (AFM), in particular, is used extensively since it provides three-dimensional images that enable the measurement of the lateral dimensions of graphene films as well as the thickness, and by extension the number of layers present. However, in the literature AFM has proven to be inaccurate with a wide range of measured values for single layer graphene thickness reported (between 0.4 and 1.7 nm). This discrepancy has been attributed to tip-surface interactions, image feedback settings and surface chemistry. In this work, we use standard and carbon nanotube modified AFM probes and a relatively new AFM imaging mode known as PeakForce tapping mode to establish a protocol that will allow users to accurately determine the thickness of graphene films. In particular, the error in measuring the first layer is reduced from 0.1–1.3 nm to 0.1–0.3 nm. Furthermore, in the process we establish that the graphene-substrate adsorbate layer and imaging force, in particular the pressure the tip exerts on the surface, are crucial components in the accurate measurement of graphene using AFM. These findings can be applied to other 2D materials. (paper)
Lischka, Alyson E; Garner, Mary
In this paper we present the development and validation of a Mathematics Teaching Pedagogical and Discourse Beliefs Instrument (MTPDBI), a 20 item partial-credit survey designed and analyzed using Rasch measurement theory. Items on the MTPDBI address beliefs about the nature of mathematics, teaching and learning mathematics, and classroom discourse practices. A Rasch partial credit model (Masters, 1982) was estimated from the pilot study data. Results show that item separation reliability is .96 and person separation reliability is .71. Other analyses indicate the instrument is a viable measure of secondary teachers' beliefs about reform-oriented mathematics teaching and learning. This instrument is proposed as a useful measure of teacher beliefs for those working with pre-service and in-service teacher development.
Bernardo, Allan B I
In this study, the author investigated the epistemological beliefs of 864 bilingual Filipino preservice teachers using Filipino and English versions of the Schommer Epistemological Questionnaire (M. Schommer, 1998). The author conducted confirmatory factor analyses to determine the dimensions and structure of the epistemological beliefs. The results revealed two factors: Simple Learning and Structured Learning. The same factors were found using the Filipino and English versions of the questionnaire. The author discusses the results in terms of how they contribute to the growing evidence regarding the possible problems with particular multidimensional theories and quantitative measures of epistemological beliefs. The results also indicate how the specific epistemological beliefs of the Filipino preservice teachers may reflect features of the Philippine educational system and its tensions regarding pedagogy.
King, Elizabeth A.
A qualitative research study of the beliefs of three science teachers about teaching and educational reform was carried out at a restructured high school belonging to the Coalition of Essential Schools (CES), a nationally prominent restructuring movement. One problem of educational reform is to sustain change in the science classroom. A new wave of reform is shifting the focus away from curriculum changes and towards professionalism of teachers empowered to restructure schools. The beliefs of the teachers are key to decisions made in the classroom. The teachers and staff of Metro High School adopted the Ten Common Principles of CES as their guide to restructuring and sustaining change. Changes included increased authority for teachers in shared decision making, increased staff time for professional development, grouping students heterogeneously, grouping students and faculty in teams for extended time periods, and organizing instruction around small group and individual student study (student-centered). The theoretical framework centers on the constructivist theory of learning, particularly Vygotsky's socio-cultural model, and Bakhtin's dialogic function of language. Nespor's belief system model was used to describe the four characteristic features of beliefs: episodic memories, alternativity, existential presumption, and evaluative loading. My research questions were: What memories of teaching have influenced the teachers? What are the teachers' beliefs about the learning environment? What are the teachers' beliefs about their students? What are the teachers' beliefs about student activities? Interviews were the primary data source for the case studies of the three teachers, with additional data from lesson plans, photo-voice, and other artifacts. The teachers shared many common beliefs including that strong peer support is necessary for reform. The teachers' beliefs allied themselves to the majority of the common principles of CES, especially personalization and
Ottaviani, Marco; Sørensen, Peter Norman
In a binary prediction market in which risk-neutral traders have heterogeneous prior beliefs and are allowed to invest a limited amount of money, the static rational expectations equilibrium price is demonstrated to underreact to information. This effect is consistent with a favorite-longshot bias......, and is more pronounced when prior beliefs are more heterogeneous. Relaxing the assumptions of risk neutrality and bounded budget, underreaction to information also holds in a more general asset market with heterogeneous priors, provided traders have decreasing absolute risk aversion. In a dynamic asset market...
of teaching in a new context and in their early years of the teaching careers of CFL teachers in the Danish context. It has been shown that the multifaceted beliefs that CFL teachers hold are based on their personal experience, shaped by context, and mediated by their classroom practices. The educational...
Mengotti, Paola; Dombert, Pascasie L; Fink, Gereon R; Vossel, Simone
Generating and updating probabilistic models of the environment is a fundamental modus operandi of the human brain. Although crucial for various cognitive functions, the neural mechanisms of these inference processes remain to be elucidated. Here, we show the causal involvement of the right temporoparietal junction (rTPJ) in updating probabilistic beliefs and we provide new insights into the chronometry of the process by combining online transcranial magnetic stimulation (TMS) with computational modeling of behavioral responses. Female and male participants performed a modified location-cueing paradigm, where false information about the percentage of cue validity (%CV) was provided in half of the experimental blocks to prompt updating of prior expectations. Online double-pulse TMS over rTPJ 300 ms (but not 50 ms) after target appearance selectively decreased participants' updating of false prior beliefs concerning %CV, reflected in a decreased learning rate of a Rescorla-Wagner model. Online TMS over rTPJ also impacted on participants' explicit beliefs, causing them to overestimate %CV. These results confirm the involvement of rTPJ in updating of probabilistic beliefs, thereby advancing our understanding of this area's function during cognitive processing. SIGNIFICANCE STATEMENT Contemporary views propose that the brain maintains probabilistic models of the world to minimize surprise about sensory inputs. Here, we provide evidence that the right temporoparietal junction (rTPJ) is causally involved in this process. Because neuroimaging has suggested that rTPJ is implicated in divergent cognitive domains, the demonstration of an involvement in updating internal models provides a novel unifying explanation for these findings. We used computational modeling to characterize how participants change their beliefs after new observations. By interfering with rTPJ activity through online transcranial magnetic stimulation, we showed that participants were less able to update
Ralph Stinebrickner; Todd R. Stinebrickner
Taking advantage of unique longitudinal data, we provide the first characterization of what college students believe at the time of entrance about their final major, relate these beliefs to actual major outcomes, and provide an understanding of why students hold the initial beliefs about majors that they do. The data collection and analysis are based directly on a conceptual model in which a student's final major is best viewed as the end result of a learning process. We find that students en...
Sergio Andrés Suárez Flórez
Full Text Available This study aims at identifying pre-service teachers’ beliefs about teaching English as a foreign language and tracking their potential changes throughout the teaching practicum. Participants were two pre-service teachers in their fifth year of their Bachelor of Arts in Foreign Languages program in a public university in Colombia. Data were gathered through a modified version of Beliefs about Language Learning Inventory before the practicum, eight weekly journal entries administered during ten weeks, and two semi-structured interviews at the end of the teaching practicum. The findings revealed that most of the pre-service teachers’ beliefs changed once they faced the reality of the classroom.
Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.
Deng, Feng; Chai, Ching Sing; Tsai, Chin-Chung; Lee, Min-Hsien
This study aimed to investigate the relationships among practicing teachers' epistemic beliefs, pedagogical beliefs and their beliefs about the use of ICT through survey methodology. Participants were 396 high school practicing teachers from mainland China. The path analysis results analyzed via structural equation modelling technique indicated…
Wang, Yulei; Liu, Jian; Qin, Hong; Yu, Zhi; Yao, Yicun
The Accurate Particle Tracer (APT) code is designed for systematic large-scale applications of geometric algorithms for particle dynamical simulations. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and nonlinear problems. To provide a flexible and convenient I/O interface, the libraries of Lua and Hdf5 are used. Following a three-step procedure, users can efficiently extend the libraries of electromagnetic configurations, external non-electromagnetic forces, particle pushers, and initialization approaches by use of the extendible module. APT has been used in simulations of key physical problems, such as runaway electrons in tokamaks and energetic particles in Van Allen belt. As an important realization, the APT-SW version has been successfully distributed on the world's fastest computer, the Sunway TaihuLight supercomputer, by supporting master-slave architecture of Sunway many-core processors. Based on large-scale simulations of a runaway beam under parameters of the ITER tokamak, it is revealed that the magnetic ripple field can disperse the pitch-angle distribution significantly and improve the confinement of energetic runaway beam on the same time.
This paper proposes an interdisciplinary explanation of the cross-cultural similarities and evolutionary patterns of witchcraft beliefs. It argues that human social dilemmas have led to the evolution of a fear system that is sensitive to signs of deceit and envy. This was adapted in the evolutionary
We study how heterogeneous beliefs about the causes and extent of global warming affect local mitigation and adaptation strategies and therefore global climate dynamics. Local policies are determined by expectations of policy makers about future climate. There are three types of expectations: strong
Educators' beliefs are powerful, affecting not only their pedagogical practices, but also student efficacy and success. The academic achievement of any particular student may rely greatly on whether the teacher believes that student has the ability to succeed. This article affirms the imperative for administrators and educators to spend time…
Sugarman, Hannah; Impey, Chris; Buxner, Sanlyn; Antonellis, Jessie
A survey of the science knowledge and attitudes toward science of nearly 10000 undergraduates at a large public university over a 20-year period included several questions addressing student beliefs in astrology and other forms of pseudoscience. The results from our data reveal that a large majority of students (78%) considered astrology "very" or…
Hansen, Pelle Guldborg
practice such defences are often acknowledged if the belief is reasonable by some general standard, even when this standard does not pertain to the rules currently governing the practice of intercourse in Denmark. As a result it has often been argued that the notion of negligent rape should be introduced...
O'Hair, Dan; Cody, Michael J.
Replicates previous findings of separate Machiavellian belief constructs (Deceit, Flatter, Immorality, and Cynicism). Indicates that different constructs predict selection of compliance-gaining strategies; for example, actors who scored high on Immorality used more referent influence on superiors. Discusses implications of this study concerning a…
Full Text Available The epistemological beliefs in learning process have been investigated from different aspects in relation with many variables in literature. Such beliefs are defined as individuals’ beliefs regarding knowledge and learning. As another related, popular concept, the metacognitive strategies are identified as the strategies used to control the process of obtaining knowledge. Thus, it is seen that both of them are employed to make learning more effective. Within this framework, the aim of the present study was to determine the epistemological beliefs and metacognitive strategies of the pre-service teachers in the distance and formal education English Language Teaching program and to investigate whether there was any difference/ were any differences between them. To collect data, “Epistemological Belief Scale” developed by Schommer (1990 and translated and validated by Deryakulu and Büyüköztürk (2002 and “Metacognitive Strategy Inventory” which was adapted for university students by Yıldız, Akpınar and Ergin (2006 were used. Then through the descriptive method they were analyzed. As a result of study, it was determined that there was a significant relationship between the epistemological beliefs and metacognitive strategy use of ELT pre-service teachers in both formal and distance education programs.
Orosz, Gábor; Krekó, Péter; Paskuj, Benedek; Tóth-Király, István; Bőthe, Beáta; Roland-Lévy, Christine
Conspiracy theory (CT) beliefs can be harmful. How is it possible to reduce them effectively? Three reduction strategies were tested in an online experiment using general and well-known CT beliefs on a comprehensive randomly assigned Hungarian sample ( N = 813): exposing rational counter CT arguments, ridiculing those who hold CT beliefs, and empathizing with the targets of CT beliefs. Several relevant individual differences were measured. Rational and ridiculing arguments were effective in reducing CT, whereas empathizing with the targets of CTs had no effect. Individual differences played no role in CT reduction, but the perceived intelligence and competence of the individual who conveyed the CT belief-reduction information contributed to the success of the CT belief reduction. Rational arguments targeting the link between the object of belief and its characteristics appear to be an effective tool in fighting conspiracy theory beliefs.
The notion of "learner beliefs" has garnered much attention in the field of second language acquisition. Although different studies have been conducted to study learners' beliefs about language learning, little research has looked into the issue of L2 readers' beliefs and their relations to reading strategies. This study investigated…
Full Text Available Abstract Background People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Methods Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Results Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Conclusion Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes
Minas, Harry; Klimidis, Steven; Tuncer, Can
People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes persists despite modernizing and acculturative influences. Different
Dudley, R Thomas
Measures of paranormal belief and emotional intelligence were given a group of 72 college students using Tobacyk's Revised Paranormal Belief Scale and Schutte, Malouff, Hall, Haggerty, Cooper, Golden, and Dornheim's Emotional Intelligence Scale. Order effects indicated that participants who took the Paranormal Belief Scale first had lower emotional intelligence scores than those who took the Emotional Intelligence Scale first. The study demonstrates the importance of taking order effects into account when conducting research on paranormal belief.
Xu, Yi; Hamamura, Takeshi
For the last several decades, Chinese society has experienced transformative changes. How are these changes understood among Chinese people? To examine this question, Part 1 in this research solicited folk beliefs of cultural change from a group of Chinese participants in an open-ended format, and the generated folk beliefs were rated by another group of participants in Part 2 to gage each belief's level of agreement. Part 3 plotted the folk beliefs retained in Part 2 using the Google Ngram V...
Orosz, Gábor; Krekó, Péter; Paskuj, Benedek; Tóth-Király, István; Bőthe, Beáta; Roland-Lévy, Christine
Conspiracy theory (CT) beliefs can be harmful. How is it possible to reduce them effectively? Three reduction strategies were tested in an online experiment using general and well-known CT beliefs on a comprehensive randomly assigned Hungarian sample (N = 813): exposing rational counter CT arguments, ridiculing those who hold CT beliefs, and empathizing with the targets of CT beliefs. Several relevant individual differences were measured. Rational and ridiculing arguments were effective in re...
Severtson, Dolores J; Henriques, Jeffrey B
Lay people have difficulty understanding the meaning of environmental health risk information. Visual images can use features that leverage visual perception capabilities and semiotic conventions to promote meaningful comprehension. Such evidence-based features were employed to develop two images of a color-coded visual scale to convey drinking water test results. The effect of these images and a typical alphanumeric (AN) lab report were explored in a repeated measures randomized trial among 261 undergraduates. Outcome measures included risk beliefs, emotions, personal safety threshold, mitigation intentions, the durability of beliefs and intentions over time, and test result recall. The plain image conveyed the strongest risk message overall, likely due to increased visual salience. The more detailed graded image conveyed a stronger message than the AN format only for females. Images only prompted meaningful risk reduction intentions among participants with optimistically biased safety threshold beliefs. Fuzzy trace theory supported some findings as follow. Images appeared to promote the consolidation of beliefs over time from an initial meaning of safety to an integrated meaning of safety and health risk; emotion potentially shaped this process. Although the AN report fostered more accurate recall, images were related to more appropriate beliefs and intentions at both time points. Findings hinted at the potential for images to prompt appropriate beliefs independent of accurate factual knowledge. Overall, results indicate that images facilitated meaningful comprehension of environmental health risk information and suggest foci for further research.
Hyland, Philip; Shevlin, Mark; Adamson, Gary; Boduszek, Daniel
Rational Emotive Behaviour Therapy (REBT) assumes that rational beliefs act as cognitive protective factors against the development of psychopathology; however little empirical evidence exists regarding the nature of the possible protective effects that they offer. The current study investigates whether rational beliefs moderate the impact of irrational beliefs on posttraumatic stress symptomology (PTS). Three hundred and thirteen active law enforcement, military, and related emergency service personnel took part in the current study. Sequential moderated multiple regression analysis was employed to investigate: (i) the direct impact of irrational beliefs on PTS; (ii) the direct impact of rational beliefs on PTS; (iii) the moderating effects of rational beliefs in the relationship between irrational beliefs and PTS. The irrational beliefs predicted by REBT theory emerged as critical predictors of PTS symptomology, in particular Depreciation beliefs. Rational beliefs (Preferences, and Acceptance beliefs) had a direct, negative impact on levels of PTS, and Acceptance beliefs moderated the impact of Catastrophizing beliefs on PTS. Irrational beliefs are important cognitive vulnerability factors in symptoms of PTS, while rational beliefs (Acceptance) appear to have a protective role in the emergence of PTS symptoms, both directly and by moderating the impact of Catastrophizing beliefs.
Eslinger, James C.
This qualitative study examines the beliefs and belief changes of eleven elementary preservice teachers about teaching science for social justice. Using constructivist grounded theory, it forwards a new theory of belief change about teaching science for social justice. The theory posits that three teaching and learning conditions may facilitate belief change: preservice teachers need to recognize (1) the relationship between science and society; (2) the relationship between individuals and society; and (3) the importance of taking action on socioscientific issues. This research responds to calls by critical scholars of teacher education who contend that beliefs in relation to equity, diversity, and multiculturalism need to be explored. They have found that many preservice teachers hold beliefs that are antithetical to social justice tenets. Since beliefs are generally considered to be precursors to actions, identifying and promoting change in beliefs are important to teaching science for social justice. Such a move may lead to the advancement of curricular and pedagogical efforts to promote the academic participation and success in elementary science of Aboriginal and racialized minority students. The study was undertaken in a year-long science methods course taught by the researcher. It was centered on the preservice teachers -- their beliefs, their belief changes, and the course pedagogies that they identified as crucial to their changes. However, the course was based on the researcher-instructor's review of the scholarly literature on science education, teacher education, and social justice. It utilized a critical -- cultural theoretical framework, and was aligned to the three dimensions of critical nature of science, critical knowledge and pedagogy, and sociopolitical action. Findings indicate that, at the beginning of the year, preservice teachers held two types of beliefs (liberal and critical) and, by the end of the course, they experienced three kinds of
Shin-Young Lee, PhD, RN
Conclusion: Results show the critical need for in-depth understanding of unique health and cultural beliefs about CRC screening in KAs. These beliefs could be useful for future intervention strategies to change health and cultural beliefs in order to increase CRC screening participation in KAs.
Klausen, Søren Harnow
While arguing that many cognitive states do indeed have a characteristic phenomenology, I find reasons for exempting beliefs from the program of cognitive phenomenology. Examining the complex relationship between beliefs and various kinds of conscious experience shows that belief is a messy conce...
According to Alan Millar, justified beliefs are well-founded beliefs. Millar cashes out the notion of well-foundedness in terms of having an adequate reason to believe something and believing it for that reason. To make his account of justified belief compatible with perceptual justification he...
Perea y Monsuwé, Andrés
All equilibrium concepts implicitly make a correct beliefs assumption, stating that a player believes that his opponents are correct about his first-order beliefs. In this paper we show that in many dynamic games of interest, this correct beliefs assumption may be incompatible with a very basic form
Presents an overview of Islamic health care beliefs and practices, noting health-related social and spiritual issues, fundamental beliefs and themes in Islam, health care beliefs and practices common among Muslims, and health-affecting social roles among Muslims. Cultural, religious, and social barriers to health care and ways to reduce them are…
Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan
In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...
Ozfidan, Burhan; Cavlazoglu, Baki; Burlbaw, Lynn; Aydin, Hasan
Achievements of educational reform advantage constructivist understandings of teaching and learning, and therefore highlight a shift in beliefs of teachers and apply these perceptions to the real world. Science teachers' beliefs have been crucial in understanding and reforming science education as beliefs of teachers regarding learning and…
van Elk, Michiel
Previous studies have shown that one's prior beliefs have a strong effect on perceptual decision-making and attentional processing. The present study extends these findings by investigating how individual differences in paranormal and conspiracy beliefs are related to perceptual and attentional biases. Two field studies were conducted in which visitors of a paranormal conducted a perceptual decision making task (i.e. the face/house categorization task; Experiment 1) or a visual attention task (i.e. the global/local processing task; Experiment 2). In the first experiment it was found that skeptics compared to believers more often incorrectly categorized ambiguous face stimuli as representing a house, indicating that disbelief rather than belief in the paranormal is driving the bias observed for the categorization of ambiguous stimuli. In the second experiment, it was found that skeptics showed a classical 'global-to-local' interference effect, whereas believers in conspiracy theories were characterized by a stronger 'local-to-global interference effect'. The present study shows that individual differences in paranormal and conspiracy beliefs are associated with perceptual and attentional biases, thereby extending the growing body of work in this field indicating effects of cultural learning on basic perceptual processes.
Michiel van Elk
Full Text Available Previous studies have shown that one's prior beliefs have a strong effect on perceptual decision-making and attentional processing. The present study extends these findings by investigating how individual differences in paranormal and conspiracy beliefs are related to perceptual and attentional biases. Two field studies were conducted in which visitors of a paranormal conducted a perceptual decision making task (i.e. the face/house categorization task; Experiment 1 or a visual attention task (i.e. the global/local processing task; Experiment 2. In the first experiment it was found that skeptics compared to believers more often incorrectly categorized ambiguous face stimuli as representing a house, indicating that disbelief rather than belief in the paranormal is driving the bias observed for the categorization of ambiguous stimuli. In the second experiment, it was found that skeptics showed a classical 'global-to-local' interference effect, whereas believers in conspiracy theories were characterized by a stronger 'local-to-global interference effect'. The present study shows that individual differences in paranormal and conspiracy beliefs are associated with perceptual and attentional biases, thereby extending the growing body of work in this field indicating effects of cultural learning on basic perceptual processes.
Johnson, Keith; Willoughby, Shannon
This article discusses our investigation regarding nature of science (NOS) implementations and epistemological beliefs within an undergraduate introductory astronomy course. The five year study consists of two years of baseline data in which no explicit use of NOS material was implemented, then three years of subsequent data in which specific NOS material was integrated into the classroom. Our original study covered two years of baseline data and one year of treatment data. Two additional years of treatment course data have revealed intriguing new insights into our students' epistemic belief structure. To monitor the evolution of belief structures across each semester we used student pre-post data on the Epistemological Beliefs About the Physical Sciences (EBAPS) assessment. The collected data were also partitioned and analyzed according to the following variables: college (Letters of Science, Business, Education, etc.), degree (BA or BS), status (freshman, sophomore, etc.), and gender (male or female). We find that the treatment course no longer undergoes significant overall epistemic deterioration after a semester of instruction. We also acquire a more detailed analysis of these findings utilizing the aforementioned variables. Most notably, we see that this intervention had a pronounced positive impact on males and on students within the college of Education, Arts & Architecture, and those with no concentration. Lastly, whether or not students believe their ability to learn science is innate or malleable did not seem to change, remaining a rigid construct with student epistemologies.
Full Text Available This article discusses our investigation regarding nature of science (NOS implementations and epistemological beliefs within an undergraduate introductory astronomy course. The five year study consists of two years of baseline data in which no explicit use of NOS material was implemented, then three years of subsequent data in which specific NOS material was integrated into the classroom. Our original study covered two years of baseline data and one year of treatment data. Two additional years of treatment course data have revealed intriguing new insights into our students’ epistemic belief structure. To monitor the evolution of belief structures across each semester we used student pre-post data on the Epistemological Beliefs About the Physical Sciences (EBAPS assessment. The collected data were also partitioned and analyzed according to the following variables: college (Letters of Science, Business, Education, etc., degree (BA or BS, status (freshman, sophomore, etc., and gender (male or female. We find that the treatment course no longer undergoes significant overall epistemic deterioration after a semester of instruction. We also acquire a more detailed analysis of these findings utilizing the aforementioned variables. Most notably, we see that this intervention had a pronounced positive impact on males and on students within the college of Education, Arts & Architecture, and those with no concentration. Lastly, whether or not students believe their ability to learn science is innate or malleable did not seem to change, remaining a rigid construct with student epistemologies.
Vainikainen, Mari-Pauliina; Wüstenberg, Sascha; Kupiainen, Sirkku; Hotulainen, Risto; Hautamäki, Jarkko
In Finland, schools' effectiveness in fostering the development of transversal skills is evaluated through large-scale learning to learn (LTL) assessments. This article presents how LTL skills--general cognitive competences and learning-related motivational beliefs--develop during primary school and how they predict pupils' CPS skills at the end…
Full Text Available Accurate traffic flow prediction is increasingly essential for successful traffic modeling, operation, and management. Traditional data driven traffic flow prediction approaches have largely assumed restrictive (shallow model architectures and do not leverage the large amount of environmental data available. Inspired by deep learning methods with more complex model architectures and effective data mining capabilities, this paper introduces the deep belief network (DBN and long short-term memory (LSTM to predict urban traffic flow considering the impact of rainfall. The rainfall-integrated DBN and LSTM can learn the features of traffic flow under various rainfall scenarios. Experimental results indicate that, with the consideration of additional rainfall factor, the deep learning predictors have better accuracy than existing predictors and also yield improvements over the original deep learning models without rainfall input. Furthermore, the LSTM can outperform the DBN to capture the time series characteristics of traffic flow data.
Chan, Wayne; McCrae, Robert R.; De Fruyt, Filip; Jussim, Lee; Löckenhoff, Corinna E.; De Bolle, Marleen; Costa, Paul T.; Sutin, Angelina R.; Realo, Anu; Allik, Jüri; Nakazato, Katsuharu; Shimonaka, Yoshiko; Hřebíčková, Martina; Kourilova, Sylvie; Yik, Michelle; Ficková, Emília; Brunner-Sciarra, Marina; de Figueora, Nora Leibovich; Schmidt, Vanina; Ahn, Chang-kyu; Ahn, Hyun-nie; Aguilar-Vafaie, Maria E.; Siuta, Jerzy; Szmigielska, Barbara; Cain, Thomas R.; Crawford, Jarret T.; Mastor, Khairul Anwar; Rolland, Jean-Pierre; Nansubuga, Florence; Miramontez, Daniel R.; Benet-Martínez, Veronica; Rossier, Jérôme; Bratko, Denis; Halberstadt, Jamin; Yamaguchi, Mami; Knežević, Goran; Martin, Thomas A.; Gheorghiu, Mirona; Smith, Peter B.; Barbaranelli, Claduio; Wang, Lei; Shakespeare-Finch, Jane; Lima, Margarida P.; Klinkosz, Waldemar; Sekowski, Andrzej; Alcalay, Lidia; Simonetti, Franco; Avdeyeva, Tatyana V.; Pramila, V. S.; Terracciano, Antonio
Age trajectories for personality traits are known to be similar across cultures. To address whether stereotypes of age groups reflect these age-related changes in personality, we asked participants in 26 countries (N = 3,323) to rate typical adolescents, adults, and old persons in their own country. Raters across nations tended to share similar beliefs about different age groups; adolescents were seen as impulsive, rebellious, undisciplined, preferring excitement and novelty, whereas old people were consistently considered lower on impulsivity, activity, antagonism, and Openness. These consensual age group stereotypes correlated strongly with published age differences on the five major dimensions of personality and most of 30 specific traits, using as criteria of accuracy both self-reports and observer ratings, different survey methodologies, and data from up to 50 nations. However, personal stereotypes were considerably less accurate, and consensual stereotypes tended to exaggerate differences across age groups. PMID:23088227
Smith, Leigh K.
An increasing interest in illuminating the relationships between context and educational reform has led researchers to examine the various interconnected factors that constitute different teaching contexts and the relationships between these elements and teachers' beliefs. The challenge is to identify those aspects of context that facilitate change in teachers' thinking and the way they approach science instruction. This study investigated the relationships between elementary teachers' science-related beliefs and the external forces within the context of their teaching. Using a situated perspective from which to view context, the activity of teaching and the related beliefs of 2 elementary teachers was examined in an effort to better understand the role of context in teachers' thinking about what science is, what it means to teach and learn science, what is involved in reform-based practices, and what science instruction might look like in their classrooms based on their interpretation of reform. Comparative case studies were developed and analyzed using a constant comparative method of analysis. Cross-ease analyses revealed a number of major themes: (a) teachers' science-related beliefs vary in level of commitment; (b) more deeply held beliefs about what it means to teach and learn science, or guiding beliefs, are profoundly resistant to change and are derived primarily from teachers' personal histories both in and outside of schools; (c) guiding beliefs are also shaped by science methods courses, teacher development, and practical classroom experience; (d) less deeply held beliefs, or perceptions of control, are teachers' beliefs about their ability to teach science according to their guiding beliefs in the presence of physical, social, or structural factors within the context of their teaching; (e) guiding beliefs are likely to override perceptions of control, enabling teachers to adapt their teaching contexts; and (f) although all aspects of context impact