Scaling behavior of online human activity

Science.gov (United States)

Zhao, Zhi-Dan; Cai, Shi-Min; Huang, Junming; Fu, Yan; Zhou, Tao

2012-11-01

The rapid development of the Internet technology enables humans to explore the web and record the traces of online activities. From the analysis of these large-scale data sets (i.e., traces), we can get insights about the dynamic behavior of human activity. In this letter, the scaling behavior and complexity of human activity in the e-commerce, such as music, books, and movies rating, are comprehensively investigated by using the detrended fluctuation analysis technique and the multiscale entropy method. Firstly, the interevent time series of rating behaviors of these three types of media show similar scaling properties with exponents ranging from 0.53 to 0.58, which implies that the collective behaviors of rating media follow a process embodying self-similarity and long-range correlation. Meanwhile, by dividing the users into three groups based on their activities (i.e., rating per unit time), we find that the scaling exponents of the interevent time series in the three groups are different. Hence, these results suggest that a stronger long-range correlations exist in these collective behaviors. Furthermore, their information complexities vary in the three groups. To explain the differences of the collective behaviors restricted to the three groups, we study the dynamic behavior of human activity at the individual level, and find that the dynamic behaviors of a few users have extremely small scaling exponents associated with long-range anticorrelations. By comparing the interevent time distributions of four representative users, we can find that the bimodal distributions may bring forth the extraordinary scaling behaviors. These results of the analysis of the online human activity in the e-commerce may not only provide insight into its dynamic behaviors but may also be applied to acquire potential economic interest.

Car-following Behavior Model Learning Using Timed Automata

NARCIS (Netherlands)

Zhang, Yihuan; Lin, Q.; Wang, Jun; Verwer, S.E.; Dochain, D.; Henrion, D.; Peaucelle, D.

Learning driving behavior is fundamental for autonomous vehicles to “understand” traffic situations. This paper proposes a novel method for learning a behavioral model of car-following using automata learning algorithms. The model is interpretable for car-following behavior analysis. Frequent common

Disruptive behaviors in the classroom: initial standardization data on a new teacher rating scale.

Science.gov (United States)

Burns, G L; Owen, S M

1990-10-01

This study presents initial standardization data on the Sutter-Eyberg Student Behavior Inventory (SESBI), a teacher-completed measure of disruptive classroom behaviors. SESBIs were completed on 1116 children in kingergarten through fifth grade in a rural eastern Washington school district. Various analyses (Cronbach's alpha, corrected item-total correlations, average interitem correlations, principal components analyses) indicated that the SESBI provides a homogeneous measure of disruptive behaviors. Support was also found for three factors within the scale (e.g., overt aggression, oppositional behavior, and attentional difficulties). While the child's age did not have a significant effect on the SESBI, the child's gender did have a significant effect on scale scores as well as on most of the items, with males being rated more problematic than females. The SESBI was also able to discriminate between children in treatment for behavioral problems or learning disabilities and children not in treatment.

Neural Behavior Chain Learning of Mobile Robot Actions

Directory of Open Access Journals (Sweden)

Lejla Banjanovic-Mehmedovic

2012-01-01

Full Text Available This paper presents a visual/motor behavior learning approach, based on neural networks. We propose Behavior Chain Model (BCM in order to create a way of behavior learning. Our behavior-based system evolution task is a mobile robot detecting a target and driving/acting towards it. First, the mapping relations between the image feature domain of the object and the robot action domain are derived. Second, a multilayer neural network for offline learning of the mapping relations is used. This learning structure through neural network training process represents a connection between the visual perceptions and motor sequence of actions in order to grip a target. Last, using behavior learning through a noticed action chain, we can predict mobile robot behavior for a variety of similar tasks in similar environment. Prediction results suggest that the methodology is adequate and could be recognized as an idea for designing different mobile robot behaviour assistance.

The Impact of Inattention, Hyperactivity/Impulsivity Symptoms, and Executive Functions on Learning Behaviors of Children with ADHD.

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Colomer, Carla; Berenguer, Carmen; Roselló, Belén; Baixauli, Inmaculada; Miranda, Ana

2017-01-01

Children diagnosed with attention deficit/hyperactivity disorder (ADHD) are at risk of experiencing lower academic achievement compared to their peers without ADHD. However, we have a limited understanding of the mechanisms underlying this association. Both the symptoms of the disorder and the executive functions can negatively influence learning behaviors, including motivation, attitude toward learning, or persistence, key aspects of the learning process. The first objective of this study was to compare different components of learning behaviors in children diagnosed with ADHD and typically developing (TD) children. The second objective was to analyze the relationships among learning behaviors, executive functioning, and symptoms of hyperactivity/impulsivity in both groups. Participants were 35 children diagnosed with ADHD and 37 with TD (7-11 years old), matched on age and IQ. The teachers filled out the Behavior Rating Inventory of Executive Function (BRIEF) and the Learning Behaviors Scale, which evaluates Competence/motivation, Attitude toward learning, Attention/persistence, and Strategy/flexibility. In addition, parents and teachers filled out the DSM-5 diagnostic criteria for ADHD. ANOVAs showed significant differences between children with ADHD and TD children on all the learning behaviors. Moreover, in both the ADHD and TD groups, the behavioral regulation index of the BRIEF predicted the search for strategies, and the metacognition index was a good predictor of motivation. However, attitude toward learning was predicted by metacognition only in the group with ADHD. Therefore, the executive functions had greater power than the typical symptoms of inattention and hyperactivity/impulsivity in predicting learning behaviors of children with ADHD. The findings are in line with other studies that support the influence of the executive functions on performance, highlighting the importance of including their development as a top priority from early ages in the

Aversive Learning and Trait Aggression Influence Retaliatory Behavior.

Science.gov (United States)

Molapour, Tanaz; Lindström, Björn; Olsson, Andreas

2016-01-01

In two experiments (n = 35, n = 34), we used a modified fear-conditioning paradigm to investigate the role of aversive learning in retaliatory behavior in social context. Participants first completed an initial aversive learning phase in which the pairing of a neutral conditioned stimulus (CS; i.e., neutral face) with a naturally aversive unconditioned stimulus (US; electric shock) was learned. Then they were given an opportunity to interact (i.e., administer 0-2 shocks) with the same faces again, during a Test phase. In Experiment 2, we used the same paradigm with the addition of online trial-by-trial ratings (e.g., US expectancy and anger) to examine the role of aversive learning, anger, and the learned expectancy of receiving punishment more closely. Our results indicate that learned aversions influenced future retaliation in a social context. In both experiments, participants showed largest skin conductance responses (SCRs) to the faces paired with one or two shocks, demonstrating successful aversive learning. Importantly, participants administered more shocks to the faces paired with the most number of shocks when the opportunity was given during test. Also, our results revealed that aggressive traits (Buss and Perry Aggression scale) were associated with retaliation only toward CSs associated with aversive experiences. These two experiments show that aggressive traits, when paired with aversive learning experiences enhance the likelihood to act anti-socially toward others.

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems

Science.gov (United States)

Wilson, Robyn S.; Hardisty, David J.; Epanchin-Niell, Rebecca S.; Runge, Michael C.; Cottingham, Kathryn L.; Urban, Dean L.; Maguire, Lynn A.; Hastings, Alan; Mumby, Peter J.; Peters, Debra P.C.

2016-01-01

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

The Relationship among Self-Regulated Learning, Procrastination, and Learning Behaviors in Blended Learning Environment

Science.gov (United States)

Yamada, Masanori; Goda, Yoshiko; Matsuda, Takeshi; Kato, Hiroshi; Miyagawa, Hiroyuki

2015-01-01

This research aims to investigate the relationship among the awareness of self-regulated learning (SRL), procrastination, and learning behaviors in blended learning environment. One hundred seventy nine freshmen participated in this research, conducted in the blended learning style class using learning management system. Data collection was…

Classroom behavior and family climate in students with learning disabilities and hyperactive behavior.

Science.gov (United States)

Margalit, M; Almougy, K

1991-01-01

The present study aimed to identify subtypes of the learning disabilities (LD) syndrome by examining classroom behavior and family climate among four groups of Israeli students ranging in age from 7 to 10 years: 22 students with LD and hyperactive behavior (HB), 22 nonhyperactive students with LD, 20 nondisabled students with HB, and 20 nondisabled nonhyperactive students. Schaefer's Classroom Behavior Inventory and Moos's Family Environmental Scale were administered to teachers and mothers, respectively. The results revealed that higher distractibility and hostility among both groups with HB differentiated between the two groups with LD. Families of children with HB were reported as less supportive and as emphasizing control less. The academic competence and temperament of the nondisabled students with HB were rated as similar to those of the two groups of students with LD. Both groups with LD were characterized by dependent interpersonal relations and by more conflictual families who fostered more achievement but less personal growth.

Learning Theory and Prosocial Behavior

Science.gov (United States)

Rosenhan, D. L.

1972-01-01

Although theories of learning which stress the role of reinforcement can help us understand altruistic behaviors, it seems clear that a more complete comprehension calls for an expansion of our notions of learning, such that they incorporate affect and cognition. (Author/JM)

Shifting workplace behavior to inspire learning: a journey to building a learning culture.

Science.gov (United States)

Schoonbeek, Sue; Henderson, Amanda

2011-01-01

This article discusses the process of building a learning culture. It began with establishing acceptance and connection with the nurse unit manager and the ward team. In the early phases of developing rapport, bullying became apparent. Because bullying undermines sharing and trust, the hallmarks of learning environments, the early intervention work assisted staff to recognize and counteract bullying behaviors. When predominantly positive relationships were restored, interactions that facilitated open communication, including asking questions and providing feedback-behaviors commensurate with learning in the workplace-were developed during regular in-service sessions. Staff participated in role-play and role modeling desired behaviors. Once staff became knowledgeable about positive learning interactions, reward and recognition strategies began to reinforce attitudes and behaviors that align with learning. Through rewards, all nurses had the opportunity to be recognized for their contribution. Nurses who excelled were invited to become champions to continue engaging the key stakeholders to further build the learning environment. Copyright 2011, SLACK Incorporated.

Enriching behavioral ecology with reinforcement learning methods.

Science.gov (United States)

Frankenhuis, Willem E; Panchanathan, Karthik; Barto, Andrew G

2018-02-13

This article focuses on the division of labor between evolution and development in solving sequential, state-dependent decision problems. Currently, behavioral ecologists tend to use dynamic programming methods to study such problems. These methods are successful at predicting animal behavior in a variety of contexts. However, they depend on a distinct set of assumptions. Here, we argue that behavioral ecology will benefit from drawing more than it currently does on a complementary collection of tools, called reinforcement learning methods. These methods allow for the study of behavior in highly complex environments, which conventional dynamic programming methods do not feasibly address. In addition, reinforcement learning methods are well-suited to studying how biological mechanisms solve developmental and learning problems. For instance, we can use them to study simple rules that perform well in complex environments. Or to investigate under what conditions natural selection favors fixed, non-plastic traits (which do not vary across individuals), cue-driven-switch plasticity (innate instructions for adaptive behavioral development based on experience), or developmental selection (the incremental acquisition of adaptive behavior based on experience). If natural selection favors developmental selection, which includes learning from environmental feedback, we can also make predictions about the design of reward systems. Our paper is written in an accessible manner and for a broad audience, though we believe some novel insights can be drawn from our discussion. We hope our paper will help advance the emerging bridge connecting the fields of behavioral ecology and reinforcement learning. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Hoarding behaviors in children with learning disabilities.

Science.gov (United States)

Testa, Renée; Pantelis, Christos; Fontenelle, Leonardo F

2011-05-01

Our objective was to describe the prevalence, comorbidity, and neuropsychological profiles of children with hoarding and learning disabilities. From 61 children with learning disabilities, 16.4% exhibited hoarding as a major clinical issue. Although children with learning disabilities and hoarding displayed greater rates of obsessive-compulsive disorder (30%) as compared to those with learning disabilities without hoarding (5.9%), the majority of patients belonging to the former group did not display obsessive-compulsive disorder diagnosis. When learning disability patients with hoarding were compared to age-, sex-, and IQ-matched learning disability subjects without hoarding, hoarders exhibited a slower learning curve on word list-learning task. In conclusion, salient hoarding behaviors were found to be relatively common in a sample of children with learning disabilities and not necessarily associated with obsessive-compulsive disorder, supporting its nosological independence. It is unclear whether underlying cognitive features may play a major role in the development of hoarding behaviors in children with learning disabilities.

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems.

Science.gov (United States)

Wilson, Robyn S; Hardisty, David J; Epanchin-Niell, Rebecca S; Runge, Michael C; Cottingham, Kathryn L; Urban, Dean L; Maguire, Lynn A; Hastings, Alan; Mumby, Peter J; Peters, Debra P C

2016-02-01

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers' actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed. © 2015

Catalog Learning: Carabid Beetles Learn to Manipulate with Innate Coherent Behavioral Patterns

Directory of Open Access Journals (Sweden)

Zhanna Reznikova

2013-07-01

Full Text Available One of the most fascinating problems in comparative psychology is how learning contributes to solving specific functional problems in animal life, and which forms of learning our species shares with non-human animals. Simulating a natural situation of territorial conflicts between predatory carabids and red wood ants in field and laboratory experiments, we have revealed a relatively simple and quite natural form of learning that has been overlooked. We call it catalog learning, the name we give to the ability of animals to establish associations between stimuli and coherent behavioral patterns (patterns consist of elementary motor acts that have a fixed order. Instead of budgeting their motor acts gradually, from chaotic to rational sequences in order to learn something new, which is characteristic for a conditioning response, animals seem to be “cataloguing” their repertoire of innate coherent behavioral patterns in order to optimize their response to a certain repetitive event. This form of learning can be described as “stimulus-pattern” learning. In our experiments four “wild” carabid species, whose cognitive abilities have never been studied before, modified their behavior in a rather natural manner in order to avoid damage from aggressive ants. Beetles learned to select the relevant coherent behavioral patterns from the set of seven patterns, which are common to all four species and apparently innate. We suggest that this form of learning differs from the known forms of associative learning, and speculate that it is quite universal and can be present in a wide variety of species, both invertebrate and vertebrate. This study suggests a new link between the concepts of cognition and innateness.

Better Behavior for Better Learning.

Science.gov (United States)

Novelli, Joan

1993-01-01

Presents strategies for banishing behavior problems in the classroom and creating a positive learning environment. The behaviors include name calling; hitting and pushing; tattling; poking and touching; overactivity; talking back; complaining about no playmates; being unprepared to work; and lying, cheating, and stealing. On-the-spot solutions are…

Online Behavior Analysis-Based Student Profile for Intelligent E-Learning

Directory of Open Access Journals (Sweden)

Kun Liang

2017-01-01

Full Text Available With the development of mobile platform, such as smart cellphone and pad, the E-Learning model has been rapidly developed. However, due to the low completion rate for E-Learning platform, it is very necessary to analyze the behavior characteristics of online learners to intelligently adjust online education strategy and enhance the quality of learning. In this paper, we analyzed the relation indicators of E-Learning to build the student profile and gave countermeasures. Adopting the similarity computation and Jaccard coefficient algorithm, we designed a system model to clean and dig into the educational data and also the students’ learning attitude and the duration of learning behavior to establish student profile. According to the E-Learning resources and learner behaviors, we also present the intelligent guide model to guide both E-Learning platform and learners to improve learning things. The study on student profile can help the E-Learning platform to meet and guide the students’ learning behavior deeply and also to provide personalized learning situation and promote the optimization of the E-Learning.

A Factor-Analytic Study of Adaptive Behavior and Intellectual Functioning in Learning Disabled Children.

Science.gov (United States)

Yeargan, Dollye R.

The factorial structure of intellectual functioning and adaptive behavior was examined in 160 learning disabled students (6 to 16 years old). Ss were administered the Wechsler Intelligence Scale for Children-Revised (WISC-R) and the Coping Inventory (CI). Factor analysis of WISC-R scores revealed three factors: verbal comprehenson, perceptual…

Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

Science.gov (United States)

Maskey, M.; Ramachandran, R.; Miller, J.

2017-12-01

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

Assessing Student Behaviors and Motivation for Actively Learning Biology

Science.gov (United States)

Moore, Michael Edward

Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is why active learning is such an effective instructional tool and the limits of this instructional method’s ability to influence performance. This dissertation builds a case in three steps for why active learning is an effective instructional tool. In step one, I assessed the influence of different types of active learning (clickers, group activities, and whole class discussions) on student engagement behavior in one semester of two different introductory biology courses and found that active learning positively influenced student engagement behavior significantly more than lecture. For step two, I examined over four semesters whether student engagement behavior was a predictor of performance and found participation (engagement behavior) in the online (video watching) and in-class course activities (clicker participation) that I measure were significant predictors of performance. In the third, I assessed whether certain active learning satisfied the psychological needs that lead to students’ intrinsic motivation to participate in those activities when compared over two semesters and across two different institutions of higher learning. Findings from this last step show us that student’s perceptions of autonomy, competency, and relatedness in doing various types of active learning are significantly higher than lecture and consistent across two institutions of higher learning. Lastly, I tie everything together, discuss implications of the research, and address future directions for research on biology student motivation and behavior.

Millions Learning: Scaling up Quality Education in Developing Countries

Science.gov (United States)

Robinson, Jenny Perlman; Winthrop, Rebecca

2016-01-01

"Millions Learning: Scaling up Quality Education in Developing Countries" tells the story of where and how quality education has scaled in low- and middle-income countries. The story emerges from wide-ranging research on scaling and learning, including 14 in-depth case studies from around the globe. Ultimately, "Millions…

The Prosocial and Antisocial Behavior in Sport Scale.

Science.gov (United States)

Kavussanu, Maria; Boardley, Ian D

2009-02-01

This research aimed to (a) develop a measure of prosocial and antisocial behavior in sport, (b) examine its invariance across sex and sport, and (c) provide evidence for its discriminant and concurrent validity. We conducted two studies. In study 1, team sport athletes (N=1,213) recruited from 103 teams completed questionnaires assessing demographics and prosocial and antisocial behaviors in sport. Factor analyses revealed two factors representing prosocial behavior and two factors representing antisocial behavior. The model had a very good fit to the data and showed configural, metric, and scalar invariance across sex and sport. The final scale consisted of 20 items. In Study 2, team-sport athletes (N=106) completed the scale and measures of empathy and goal orientation. Analyses provided support for the discriminant and concurrent validity of the scale. In conclusion, the new scale can be used to measure prosocial and antisocial behaviors in team sport.

The development and validation of the Epilepsy and Learning Disabilities Quality of Life (ELDQOL) scale.

Science.gov (United States)

Buck, Deborah; Smith, Monica; Appleton, Richard; Baker, Gus A; Jacoby, Ann

2007-02-01

Few suitable instruments exist for use with people, especially children, with both epilepsy and learning disabilities. One such measure is the Epilepsy and Learning Disabilities Quality of Life scale (ELDQOL), which has recently undergone revision following feedback from relevant users. This article reports on the final psychometric testing phase of this scale. ELDQOL consists of 70 items covering seizure severity, seizure-related injuries, antiepileptic drug side effects, behavior, mood, physical, cognitive, and social functioning, parental concern, communication, overall quality of life, and overall health. Revalidation involved a qualitative phase, to ascertain users' opinions on the wording, coverage, and layout of the questionnaire, and a quantitative phase, to examine internal consistency, test-retest reliability, and validity. There is very good evidence of the reliability and validity of the final version of ELDQOL, making it a promising instrument for assessing quality of life in children/young adults with epilepsy and learning disabilities.

Review: The Necessity of Producing/Normalizing Adaptive Behavior Scales in Diagnosing Training Treatment Rehabilitation of Peop e and Assessment of the Programs

Directory of Open Access Journals (Sweden)

Seyyed Jalal Sadrosadat

2000-10-01

Full Text Available Adaptive behavior is defined as the manner in which people cope with the natural and social demands of their environments. Impairments in adaptive behavior are described as significant limitations in an individual's effectiveness in meeting the standards of maturation, learning, personal independence, and/or social responsibility that are expected for one's age level and cultural group, as determined by clinical assessment, and usually, standardized scales. The definitions of adaptive deficiencies imply an individual's ability to cope with demands of his or her environment. Some scholars support this notion when describing adaptive behavior's relationship to mental retardation. Despite the fact that adaptive behavior scales are the necessary tools in diagnosing training: treatment. Rehabilitation of people (Particularly with developmental disorders and the assessment of programs, those are not available to professionals. This article tries to explain the necessity of producing/normalizing such scales, and introduces one of the most famous scales named as "Adaptive Behavior Scale-Residential and Community".

Decentralized Reinforcement Learning of robot behaviors

NARCIS (Netherlands)

Leottau, David L.; Ruiz-del-Solar, Javier; Babuska, R.

2018-01-01

A multi-agent methodology is proposed for Decentralized Reinforcement Learning (DRL) of individual behaviors in problems where multi-dimensional action spaces are involved. When using this methodology, sub-tasks are learned in parallel by individual agents working toward a common goal. In

Integrating cross-scale analysis in the spatial and temporal domains for classification of behavioral movement

Directory of Open Access Journals (Sweden)

Ali Soleymani

2014-06-01

Full Text Available Since various behavioral movement patterns are likely to be valid within different, unique ranges of spatial and temporal scales (e.g., instantaneous, diurnal, or seasonal with the corresponding spatial extents, a cross-scale approach is needed for accurate classification of behaviors expressed in movement. Here, we introduce a methodology for the characterization and classification of behavioral movement data that relies on computing and analyzing movement features jointly in both the spatial and temporal domains. The proposed methodology consists of three stages. In the first stage, focusing on the spatial domain, the underlying movement space is partitioned into several zonings that correspond to different spatial scales, and features related to movement are computed for each partitioning level. In the second stage, concentrating on the temporal domain, several movement parameters are computed from trajectories across a series of temporal windows of increasing sizes, yielding another set of input features for the classification. For both the spatial and the temporal domains, the ``reliable scale'' is determined by an automated procedure. This is the scale at which the best classification accuracy is achieved, using only spatial or temporal input features, respectively. The third stage takes the measures from the spatial and temporal domains of movement, computed at the corresponding reliable scales, as input features for behavioral classification. With a feature selection procedure, the most relevant features contributing to known behavioral states are extracted and used to learn a classification model. The potential of the proposed approach is demonstrated on a dataset of adult zebrafish (Danio rerio swimming movements in testing tanks, following exposure to different drug treatments. Our results show that behavioral classification accuracy greatly increases when firstly cross-scale analysis is used to determine the best analysis scale, and

Determining the Effects of LMS Learning Behaviors on Academic Achievement in a Learning Analytic Perspective

OpenAIRE

Mehmet FIRAT

2016-01-01

Two of the most important outcomes of learning analytics are predicting students’ learning and providing effective feedback. Learning Management Systems (LMS), which are widely used to support online and face-to-face learning, provide extensive research opportunities with detailed records of background data regarding users’ behaviors. The purpose of this study was to investigate the effects of undergraduate students’ LMS learning behaviors on their academic achievements. In line with this pur...

How Does Self-Regulated Learning Relate to Active Procrastination and Other Learning Behaviors?

Science.gov (United States)

Yamada, Masanori; Goda, Yoshiko; Matsuda, Takeshi; Saito, Yutaka; Kato, Hiroshi; Miyagawa, Hiroyuki

2016-01-01

This research investigates the relationship between self-regulated learning awareness, procrastination, and learning behaviors in a blended learning environment. Participants included 179 first-grade university students attending a blended learning-style class that used a learning management system. Data were collected using questionnaires on…

Frustration-Instigated Behavior and Learned Helplessness.

Science.gov (United States)

Winefield, Anthony H.

1979-01-01

Compares M. E. P. Seligman's recent work on learned helplessness with N. R. F. Maier's 30-year-old work on frustration behavior. Notes striking similarities between the two approaches. Concludes that the learned helplessness model might explain the "abnormal fixations" that Maier reported. (Author/RL)

Using Mobile Learning: Determinates Impacting Behavioral Intention

Science.gov (United States)

Lowenthal, Jeffrey N.

2010-01-01

This study examined the factors or determinates that impact the behavioral intention of students to use mobile learning (m-learning) technology. These determinates include performance expectancy, effort expectancy, and self-management of learning, all mediated by age, gender, or both. Regression coefficients showed strong and significant…

The Impact on Career Development of Learning Opportunities and Learning Behavior at Work.

Science.gov (United States)

Van der Sluis, Lidewey E. C.; Poell, Rob E.

2003-01-01

Survey responses were received in 1998 (n=63) and 1999 (n=98) from master's of business administration graduates. Hierarchical regression and difference of means tests found that career development depended on learning opportunities at work and on individual learning behavior. Behavior was more predictive of objective career development measures,…

Learning a decision maker's utility function from (possibly) inconsistent behavior

DEFF Research Database (Denmark)

Nielsen, Thomas Dyhre; Jensen, Finn Verner

2004-01-01

developed for learning the probabilities from a database.However, methods for learning the utilities have only received limitedattention in the computer science community. A promising approach for learning a decision maker's utility function is to takeoutset in the decision maker's observed behavioral...... patterns, and then find autility function which (together with a domain model) can explainthis behavior. That is, it is assumed that decision maker's preferences arereflected in the behavior. Standard learning algorithmsalso assume that the decision maker is behavioralconsistent, i.e., given a model ofthe...... decision problem, there exists a utility function which canaccount for all the observed behavior. Unfortunately, this assumption israrely valid in real-world decision problems, and in these situationsexisting learning methods may only identify a trivial utilityfunction. In this paper we relax...

The Impact of Individual Differences on E-Learning System Behavioral Intention

Science.gov (United States)

Liao, Peiwen; Yu, Chien; Yi, Chincheh

This study investigated the impact of contingent variables on the relationship between four predictors and employees' behavioral intention with e-learning. Seven hundred and twenty-two employees in online training and education were asked to answer questionnaires about their learning styles, perceptions of the quality of the proposed predictors and behavioral intention with e-learning systems. The results of analysis showed that three contingent variables, gender, job title and industry, significantly influenced the perceptions of predictors and employees' behavioral intention with the e-learning system. This study also found a statistically significant moderating effect of two contingent variables, gender, job title and industry, on the relationship between predictors and e-learning system behavioral intention. The results suggest that a serious consideration of contingent variables is crucial for improving e-learning system behavioral intention. The implications of these results for the management of e-learning systems are discussed.

Scaling behavior of gas permeability measurements in volcanic tuffs

International Nuclear Information System (INIS)

Tidwell, V.C.

1994-01-01

One of the critical issues facing the Yucca Mountain site characterization and performance assessment programs is the manner in which property scaling is addressed. Property scaling becomes an issue whenever heterogeneous media properties are measured at one scale but applied at another. A research program has been established to challenge current understanding of property scaling with the aim of developing and testing models that describe scaling behavior in a quantitative manner. Scaling of constitutive rock properties is investigated through physical experimentation involving the collection of suites of gas-permeability data measured over a range of discrete scales. The approach is to systematically isolate those factors believed to influence property scaling and investigate their relative contributions to overall scaling behavior. Two blocks of tuff, each exhibiting differing heterogeneity structure, have recently been examined. Results of the investigation show very different scaling behavior, as exhibited by changes in the distribution functions and variograms, for the two tuff samples. Even for the relatively narrow range of measurement scales employed significant changes in the distribution functions, variograms, and summary statistics occurred. Because such data descriptors will likely play an important role in calculating effective media properties, these results demonstrate both the need to understand and accurately model scaling behavior

Self-regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison Between Professional Training and English Learning.

Science.gov (United States)

Tseng, Min-Chen; Chen, Chia-Cheng

2017-06-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between students' professional training and English learning. The participants consisted of 344 arts majors. The Academic Self-Regulation Questionnaire and the Revised Learning Process Questionnaire were adopted to examine students' self-regulatory behaviors and their approaches to learning. The results show that a positive and significant correlation was found in students' self-regulatory behaviors between professional training and English learning. The results indicated that increases in using self-regulatory behaviors in professional training were associated with increases in applying self-regulatory behaviors in learning English. Seeking assistance, self-evaluation, and planning and organizing were significant predictors for learning English. In addition, arts students used the deep approach more often than the surface approach in both their professional training and English learning. A positive correlation was found in DA, whereas a negative correlation was shown in SA between students' self-regulatory behaviors and their approaches to learning. Students with high self-regulation adopted a deep approach, and they applied the surface approach less in professional training and English learning. In addition, a SEM model confirmed that DA had a positive influence; however, SA had a negative influence on self-regulatory behaviors.

Developing the Cyber Victimization Experiences and Cyberbullying Behaviors Scales.

Science.gov (United States)

Betts, Lucy R; Spenser, Karin A

2017-01-01

The reported prevalence rates of cyber victimization experiences and cyberbullying behaviors vary. Part of this variation is likely due to the diverse definitions and operationalizations of the constructs adopted in previous research and the lack of psychometrically robust measures. Through 2 studies, the authors developed (Study 1) and evaluated (Study 2) the cyber victimization experiences and cyberbullying behaviors scales. Participants in Study 1 were 393 (122 boys, 171 girls) and in Study 2 were 345 (153 boys, 192 girls) 11-15-year-olds who completed measures of cyber victimization experiences, cyberbullying behaviors, face-to-face victimization experiences, face-to-face bullying behaviors, and social desirability. The 3-factor cyber victimization experiences scale comprised threat, shared images, and personal attack. The 3-factor cyberbullying behaviors scale comprised sharing images, gossip, and personal attack. Both scales demonstrated acceptable internal consistency and convergent validity.

Instructional control of reinforcement learning: a behavioral and neurocomputational investigation.

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Doll, Bradley B; Jacobs, W Jake; Sanfey, Alan G; Frank, Michael J

2009-11-24

Humans learn how to behave directly through environmental experience and indirectly through rules and instructions. Behavior analytic research has shown that instructions can control behavior, even when such behavior leads to sub-optimal outcomes (Hayes, S. (Ed.). 1989. Rule-governed behavior: cognition, contingencies, and instructional control. Plenum Press.). Here we examine the control of behavior through instructions in a reinforcement learning task known to depend on striatal dopaminergic function. Participants selected between probabilistically reinforced stimuli, and were (incorrectly) told that a specific stimulus had the highest (or lowest) reinforcement probability. Despite experience to the contrary, instructions drove choice behavior. We present neural network simulations that capture the interactions between instruction-driven and reinforcement-driven behavior via two potential neural circuits: one in which the striatum is inaccurately trained by instruction representations coming from prefrontal cortex/hippocampus (PFC/HC), and another in which the striatum learns the environmentally based reinforcement contingencies, but is "overridden" at decision output. Both models capture the core behavioral phenomena but, because they differ fundamentally on what is learned, make distinct predictions for subsequent behavioral and neuroimaging experiments. Finally, we attempt to distinguish between the proposed computational mechanisms governing instructed behavior by fitting a series of abstract "Q-learning" and Bayesian models to subject data. The best-fitting model supports one of the neural models, suggesting the existence of a "confirmation bias" in which the PFC/HC system trains the reinforcement system by amplifying outcomes that are consistent with instructions while diminishing inconsistent outcomes.

Iterative perceptual learning for social behavior synthesis

NARCIS (Netherlands)

de Kok, I.A.; Poppe, Ronald Walter; Heylen, Dirk K.J.

We introduce Iterative Perceptual Learning (IPL), a novel approach to learn computational models for social behavior synthesis from corpora of human–human interactions. IPL combines perceptual evaluation with iterative model refinement. Human observers rate the appropriateness of synthesized

The Impact of Cognitive Dissonance on Learning Work Behavior

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Dechawatanapaisal, Decha; Siengthai, Sununta

2006-01-01

Purpose: This research proposes a framework, which identifies the underlying factors that shape learning behavior in the workplace. It takes organizational members' perspectives into consideration to gain better understanding on managing people and their behavior in the organizational learning process. Design/methodology/approach: Primary data…

The Impact of Robot Tutor Nonverbal Social Behavior on Child Learning

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James Kennedy

2017-04-01

Full Text Available Several studies have indicated that interacting with social robots in educational contexts may lead to a greater learning than interactions with computers or virtual agents. As such, an increasing amount of social human–robot interaction research is being conducted in the learning domain, particularly with children. However, it is unclear precisely what social behavior a robot should employ in such interactions. Inspiration can be taken from human–human studies; this often leads to an assumption that the more social behavior an agent utilizes, the better the learning outcome will be. We apply a nonverbal behavior metric to a series of studies in which children are taught how to identify prime numbers by a robot with various behavioral manipulations. We find a trend, which generally agrees with the pedagogy literature, but also that overt nonverbal behavior does not account for all learning differences. We discuss the impact of novelty, child expectations, and responses to social cues to further the understanding of the relationship between robot social behavior and learning. We suggest that the combination of nonverbal behavior and social cue congruency is necessary to facilitate learning.

Learning Behavior Models for Interpreting and Predicting Traffic Situations

OpenAIRE

Gindele, Tobias

2014-01-01

In this thesis, we present Bayesian state estimation and machine learning methods for predicting traffic situations. The cognitive ability to assess situations and behaviors of traffic participants, and to anticipate possible developments is an essential requirement for several applications in the traffic domain, especially for self-driving cars. We present a method for learning behavior models from unlabeled traffic observations and develop improved learning methods for decision trees.

Iterative Perceptual Learning for Social Behavior Synthesis

NARCIS (Netherlands)

de Kok, I.A.; Poppe, Ronald Walter; Heylen, Dirk K.J.

We introduce Iterative Perceptual Learning (IPL), a novel approach for learning computational models for social behavior synthesis from corpora of human-human interactions. The IPL approach combines perceptual evaluation with iterative model refinement. Human observers rate the appropriateness of

Science Curiosity in Learning Environments: Developing an Attitudinal Scale for Research in Schools, Homes, Museums, and the Community

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Weible, Jennifer L.; Zimmerman, Heather Toomey

2016-01-01

Although curiosity is considered an integral aspect of science learning, researchers have debated how to define, measure, and support its development in individuals. Prior measures of curiosity include questionnaire type scales (primarily for adults) and behavioral measures. To address the need to measure scientific curiosity, the Science…

Active Learning of Classification Models with Likert-Scale Feedback.

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Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone.

Observing Animal Behavior at the Zoo: A Learning Laboratory

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Hull, Debra B.

2003-01-01

Undergraduate students in a learning laboratory course initially chose a species to study; researched that species' physical and behavioral characteristics; then learned skills necessary to select, operationalize, observe, and record animal behavior accurately. After their classroom preparation, students went to a local zoo to observe the behavior…

The impact on career development of learning opportunities and learning behavior at work

NARCIS (Netherlands)

van der Sluis, E.C.; Poell, R.F.

2003-01-01

This study focuses on the individual career development process of M.B.A.s on the job, in an era emphasizing personal responsibility for learning and development. The impact of learning opportunities and individual learning behavior was analyzed through repeated measures. Hierarchical regressions

Learning design and feedback processes at scale

DEFF Research Database (Denmark)

Ringtved, Ulla L.; Miligan, Sandra; Corrin, Linda

2016-01-01

Design for teaching in scaled courses is shifting away from replication of the traditional on-campus or online teaching-learning relationship towards exploiting the distinctive characteristic and potentials of that environment to transform both teaching and learning. This involves consideration...... design and would benefit from learning analytics support? What is the character of analytics that can be deployed to help deliver good design of online learning platforms? What are the theoretical and pedagogical bases inherent in different analytics designs? These and other questions will be examined...

Scaling behavior of heavy fermion metals

Energy Technology Data Exchange (ETDEWEB)

Shaginyan, V.R., E-mail: vrshag@thd.pnpi.spb.r [Petersburg Nuclear Physics Institute, RAS, Gatchina, 188300 (Russian Federation); CTSPS, Clark Atlanta University, Atlanta, GA 30314 (United States); Amusia, M.Ya. [Racah Institute of Physics, Hebrew University, Jerusalem 91904 (Israel); Ioffe Physical Technical Institute, RAS, St. Petersburg 194021 (Russian Federation); Msezane, A.Z. [CTSPS, Clark Atlanta University, Atlanta, GA 30314 (United States); Popov, K.G. [Komi Science Center, Ural Division, RAS, 3a, Chernova str. Syktyvkar, 167982 (Russian Federation)

2010-07-15

Strongly correlated Fermi systems are fundamental systems in physics that are best studied experimentally, which until very recently have lacked theoretical explanations. This review discusses the construction of a theory and the analysis of phenomena occurring in strongly correlated Fermi systems such as heavy-fermion (HF) metals and two-dimensional (2D) Fermi systems. It is shown that the basic properties and the scaling behavior of HF metals can be described within the framework of a fermion condensation quantum phase transition (FCQPT) and an extended quasiparticle paradigm that allow us to explain the non-Fermi liquid behavior observed in strongly correlated Fermi systems. In contrast to the Landau paradigm stating that the quasiparticle effective mass is a constant, the effective mass of new quasiparticles strongly depends on temperature, magnetic field, pressure, and other parameters. Having analyzed the collected facts on strongly correlated Fermi systems with quite a different microscopic nature, we find these to exhibit the same non-Fermi liquid behavior at FCQPT. We show both analytically and using arguments based entirely on the experimental grounds that the data collected on very different strongly correlated Fermi systems have a universal scaling behavior, and materials with strongly correlated fermions can unexpectedly be uniform in their diversity. Our analysis of strongly correlated systems such as HF metals and 2D Fermi systems is in the context of salient experimental results. Our calculations of the non-Fermi liquid behavior, the scales and thermodynamic, relaxation and transport properties are in good agreement with experimental facts.

Observations of Student Behavior in Collaborative Learning Groups

Science.gov (United States)

Adams, Jeffrey P.; Brissenden, Gina; Lindell, Rebecca S.; Slater, Timothy F.; Wallace, Joy

In an effort to determine how our students were responding to the use of collaborative learning groups in our large enrollment introductory astronomy (ASTRO 101) courses, we systematically observed the behavior of 270 undergraduate students working in 48 self-formed groups. Their observed behaviors were classified as: (i) actively engaged; (ii) watching actively; (iii) watching passively; and (iv) disengaged. We found that male behavior is consistent regardless of the sex-composition of the groups. However, females were categorized as watching passively and or disengaged significantly more frequently when working in groups that contained uneven numbers of males and females. This case study observation suggests that faculty who use collaborative learning groups might find that the level of student participation in collaborative group learning activities can depend on the sex-composition of the group.

Mechanisms of social avoidance learning can explain the emergence of adaptive and arbitrary behavioral traditions in humans.

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Lindström, Björn; Olsson, Andreas

2015-06-01

Many nonhuman animals preferentially copy the actions of others when the environment contains predation risk or other types of danger. In humans, the role of social learning in avoidance of danger is still unknown, despite the fundamental importance of social learning for complex social behaviors. Critically, many social behaviors, such as cooperation and adherence to religious taboos, are maintained by threat of punishment. However, the psychological mechanisms allowing threat of punishment to generate such behaviors, even when actual punishment is rare or absent, are largely unknown. To address this, we used both computer simulations and behavioral experiments. First, we constructed a model where simulated agents interacted under threat of punishment and showed that mechanisms' (a) tendency to copy the actions of others through social learning, together with (b) the rewarding properties of avoiding a threatening punishment, could explain the emergence, maintenance, and transmission of large-scale behavioral traditions, both when punishment is common and when it is rare or nonexistent. To provide empirical support for our model, including the 2 mechanisms, we conducted 4 experiments, showing that humans, if threatened with punishment, are exceptionally prone to copy and transmit the behavior observed in others. Our results show that humans, similar to many nonhuman animals, use social learning if the environment is perceived as dangerous. We provide a novel psychological and computational basis for a range of human behaviors characterized by the threat of punishment, such as the adherence to cultural norms and religious taboos. (c) 2015 APA, all rights reserved).

Learning Analytics focused on student behavior. Case study: dropout in distance learning institutions

Directory of Open Access Journals (Sweden)

Jose Aguilar

2017-04-01

Full Text Available Normally, Learning Analytics (LA can be focused on the analysis of the learning process or the student behavior. In this paper is analyzed the use of LA in the context of distance learning universities, particularly focuses on the students’ behavior. We propose to use a new concept, called "Autonomic Cycle of Learning Analysis Tasks", which defines a set of tasks of LA, whose common objective is to achieve an improvement in the process under study. In this paper, we develop the "Autonomic Cycle of LA Tasks" to analyze the dropout in distance learning institutions. We use a business intelligence methodology in order to develop the "Autonomic Cycle of LA Tasks" for the analysis of the dropout in distance learning. The Autonomic Cycle identifies factors that influence the decision of a student to abandon their studies, predicts the potentially susceptible students to abandon their university studies, and define a motivational pattern for these students.

Determining the Effects of LMS Learning Behaviors on Academic Achievement in a Learning Analytic Perspective

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Mehmet FIRAT

2016-02-01

Full Text Available Two of the most important outcomes of learning analytics are predicting students’ learning and providing effective feedback. Learning Management Systems (LMS, which are widely used to support online and face-to-face learning, provide extensive research opportunities with detailed records of background data regarding users’ behaviors. The purpose of this study was to investigate the effects of undergraduate students’ LMS learning behaviors on their academic achievements. In line with this purpose, the participating students’ online learning behaviors in LMS were examined by using learning analytics for 14 weeks, and the relationship between students’ behaviors and their academic achievements was analyzed, followed by an analysis of their views about the influence of LMS on their academic achievement. The present study, in which quantitative and qualitative data were collected, was carried out with the explanatory mixed method. A total of 71 undergraduate students participated in the study. The results revealed that the students used LMSs as a support to face-to-face education more intensively on course days (at the beginning of the related lessons and at nights on course days and that they activated the content elements the most. Lastly, almost all the students agreed that LMSs helped increase their academic achievement only when LMSs included such features as effectiveness, interaction, reinforcement, attractive design, social media support, and accessibility.

Learning assessment for students with mental and behavioral disorders

DEFF Research Database (Denmark)

Dræby, Anders

The session aims at presenting a learning-based model for how to conduct a comprehensive psychological evaluation of the learning resources and challenges amongst students with mental and behavioral disorders. In the learning assessment model the learning resources and challenges of the students...

Scaling prediction errors to reward variability benefits error-driven learning in humans.

Science.gov (United States)

Diederen, Kelly M J; Schultz, Wolfram

2015-09-01

Effective error-driven learning requires individuals to adapt learning to environmental reward variability. The adaptive mechanism may involve decays in learning rate across subsequent trials, as shown previously, and rescaling of reward prediction errors. The present study investigated the influence of prediction error scaling and, in particular, the consequences for learning performance. Participants explicitly predicted reward magnitudes that were drawn from different probability distributions with specific standard deviations. By fitting the data with reinforcement learning models, we found scaling of prediction errors, in addition to the learning rate decay shown previously. Importantly, the prediction error scaling was closely related to learning performance, defined as accuracy in predicting the mean of reward distributions, across individual participants. In addition, participants who scaled prediction errors relative to standard deviation also presented with more similar performance for different standard deviations, indicating that increases in standard deviation did not substantially decrease "adapters'" accuracy in predicting the means of reward distributions. However, exaggerated scaling beyond the standard deviation resulted in impaired performance. Thus efficient adaptation makes learning more robust to changing variability. Copyright © 2015 the American Physiological Society.

Factor Structure of Child Behavior Scale Scores in Peruvian Preschoolers

Science.gov (United States)

Meyer, Erin L.; Schaefer, Barbara A.; Soto, Cesar Merino; Simmons, Crystal S.; Anguiano, Rebecca; Brett, Jeremy; Holman, Alea; Martin, Justin F.; Hata, Heidi K.; Roberts, Kimberly J.; Mello, Zena R.; Worrell, Frank C.

2011-01-01

Behavior rating scales aid in the identification of problem behaviors, as well as the development of interventions to reduce such behavior. Although scores on many behavior rating scales have been validated in the United States, there have been few such studies in other cultural contexts. In this study, the structural validity of scores on a…

A Social Learning Model of Adolescent Contraceptive Behavior.

Science.gov (United States)

Balassone, Mary Lou

1991-01-01

Research findings and theories regarding adolescent contraceptive use are reviewed to propose an alternative framework relying on social learning theory. Environmental context, cognitive influences, and behavior execution constraints are suggested as the foundation for contraceptive behaviors. The behavioral skills teenagers need to use birth…

Teacher Behavioral Practices: Relations to Student Risk Behaviors, Learning Barriers, and School Climate

Science.gov (United States)

Martinez, Andrew; Mcmahon, Susan D.; Coker, Crystal; Keys, Christopher B.

2016-01-01

Student behavioral problems pose a myriad of challenges for schools. In this study, we examine the relations among teacher and school-level constructs (i.e., teacher collaboration, supervision/discipline, instructional management), and student-related outcomes (i.e., high-risk behaviors, barriers to learning, student social-behavioral climate).…

Spanish adaptation of the Participatory Behaviors Scale (PBS

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Alejandro Magallares

2016-04-01

Full Text Available The aim of this study was to adapt the Participatory Behaviors Scale (PBS and validate the results for use among the Spanish population. Using snowball sampling methodology, 501 individuals from all areas of Spain were selected to participate in the study. The Participatory Behaviors Scale (PBS and questionnaires that measure a sense of community, belief in a just world and Machiavellianism were used to analyze the criterion validity of the adapted scale. A confirmatory factor analysis indicated that the items on the questionnaire fit a second-order model with four factors, which corresponded to the four dimensions proposed by the original authors, namely, disengagement, civil participation, formal political participation and activism. Additionally, it has been found that the scale is related to a sense of community, belief in a just world and Machiavellianism. In light of these results, we concluded that the questionnaire is methodologically valid and can be used by the scientific community to measure participatory behavior.

Behavior learning in differential games and reorientation maneuvers

Science.gov (United States)

Satak, Neha

The purpose of this dissertation is to apply behavior learning concepts to incomplete- information continuous time games. Realistic game scenarios are often incomplete-information games in which the players withhold information. A player may not know its opponent's objectives and strategies prior to the start of the game. This lack of information can limit the player's ability to play optimally. If the player can observe the opponent's actions, it can better optimize its achievements by taking corrective actions. In this research, a framework to learn an opponent's behavior and take corrective actions is developed. The framework will allow a player to observe the opponent's actions and formulate behavior models. The developed behavior model can then be utilized to find the best actions for the player that optimizes the player's objective function. In addition, the framework proposes that the player plays a safe strategy at the beginning of the game. A safe strategy is defined in this research as a strategy that guarantees a minimum pay-off to the player independent of the other player's actions. During the initial part of the game, the player will play the safe strategy until it learns the opponent's behavior. Two methods to develop behavior models that differ in the formulation of the behavior model are proposed. The first method is the Cost-Strategy Recognition (CSR) method in which the player formulates an objective function and a strategy for the opponent. The opponent is presumed to be rational and therefore will play to optimize its objective function. The strategy of the opponent is dependent on the information available to the opponent about other players in the game. A strategy formulation presumes a certain level of information available to the opponent. The previous observations of the opponent's actions are used to estimate the parameters of the formulated behavior model. The estimated behavior model predicts the opponent's future actions. The second

Patterns in clinical students' self-regulated learning behavior: a Q-methodology study.

Science.gov (United States)

Berkhout, Joris J; Teunissen, Pim W; Helmich, Esther; van Exel, Job; van der Vleuten, Cees P M; Jaarsma, Debbie A D C

2017-03-01

Students feel insufficiently supported in clinical environments to engage in active learning and achieve a high level of self-regulation. As a result clinical learning is highly demanding for students. Because of large differences between students, supervisors may not know how to support them in their learning process. We explored patterns in undergraduate students' self-regulated learning behavior in the clinical environment, to improve tailored supervision, using Q-methodology. Q-methodology uses features of both qualitative and quantitative methods for the systematic investigation of subjective issues by having participants sort statements along a continuum to represent their opinion. We enrolled 74 students between December 2014 and April 2015 and had them characterize their learning behavior by sorting 52 statements about self-regulated learning behavior and explaining their response. The statements used for the sorting were extracted from a previous study. The data was analyzed using by-person factor analysis to identify clusters of individuals with similar sorts of the statements. The resulting factors and qualitative data were used to interpret and describe the patterns that emerged. Five resulting patterns were identified in students' self-regulated learning behavior in the clinical environment, which we labelled: Engaged, Critically opportunistic, Uncertain, Restrained and Effortful. The five patterns varied mostly regarding goals, metacognition, communication, effort, and dependence on external regulation for learning. These discrete patterns in students' self-regulated learning behavior in the clinical environment are part of a complex interaction between student and learning context. The results suggest that developing self-regulated learning behavior might best be supported regarding individual students' needs.

Predicting risk behaviors: development and validation of a diagnostic scale.

Science.gov (United States)

Witte, K; Cameron, K A; McKeon, J K; Berkowitz, J M

1996-01-01

The goal of this study was to develop and validate the Risk Behavior Diagnosis (RBD) Scale for use by health care providers and practitioners interested in promoting healthy behaviors. Theoretically guided by the Extended Parallel Process Model (EPPM; a fear appeal theory), the RBD scale was designed to work in conjunction with an easy-to-use formula to determine which types of health risk messages would be most appropriate for a given individual or audience. Because some health risk messages promote behavior change and others backfire, this type of scale offers guidance to practitioners on how to develop the best persuasive message possible to motivate healthy behaviors. The results of the study demonstrate the RBD scale to have a high degree of content, construct, and predictive validity. Specific examples and practical suggestions are offered to facilitate use of the scale for health practitioners.

Behavioral Style, Culture, and Teaching and Learning.

Science.gov (United States)

Hilliard, Asa G., III

1992-01-01

Argues that unique behavioral styles can be identified among African-American populations and that behavioral style may help explain differences in test performance for white and African-American students. Implications for all students of providing stylistic diversity in the schools and student ability to use multiple learning styles are…

Leaders Who Learn: The Intersection of Behavioral Science, Adult Learning and Leadership

Science.gov (United States)

Sabga, Natalya I.

2017-01-01

This study examines if a relationship exists among three rich research streams, specifically the behavioral science of motivation, adult learning and leadership. What motivates adult professionals to continue learning and how is that connected to their style and efficacy as leaders? An extension of literature to connect Andragogy,…

Development and validation of the Simulation Learning Effectiveness Scale for nursing students.

Science.gov (United States)

Pai, Hsiang-Chu

2016-11-01

To develop and validate the Simulation Learning Effectiveness Scale, which is based on Bandura's social cognitive theory. A simulation programme is a significant teaching strategy for nursing students. Nevertheless, there are few evidence-based instruments that validate the effectiveness of simulation learning in Taiwan. This is a quantitative descriptive design. In Study 1, a nonprobability convenience sample of 151 student nurses completed the Simulation Learning Effectiveness Scale. Exploratory factor analysis was used to examine the factor structure of the instrument. In Study 2, which involved 365 student nurses, confirmatory factor analysis and structural equation modelling were used to analyse the construct validity of the Simulation Learning Effectiveness Scale. In Study 1, exploratory factor analysis yielded three components: self-regulation, self-efficacy and self-motivation. The three factors explained 29·09, 27·74 and 19·32% of the variance, respectively. The final 12-item instrument with the three factors explained 76·15% of variance. Cronbach's alpha was 0·94. In Study 2, confirmatory factor analysis identified a second-order factor termed Simulation Learning Effectiveness Scale. Goodness-of-fit indices showed an acceptable fit overall with the full model (χ 2 /df (51) = 3·54, comparative fit index = 0·96, Tucker-Lewis index = 0·95 and standardised root-mean-square residual = 0·035). In addition, teacher's competence was found to encourage learning, and self-reflection and insight were significantly and positively associated with Simulation Learning Effectiveness Scale. Teacher's competence in encouraging learning also was significantly and positively associated with self-reflection and insight. Overall, theses variable explained 21·9% of the variance in the student's learning effectiveness. The Simulation Learning Effectiveness Scale is a reliable and valid means to assess simulation learning effectiveness for nursing students

Beliefs and Behaviors in Learning Critical Thinking Skills

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Octavian REPOLSCHI

2015-12-01

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.

Perceived Coach Attitudes and Behaviors Scale: Development and Validation Study

Science.gov (United States)

Üzüm, Hanifi; Karli, Ünal; Yildiz, Nuh Osman

2018-01-01

The purpose of the study was to develop a scale, which will serve to determine how attitudes and behaviors of the coaches are perceived by the athletes. The scale, named as "Perceived Coach Attitudes and Behaviors Scale" (PCABS) was developed through various processes including exploratory and confirmatory factor analysis. Following the…

Student Nutrition, Learning and Behavior.

Science.gov (United States)

Royster, Martha

This discussion addresses several nutrition issues considered important to schools, students, and educators in the United States. Contents consist of a review of malnutrition and learning research and discussions of food additives and allergies, diet and hyperkinesia, the effects of caffeine and sugar on children's behavior, and the National…

Development and Validation of Children's Responsible Environmental Behavior Scale

Science.gov (United States)

Erdogan, Mehmet; Ok, Ahmet; Marcinkowski, Thomas Joseph

2012-01-01

Though environmentally responsible behavior (ERB) has been a focus of many studies in the field of environmental education, very few scales have been developed to assess children's ERB. In this regard, this article focuses on the development and validation of Children's Responsible Environmental Behavior Scale (CREBS) and also reports the…

Developing Scale for Assimilate the Integration between Learning Theories and E-learning.

Directory of Open Access Journals (Sweden)

George Maher Iskander

2014-03-01

Full Text Available As e-learning tend to get more and more significant for all kind of universities, researchers and consultants are becoming aware of the fact that a high technology approach and Blackboard do not guarantee successful teaching and learning. Thus, a move to pedagogy-based theories can be observed within the field of e-learning. This study describes the procedure of the development of an empirically-based psychometrically-sound instrument to measure instructional model for e-learning system at Middle East universities. In order to accelerate the acceptance of e-learning and implementation of institution-wide adoption of e-learning, it is important to understand students' perceptions with instructional model for e- learning. The 19-item scale developed shows a high probability of differentiating between positive and negative perceptions and the methods which can be used for embedding the traditional learning theories into e-learning.

Increasing character value and conservation behavior through integrated ethnoscience chemistry in chemistry learning: A Case Study in The Department of Science Universitas Negeri Semarang.

Science.gov (United States)

Sudarmin; Sumarni, Woro

2018-04-01

The purpose of this study was to obtain a factual picture of the improvement of students' conservation character and conservation behavior through the application integrated ethnoscience chemistry learning. This research was a case study on students majoring in the Department Of Science Mathematics and Natural Science Faculty Universitas Negeri Semarang. The subjects of the study were 30 students attending ethnoscience course in one of the teacher education institutions in the even semester of the academic year of 2016/2017. The subjects were given chemistry learning integrated into ethnoscience for eight weeks. The technique of data collection was done by using attitude scale arranged based on Likert scale. The data were analyzed by using qualitative descriptive. The results showed that the integrated ethnoscience chemistry learning contributed positively to the improvement of the character value and conservation behavior

Temporal scaling behavior of forest and urban fires

Science.gov (United States)

Wang, J.; Song, W.; Zheng, H.; Telesca, L.

2009-04-01

It has been found that many natural systems are characterized by scaling behavior. In such systems natural factors dominate the event dynamics. Forest fires in different countries have been found to exhibit frequency-size power law over many orders of magnitude and with similar value of parameters. But in countries with high population density such as China and Japan, more than 95% of the forest fire disasters are caused by human activities. Furthermore, with the development of society, the wildland-urban interface (WUI) area is becoming more and more populated, and the forest fire is much connected with urban fire. Therefore exploring the scaling behavior of fires dominated by human-related factors is very challenging. The present paper explores the temporal scaling behavior of forest fires and urban fires in Japan with mathematical methods. Two factors, Allan factor (AF) and Fano factor (FF) are used to investigate time-scaling of fire systems. It is found that the FF for both forest fires and urban fires increases linearly in log-log scales, and this indicates that it behaves as a power-law for all the investigated timescales. From the AF plot a 7 days cycle is found, which indicates a weekly cycle. This may be caused by human activities which has a weekly periodicity because on weekends people usually have more outdoor activities, which may cause more hidden trouble of fire disasters. Our findings point out that although the human factors are the main cause, both the forest fires and urban fires exhibit time-scaling behavior. At the same time, the scaling exponents for urban fires are larger than forest fires, signifying a more intense clustering. The reason may be that fires are affected not only by weather condition, but also by human activities, which play a more important role for urban fires than forest fires and have a power law distribution and scaling behavior. Then some work is done to the relative humidity. Similar distribution law characterizes the

Dysfunctional Consumer Behavior: Proposition of a Measurement Scale

Directory of Open Access Journals (Sweden)

Marília Lara Marcondes Machado de Oliveira

2015-01-01

Full Text Available This study focuses on the development of a scale that can identify customers that are more prone to behave in a dysfunctional manner. Dysfunctional Consumer Behavior can negatively influence the organization profits, since this kind of consumer can generate monetary losses, such as fixing damaged pr operty. Several hypotheses are proposed based on consumer characteristics that could foster dysfunctional behavior. For this, we used an hybrid methodology, combining Churchill’s (1979 with C - OAR - SE (2002. In order to develop the scale, scenarios with dy sfunctional behaviors where constructed. Respondents were asked to rate the appropriateness of each behavior and answers a group of questions based on the hypothesis developed. The data was collected over the Internet (Amazon Turk and the statistical meth ods used for the scale development were cluster and discriminant analysis. The results showed evidence that it is possible to distinguish consumers through a discriminant function using interpersonal influence, such as aggressiveness, self - exposure, moral flexibility and machiavellianism; and personality aspects, such as dissatisfaction and acceptance.

Value-Eroding Teacher Behaviors Scale: A Validity and Reliability Study

Science.gov (United States)

Arseven, Zeynep; Kiliç, Abdurrahman; Sahin, Seyma

2016-01-01

In the present study, it is aimed to develop a valid and reliable scale for determining value-eroding behaviors of teachers, hence their values of judgment. The items of the "Value-eroding Teacher Behaviors Scale" were designed in the form of 5-point likert type rating scale. The exploratory factor analysis (EFA) was conducted to…

An approach to children's smoking behavior using social cognitive learning theory.

Science.gov (United States)

Bektas, Murat; Ozturk, Candan; Armstrong, Merry

2010-01-01

This review article discusses the theoretical principles of social cognitive learning theory and children's risk-taking behavior of cigarette smoking, along with preventive initiatives. Social cognitive learning theorists examine the behavior of initiating and sustained smoking using a social systems approach. The authors discuss the reciprocal determinism aspect of the theory as applied to the importance of individual factors, and environment and behavioral interactions that influence smoking behavior. Included is the concept of vicarious capability that suggests that smoking behavior is determined in response to and interaction with feedback provided by the environment. The principle of self-regulatory capability asserts that people have control over their own behavior and thus that behavior change is possible. The principle of self-efficacy proposes that high level of self-efficacy of an individual may decrease the behavior of attempting to or continuing to smoke. Examples of initiatives to be undertaken in order to prevent smoking in accordance with social cognitive learning theory are presented at the end of each principle.

Two Programs Educating the Public in Animal Learning and Behavior

OpenAIRE

Estep, Daniel Q.

2002-01-01

Two educational programs have been developed that teach basic principles of animal learning and behavior and how they can be used in day to day interactions with companion animals. The first program educates violators of animal control laws about animal learning and cat and dog behavior to help them resolve their problems with their animals and avoid future animal control violations. The second educates home service providers concerning basic principles of animal communication, dog behavior, ...

Some chaotic behaviors in a MCA learning algorithm with a constant learning rate

International Nuclear Information System (INIS)

Lv Jiancheng; Yi Zhang

2007-01-01

Douglas's minor component analysis algorithm with a constant learning rate has both stability and chaotic dynamical behavior under some conditions. The paper explores such dynamical behavior of this algorithm. Certain stability and chaos of this algorithm are derived. Waveform plots, Lyapunov exponents and bifurcation diagrams are presented to illustrate the existence of chaotic behavior

Abnormal Gait Behavior Detection for Elderly Based on Enhanced Wigner-Ville Analysis and Cloud Incremental SVM Learning

Directory of Open Access Journals (Sweden)

Jian Luo

2016-01-01

Full Text Available A cloud based health care system is proposed in this paper for the elderly by providing abnormal gait behavior detection, classification, online diagnosis, and remote aid service. Intelligent mobile terminals with triaxial acceleration sensor embedded are used to capture the movement and ambulation information of elderly. The collected signals are first enhanced by a Kalman filter. And the magnitude of signal vector features is then extracted and decomposed into a linear combination of enhanced Gabor atoms. The Wigner-Ville analysis method is introduced and the problem is studied by joint time-frequency analysis. In order to solve the large-scale abnormal behavior data lacking problem in training process, a cloud based incremental SVM (CI-SVM learning method is proposed. The original abnormal behavior data are first used to get the initial SVM classifier. And the larger abnormal behavior data of elderly collected by mobile devices are then gathered in cloud platform to conduct incremental training and get the new SVM classifier. By the CI-SVM learning method, the knowledge of SVM classifier could be accumulated due to the dynamic incremental learning. Experimental results demonstrate that the proposed method is feasible and can be applied to aged care, emergency aid, and related fields.

Traditional Classroom vs E-learning in Higher Education: Difference between Students' Behavioral Engagement

Directory of Open Access Journals (Sweden)

Fei Li

2014-03-01

Full Text Available We discuss traditional classroom, e-learning, behavioral engagement and difference between behavioral engagements in two kind of instruction environment. Results from variance analyses suggest that there is no significant difference between engagements of active learning in different classroom conditions, and there exist significant differences on higher-level learning of innovative and critical thinking. Our findings highlight students' behavioral engagements in two environments have no significant advantage over each other, but e-learning facilitates higher-level learning better.

Place learning overrides innate behaviors in Drosophila.

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Baggett, Vincent; Mishra, Aditi; Kehrer, Abigail L; Robinson, Abbey O; Shaw, Paul; Zars, Troy

2018-03-01

Animals in a natural environment confront many sensory cues. Some of these cues bias behavioral decisions independent of experience, and action selection can reveal a stimulus-response (S-R) connection. However, in a changing environment it would be a benefit for an animal to update behavioral action selection based on experience, and learning might modify even strong S-R relationships. How animals use learning to modify S-R relationships is a largely open question. Three sensory stimuli, air, light, and gravity sources were presented to individual Drosophila melanogaster in both naïve and place conditioning situations. Flies were tested for a potential modification of the S-R relationships of anemotaxis, phototaxis, and negative gravitaxis by a contingency that associated place with high temperature. With two stimuli, significant S-R relationships were abandoned when the cue was in conflict with the place learning contingency. The role of the dunce ( dnc ) cAMP-phosphodiesterase and the rutabaga ( rut ) adenylyl cyclase were examined in all conditions. Both dnc 1 and rut 2080 mutant flies failed to display significant S-R relationships with two attractive cues, and have characteristically lower conditioning scores under most conditions. Thus, learning can have profound effects on separate native S-R relationships in multiple contexts, and mutation of the dnc and rut genes reveal complex effects on behavior. © 2018 Baggett et al.; Published by Cold Spring Harbor Laboratory Press.

Large-scale weakly supervised object localization via latent category learning.

Science.gov (United States)

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

Review: The Necessity of Producing/Normalizing Adaptive Behavior Scales in Diagnosing Training Treatment Rehabilitation of Peop e and Assessment of the Programs

OpenAIRE

Seyyed Jalal Sadrosadat; Leila Sadrosadat

2000-01-01

Adaptive behavior is defined as the manner in which people cope with the natural and social demands of their environments. Impairments in adaptive behavior are described as significant limitations in an individual's effectiveness in meeting the standards of maturation, learning, personal independence, and/or social responsibility that are expected for one's age level and cultural group, as determined by clinical assessment, and usually, standardized scales. The definitions of adaptive deficie...

The Validation of the Active Learning in Health Professions Scale

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Kammer, Rebecca; Schreiner, Laurie; Kim, Young K.; Denial, Aurora

2015-01-01

There is a need for an assessment tool for evaluating the effectiveness of active learning strategies such as problem-based learning in promoting deep learning and clinical reasoning skills within the dual environments of didactic and clinical settings in health professions education. The Active Learning in Health Professions Scale (ALPHS)…

Implementation of the Agitated Behavior Scale in the Electronic Health Record.

Science.gov (United States)

Wilson, Helen John; Dasgupta, Kritis; Michael, Kathleen

The purpose of the study was to implement an Agitated Behavior Scale through an electronic health record and to evaluate the usability of the scale in a brain injury unit at a rehabilitation hospital. A quality improvement project was conducted in the brain injury unit at a large rehabilitation hospital with registered nurses as participants using convenience sampling. The project consisted of three phases and included education, implementation of the scale in the electronic health record, and administration of the survey questionnaire, which utilized the system usability scale. The Agitated Behavior Scale was found to be usable, and there was 92.2% compliance with the use of the electronic Electronic Agitated Behavior Scale. The Agitated Behavior Scale was effectively implemented in the electronic health record and was found to be usable in the assessment of agitation. Utilization of the scale through the electronic health record on a daily basis will allow for an early identification of agitation in patients with traumatic brain injury and enable prompt interventions to manage agitation.

Large-Scale Machine Learning for Classification and Search

Science.gov (United States)

Liu, Wei

2012-01-01

With the rapid development of the Internet, nowadays tremendous amounts of data including images and videos, up to millions or billions, can be collected for training machine learning models. Inspired by this trend, this thesis is dedicated to developing large-scale machine learning techniques for the purpose of making classification and nearest…

Amygdala subsystems and control of feeding behavior by learned cues.

Science.gov (United States)

Petrovich, Gorica D; Gallagher, Michela

2003-04-01

A combination of behavioral studies and a neural systems analysis approach has proven fruitful in defining the role of the amygdala complex and associated circuits in fear conditioning. The evidence presented in this chapter suggests that this approach is also informative in the study of other adaptive functions that involve the amygdala. In this chapter we present a novel model to study learning in an appetitive context. Furthermore, we demonstrate that long-recognized connections between the amygdala and the hypothalamus play a crucial role in allowing learning to modulate feeding behavior. In the first part we describe a behavioral model for motivational learning. In this model a cue that acquires motivational properties through pairings with food delivery when an animal is hungry can override satiety and promote eating in sated rats. Next, we present evidence that a specific amygdala subsystem (basolateral area) is responsible for allowing such learned cues to control eating (override satiety and promote eating in sated rats). We also show that basolateral amygdala mediates these actions via connectivity with the lateral hypothalamus. Lastly, we present evidence that the amygdalohypothalamic system is specific for the control of eating by learned motivational cues, as it does not mediate another function that depends on intact basolateral amygdala, namely, the ability of a conditioned cue to support new learning based on its acquired value. Knowledge about neural systems through which food-associated cues specifically control feeding behavior provides a defined model for the study of learning. In addition, this model may be informative for understanding mechanisms of maladaptive aspects of learned control of eating that contribute to eating disorders and more moderate forms of overeating.

An augmented Lagrangian multi-scale dictionary learning algorithm

Directory of Open Access Journals (Sweden)

Ye Meng

2011-01-01

Full Text Available Abstract Learning overcomplete dictionaries for sparse signal representation has become a hot topic fascinated by many researchers in the recent years, while most of the existing approaches have a serious problem that they always lead to local minima. In this article, we present a novel augmented Lagrangian multi-scale dictionary learning algorithm (ALM-DL, which is achieved by first recasting the constrained dictionary learning problem into an AL scheme, and then updating the dictionary after each inner iteration of the scheme during which majorization-minimization technique is employed for solving the inner subproblem. Refining the dictionary from low scale to high makes the proposed method less dependent on the initial dictionary hence avoiding local optima. Numerical tests for synthetic data and denoising applications on real images demonstrate the superior performance of the proposed approach.

Learner Behaviors and Perceptions of Autonomous Language Learning

Science.gov (United States)

Bekleyen, Nilüfer; Selimoglu, Figen

2016-01-01

The purpose of the present study was to investigate the learners' behaviors and perceptions about autonomous language learning at the university level in Turkey. It attempts to reveal what type of perceptions learners held regarding teachers' and their own responsibilities in the language learning process. Their autonomous language learning…

Development of the Self-Directed Learning Skills Scale

Science.gov (United States)

Ayyildiz, Yildizay; Tarhan, Leman

2015-01-01

The purpose of this study was to develop a valid and reliable scale for assessing high school students' self-directed learning skills. Based on a literature review and data obtained from similar instruments, all skills related to self-directed learning were identified. Next, an item pool was prepared and administered to 255 students from various…

Instructional control of reinforcement learning: A behavioral and neurocomputational investigation

NARCIS (Netherlands)

Doll, B.B.; Jacobs, W.J.; Sanfey, A.G.; Frank, M.J.

2009-01-01

Humans learn how to behave directly through environmental experience and indirectly through rules and instructions. Behavior analytic research has shown that instructions can control behavior, even when such behavior leads to sub-optimal outcomes (Hayes, S (Ed) 1989. Rule-governed behavior:

Exercising during learning improves vocabulary acquisition: behavioral and ERP evidence.

Science.gov (United States)

Schmidt-Kassow, Maren; Kulka, Anna; Gunter, Thomas C; Rothermich, Kathrin; Kotz, Sonja A

2010-09-20

Numerous studies have provided evidence that physical activity promotes cortical plasticity in the adult brain and in turn facilitates learning. However, until now, the effect of simultaneous physical activity (e.g. bicycling) on learning performance has not been investigated systematically. The current study aims at clarifying whether simultaneous motor activity influences verbal learning compared to learning in a physically passive situation. Therefore the learning behavior of 12 healthy subjects (4 male, 19-33 years) was monitored over a period of 3 weeks. During that time, behavioral and electrophysiological responses to memorized materials were measured. We found a larger N400 effect and better performance in vocabulary tests when subjects were physically active during the encoding phase. Thus, our data indicate that simultaneous physical activity during vocabulary learning facilitates memorization of new items. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior

Science.gov (United States)

2006-09-28

navigate in an unstructured environment to a specific target or location. 15. SUBJECT TERMS autonomous vehicles , fuzzy logic, learning behavior...ANSI-Std Z39-18 Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior FINAL REPORT 9/28/2006 Dean B. Edwards Department...the future, as greater numbers of autonomous vehicles are employed, it is hoped that lower LONG-TERM GOALS Use LAGR (Learning Applied to Ground Robots

Civic Engagement Scale

Directory of Open Access Journals (Sweden)

Amy Doolittle

2013-07-01

Full Text Available This study reports on the development and validation of the Civic Engagement Scale (CES. This scale is developed to be easily administered and useful to educators who are seeking to measure the attitudes and behaviors that have been affected by a service-learning experience. This instrument was administered as a validation study in a purposive sample of social work and education majors at three universities (N = 513 with a return of 354 (69%. After the reliability and validity analysis was completed, the Attitude subscale was left with eight items and a Cronbach’s alpha level of .91. The Behavior subscale was left with six items and a Cronbach’s alpha level of .85. Principal component analysis indicated a two-dimensional scale with high loadings on both factors (mean factor loading for the attitude factor = .79, and mean factor loading for the behavior factor = .77. These results indicate that the CES is strong enough to recommend its use in educational settings. Preliminary use has demonstrated that this scale will be useful to researchers seeking to better understand the relationship of attitudes and behaviors with civic engagement in the service-learning setting. The primary limitations of this research are that the sample was limited to social work and education majors who were primarily White (n = 312, 88.1% and female (n = 294, 83.1%. Therefore, further research would be needed to generalize this research to other populations.

Development of a Behaviorally Anchored Rating Scale for Leadership

Science.gov (United States)

2018-01-01

Research Product 2018-06 Development of a Behaviorally Anchored Rating Scale for Leadership Tatiana H. Toumbeva Krista L...anchored Rating Scale for Leadership 5a. CONTRACT NUMBER W5J9CQ-11-D-0004 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62278 6...observer- based behavioral measure to help instructors more reliably and accurately evaluate the development of leadership attributes and competencies

Differentiating children with attention-deficit/hyperactivity disorder, conduct disorder, learning disabilities and autistic spectrum disorders by means of their motor behavior characteristics.

Science.gov (United States)

Efstratopoulou, Maria; Janssen, Rianne; Simons, Johan

2012-01-01

The study was designed to investigate the discriminant validity of the Motor Behavior Checklist (MBC) for distinguishing four group of children independently classified with Attention-Deficit/Hyperactivity Disorder, (ADHD; N=22), Conduct Disorder (CD; N=17), Learning Disabilities (LD; N=24) and Autistic Spectrum Disorders (ASD; N=20). Physical education teachers used the MBC for children to rate their pupils based on their motor related behaviors. A multivariate analysis revealed significant differences among the groups on different problem scales. The results indicated that the MBC for children may be effective in discriminating children with similar disruptive behaviors (e.g., ADHD, CD) and autistic disorders, based on their motor behavior characteristics, but not children with Learning Disabilities (LD), when used by physical education teachers in school settings. Copyright © 2011 Elsevier Ltd. All rights reserved.

Disruptive behavior scale for adolescents (DISBA): development and psychometric properties.

Science.gov (United States)

Karimy, Mahmood; Fakhri, Ahmad; Vali, Esmaeel; Vali, Farzaneh; Veiga, Feliciano H; Stein, L A R; Araban, Marzieh

2018-01-01

Growing evidence indicates that if disruptive behavior is left unidentified and untreated, a significant proportion of these problems will persist and may develop into problems linked with delinquency, substance abuse, and violence. Research is needed to develop valid and reliable measures of disruptive behavior to assist recognition and impact of treatments on disruptive behavior. The aim of this study was to develop and evaluate the psychometric properties of a scale for disruptive behavior in adolescents. Six hundred high school students (50% girls), ages ranged 15-18 years old, selected through multi stage random sampling. Psychometrics of the disruptive behavior scale for adolescents (DISBA) (Persian version) was assessed through content validity, explanatory factor analysis (EFA) using Varimax rotation and confirmatory factor analysis (CFA). The reliability of this scale was assessed via internal consistency and test-retest reliability. EFA revealed four factors accounting for 59% of observed variance. The final 29-item scale contained four factors: (1) aggressive school behavior, (2) classroom defiant behavior, (3) unimportance of school, and (4) defiance to school authorities. Furthermore, CFA produced a sufficient Goodness of Fit Index > 0.90. Test-retest and internal consistency reliabilities were acceptable at 0.85 and 0.89, respectively. The findings from this study suggest that the Iranian version of DISBA questionnaire has content validity. Further studies are needed to evaluate stronger psychometric properties for DISBA.

Fast social-like learning of complex behaviors based on motor motifs

Science.gov (United States)

Calvo Tapia, Carlos; Tyukin, Ivan Y.; Makarov, Valeri A.

2018-05-01

Social learning is widely observed in many species. Less experienced agents copy successful behaviors exhibited by more experienced individuals. Nevertheless, the dynamical mechanisms behind this process remain largely unknown. Here we assume that a complex behavior can be decomposed into a sequence of n motor motifs. Then a neural network capable of activating motor motifs in a given sequence can drive an agent. To account for (n -1 )! possible sequences of motifs in a neural network, we employ the winnerless competition approach. We then consider a teacher-learner situation: one agent exhibits a complex movement, while another one aims at mimicking the teacher's behavior. Despite the huge variety of possible motif sequences we show that the learner, equipped with the provided learning model, can rewire "on the fly" its synaptic couplings in no more than (n -1 ) learning cycles and converge exponentially to the durations of the teacher's motifs. We validate the learning model on mobile robots. Experimental results show that the learner is indeed capable of copying the teacher's behavior composed of six motor motifs in a few learning cycles. The reported mechanism of learning is general and can be used for replicating different functions, including, for example, sound patterns or speech.

A phenomenological memristor model for synaptic memory and learning behaviors

Institute of Scientific and Technical Information of China (English)

Nan Shao; Sheng-Bing Zhang; Shu-Yuan Shao

2017-01-01

Properties that are similar to the memory and learning functions in biological systems have been observed and reported in the experimental studies of memristors fabricated by different materials.These properties include the forgetting effect,the transition from short-term memory (STM) to long-term memory (LTM),learning-experience behavior,etc.The mathematical model of this kind of memristor would be very important for its theoretical analysis and application design.In our analysis of the existing memristor model with these properties,we find that some behaviors of the model are inconsistent with the reported experimental observations.A phenomenological memristor model is proposed for this kind of memristor.The model design is based on the forgetting effect and STM-to-LTM transition since these behaviors are two typical properties of these memristors.Further analyses of this model show that this model can also be used directly or modified to describe other experimentally observed behaviors.Simulations show that the proposed model can give a better description of the reported memory and learning behaviors of this kind of memristor than the existing model.

Human learning: Power laws or multiple characteristic time scales?

Directory of Open Access Journals (Sweden)

Gottfried Mayer-Kress

2006-09-01

Full Text Available The central proposal of A. Newell and Rosenbloom (1981 was that the power law is the ubiquitous law of learning. This proposition is discussed in the context of the key factors that led to the acceptance of the power law as the function of learning. We then outline the principles of an epigenetic landscape framework for considering the role of the characteristic time scales of learning and an approach to system identification of the processes of performance dynamics. In this view, the change of performance over time is the product of a superposition of characteristic exponential time scales that reflect the influence of different processes. This theoretical approach can reproduce the traditional power law of practice – within the experimental resolution of performance data sets - but we hypothesize that this function may prove to be a special and perhaps idealized case of learning.

Less is more: regularization perspectives on large scale machine learning

CERN Multimedia

CERN. Geneva

2017-01-01

Deep learning based techniques provide a possible solution at the expanse of theoretical guidance and, especially, of computational requirements. It is then a key challenge for large scale machine learning to devise approaches guaranteed to be accurate and yet computationally efficient. In this talk, we will consider a regularization perspectives on machine learning appealing to classical ideas in linear algebra and inverse problems to scale-up dramatically nonparametric methods such as kernel methods, often dismissed because of prohibitive costs. Our analysis derives optimal theoretical guarantees while providing experimental results at par or out-performing state of the art approaches.

Enhancing students' learning in problem based learning: validation of a self-assessment scale for active learning and critical thinking.

Science.gov (United States)

Khoiriyah, Umatul; Roberts, Chris; Jorm, Christine; Van der Vleuten, C P M

2015-08-26

Problem based learning (PBL) is a powerful learning activity but fidelity to intended models may slip and student engagement wane, negatively impacting learning processes, and outcomes. One potential solution to solve this degradation is by encouraging self-assessment in the PBL tutorial. Self-assessment is a central component of the self-regulation of student learning behaviours. There are few measures to investigate self-assessment relevant to PBL processes. We developed a Self-assessment Scale on Active Learning and Critical Thinking (SSACT) to address this gap. We wished to demonstrated evidence of its validity in the context of PBL by exploring its internal structure. We used a mixed methods approach to scale development. We developed scale items from a qualitative investigation, literature review, and consideration of previous existing tools used for study of the PBL process. Expert review panels evaluated its content; a process of validation subsequently reduced the pool of items. We used structural equation modelling to undertake a confirmatory factor analysis (CFA) of the SSACT and coefficient alpha. The 14 item SSACT consisted of two domains "active learning" and "critical thinking." The factorial validity of SSACT was evidenced by all items loading significantly on their expected factors, a good model fit for the data, and good stability across two independent samples. Each subscale had good internal reliability (>0.8) and strongly correlated with each other. The SSACT has sufficient evidence of its validity to support its use in the PBL process to encourage students to self-assess. The implementation of the SSACT may assist students to improve the quality of their learning in achieving PBL goals such as critical thinking and self-directed learning.

Development and examination of the psychometric properties of the Learning Experience Scale in nursing.

Science.gov (United States)

Takase, Miyuki; Imai, Takiko; Uemura, Chizuru

2016-06-01

This paper examines the psychometric properties of the Learning Experience Scale. A survey method was used to collect data from a total of 502 nurses. Data were analyzed by factor analysis and the known-groups technique to examine the construct validity of the scale. In addition, internal consistency was evaluated by Cronbach's alpha, and stability was examined by test-retest correlation. Factor analysis showed that the Learning Experience Scale consisted of five factors: learning from practice, others, training, feedback, and reflection. The scale also had the power to discriminate between nurses with high and low levels of nursing competence. The internal consistency and the stability of the scale were also acceptable. The Learning Experience Scale is a valid and reliable instrument, and helps organizations to effectively design learning interventions for nurses. © 2015 Wiley Publishing Asia Pty Ltd.

Personalized learning: From neurogenetics of behaviors to designing optimal language training.

Science.gov (United States)

Wong, Patrick C M; Vuong, Loan C; Liu, Kevin

2017-04-01

Variability in drug responsivity has prompted the development of Personalized Medicine, which has shown great promise in utilizing genotypic information to develop safer and more effective drug regimens for patients. Similarly, individual variability in learning outcomes has puzzled researchers who seek to create optimal learning environments for students. "Personalized Learning" seeks to identify genetic, neural and behavioral predictors of individual differences in learning and aims to use predictors to help create optimal teaching paradigms. Evidence for Personalized Learning can be observed by connecting research in pharmacogenomics, cognitive genetics and behavioral experiments across domains of learning, which provides a framework for conducting empirical studies from the laboratory to the classroom and holds promise for addressing learning effectiveness in the individual learners. Evidence can also be seen in the subdomain of speech learning, thus providing initial support for the applicability of Personalized Learning to language. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptation and learning: characteristic time scales of performance dynamics.

Science.gov (United States)

Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

2009-12-01

A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

A SCALE-UP Mock-Up: Comparison of Student Learning Gains in High- and Low-Tech Active-Learning Environments

Science.gov (United States)

Soneral, Paula A. G.; Wyse, Sara A.

2017-01-01

Student-centered learning environments with upside-down pedagogies (SCALE-UP) are widely implemented at institutions across the country, and learning gains from these classrooms have been well documented. This study investigates the specific design feature(s) of the SCALE-UP classroom most conducive to teaching and learning. Using pilot survey data from instructors and students to prioritize the most salient SCALE-UP classroom features, we created a low-tech “Mock-up” version of this classroom and tested the impact of these features on student learning, attitudes, and satisfaction using a quasi-­experimental setup. The same instructor taught two sections of an introductory biology course in the SCALE-UP and Mock-up rooms. Although students in both sections were equivalent in terms of gender, grade point average, incoming ACT, and drop/fail/withdraw rate, the Mock-up classroom enrolled significantly more freshmen. Controlling for class standing, multiple regression modeling revealed no significant differences in exam, in-class, preclass, and Introduction to Molecular and Cellular Biology Concept Inventory scores between the SCALE-UP and Mock-up classrooms. Thematic analysis of student comments highlighted that collaboration and whiteboards enhanced the learning experience, but technology was not important. Student satisfaction and attitudes were comparable. These results suggest that the benefits of a SCALE-UP experience can be achieved at lower cost without technology features. PMID:28213582

Development and Examination of Personal and Social Responsibility Behaviors Scale

OpenAIRE

Bijen FİLİZ; Gıyasettin DEMİRHAN

2018-01-01

In this study, “Personal and Social Responsibility Behaviors Scale (PSRB-S)” was developed in order to determine students’ responsibility behaviors in accordance with “Personal and Social Responsibility” model developed by Don Hellison and students’ personal and social responsibility levels were examined in terms of gender, age and years of sport practice through this scale. Pertaining to personal and social dimension of responsibility, four-category Likert type trial scale consisting of 52 i...

Selective visual scaling of time-scale processes facilitates broadband learning of isometric force frequency tracking.

Science.gov (United States)

King, Adam C; Newell, Karl M

2015-10-01

The experiment investigated the effect of selectively augmenting faster time scales of visual feedback information on the learning and transfer of continuous isometric force tracking tasks to test the generality of the self-organization of 1/f properties of force output. Three experimental groups tracked an irregular target pattern either under a standard fixed gain condition or with selectively enhancement in the visual feedback display of intermediate (4-8 Hz) or high (8-12 Hz) frequency components of the force output. All groups reduced tracking error over practice, with the error lowest in the intermediate scaling condition followed by the high scaling and fixed gain conditions, respectively. Selective visual scaling induced persistent changes across the frequency spectrum, with the strongest effect in the intermediate scaling condition and positive transfer to novel feedback displays. The findings reveal an interdependence of the timescales in the learning and transfer of isometric force output frequency structures consistent with 1/f process models of the time scales of motor output variability.

Developing a "Social Presence Scale" for E-Learning Environments

Science.gov (United States)

Kilic Cakmak, Ebru; Cebi, Ayça; Kan, Adnan

2014-01-01

The purpose of the current study is to develop a "social presence scale" for e-learning environments. A systematic approach was followed for developing the scale. The scale was applied to 461 students registered in seven different programs at Gazi University. The sample was split into two subsamples on a random basis (n1 = 261; n2 =…

Yolk hormones influence in ovo chemosensory learning, growth, and feeding behavior in domestic chicks.

Science.gov (United States)

Bertin, Aline; Meurisse, Maryse; Arnould, Cécile; Leterrier, Christine; Constantin, Paul; Cornilleau, Fabien; Vaudin, Pascal; Burlot, Thierry; Delaveau, Joel; Rat, Christophe; Calandreau, Ludovic

2016-03-01

In this study, we assessed whether prenatal exposure to elevated yolk steroid hormones can influence in ovo chemosensory learning and the behavior of domestic chicks. We simulated a maternal environmental challenge by experimentally enhancing yolk progesterone, testosterone, and estradiol concentrations in hen eggs prior to incubation. The embryos from these hormones-treated eggs (HO) as well as sham embryos (O) that had received the vehicle-only were exposed to the odor of fish oil (menhaden) between embryonic Days 11 and 20. An additional group of control embryos (C) was not exposed to the odor. All chicks were tested following hatching for their feeding preferences between foods that were or were not odorized with the menhaden odor. In the 3-min choice tests, the behavior of O chicks differed significantly according to the type of food whereas C and HO chicks showed no preference between odorized and non-odorized food. Our result suggests weaker response in HO chicks. In addition, HO chicks showed impaired growth and reduced intake of an unfamiliar food on the 24-h time scale compared to controls. Our data suggest that embryonic exposure to increased yolk hormone levels can alter growth, chemosensory learning, and the development of feeding behaviors. © 2015 Wiley Periodicals, Inc.

Personalized Learning: From Neurogenetics of Behaviors to Designing Optimal Language Training

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Wong, Patrick C. M.; Vuong, Loan; Liu, Kevin

2016-01-01

Variability in drug responsivity has prompted the development of Personalized Medicine, which has shown great promise in utilizing genotypic information to develop safer and more effective drug regimens for patients. Similarly, individual variability in learning outcomes has puzzled researchers who seek to create optimal learning environments for students. “Personalized Learning” seeks to identify genetic, neural and behavioral predictors of individual differences in learning and aims to use predictors to help create optimal teaching paradigms. Evidence for Personalized Learning can be observed by connecting research in pharmacogenomics, cognitive genetics and behavioral experiments across domains of learning, which provides a framework for conducting empirical studies from the laboratory to the classroom and holds promise for addressing learning effectiveness in the individual learners. Evidence can also be seen in the subdomain of speech learning, thus providing initial support for the applicability of Personalized Learning to language. PMID:27720749

CACNA1C gene regulates behavioral strategies in operant rule learning.

Science.gov (United States)

Koppe, Georgia; Mallien, Anne Stephanie; Berger, Stefan; Bartsch, Dusan; Gass, Peter; Vollmayr, Barbara; Durstewitz, Daniel

2017-06-01

Behavioral experiments are usually designed to tap into a specific cognitive function, but animals may solve a given task through a variety of different and individual behavioral strategies, some of them not foreseen by the experimenter. Animal learning may therefore be seen more as the process of selecting among, and adapting, potential behavioral policies, rather than mere strengthening of associative links. Calcium influx through high-voltage-gated Ca2+ channels is central to synaptic plasticity, and altered expression of Cav1.2 channels and the CACNA1C gene have been associated with severe learning deficits and psychiatric disorders. Given this, we were interested in how specifically a selective functional ablation of the Cacna1c gene would modulate the learning process. Using a detailed, individual-level analysis of learning on an operant cue discrimination task in terms of behavioral strategies, combined with Bayesian selection among computational models estimated from the empirical data, we show that a Cacna1c knockout does not impair learning in general but has a much more specific effect: the majority of Cacna1c knockout mice still managed to increase reward feedback across trials but did so by adapting an outcome-based strategy, while the majority of matched controls adopted the experimentally intended cue-association rule. Our results thus point to a quite specific role of a single gene in learning and highlight that much more mechanistic insight could be gained by examining response patterns in terms of a larger repertoire of potential behavioral strategies. The results may also have clinical implications for treating psychiatric disorders.

A scale of lifelong learning attitudes of teachers: The development of LLLAS

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Cigdem Hursen

2016-03-01

Full Text Available Knowledge, which is the most significant characteristic of today’s knowledge society, has been changing and improving very rapidly. Particularly, the developments in science and technology have been influencing social, economical and cultural life; thus professions and descriptions of professions have been continuously renewed. In addition, the needed profile of man power relevant to the changing professions has been changing continuously and the learnt knowledge has not been prevalent. For this reason, there is a need for the individuals to update their knowledge and skills continuously in order to adopt themselves to the technological changes and new work conditions. Lifelong learning approach can provide societies and individuals with opportunities to catch up with these changes and developments. In raising individuals as lifelong learners, teachers play a big role. In order to establish lifelong learning societies, first of all teachers should have all the characteristics of lifelong learning. This is why it is extremely important to determine what the attitudes of the teachers are towards lifelong learning approach. However, there has not been developed any scale measuring teachers’ attitudes towards lifelong learning approach so far. Therefore, in this current study, it is aimed to develop a scale to determine what the attitudes of the teachers are towards lifelong learning approach. The subject group is consisted of 300 teachers, working in the schools of the Northern Cyprus. The findings on the validity of the structure of the scale are measured by the factor analysis. As a result of the analysis, a lifelong learning attitude scale is developed with 19 items in three sub-dimensions (LLLAS. The sub-dimensions of the scale are formed in the following expressions: “reluctance to learn”, “belief in the benefits of learning activities for professional development”, “awareness of personal learning skills”. As the result of the

The antecedents of e-learning outcome: an examination of system quality, technology readiness, and learning behavior.

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Ho, Li-An

2009-01-01

The rapid advancement of Internet and computer technology has not only influenced the way we live, but also the way we learn. Due to the implementation of e-learning in urban junior high schools in Taiwan, it has become essential to find out how external and internal factors affect junior high school students' online learning behavior, which consequently affects their learning outcome. The present study aims to propose a conceptual structural equation model to investigate the relationships among e-Learning system quality (eLSQ), technology readiness (TR), learning behavior (LB), and learning outcome (LO), and to demonstrate the direct and indirect effect of eLSQ and TR on LO from the perspectives of LB. Data collected from 10 urban junior high schools in Taiwan (N = 376) were analyzed using structural equation modeling. Results reveal that both eLSQ and TR have a direct and significant impact on LB. However, eLSQ and TR influence LO indirectly through LB. In addition, LB has a direct and positive significant influence on LO. Managerial implications are proposed and research limitations are discussed.

Newton Methods for Large Scale Problems in Machine Learning

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Hansen, Samantha Leigh

2014-01-01

The focus of this thesis is on practical ways of designing optimization algorithms for minimizing large-scale nonlinear functions with applications in machine learning. Chapter 1 introduces the overarching ideas in the thesis. Chapters 2 and 3 are geared towards supervised machine learning applications that involve minimizing a sum of loss…

Early adversity and learning: implications for typical and atypical behavioral development.

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Hanson, Jamie L; van den Bos, Wouter; Roeber, Barbara J; Rudolph, Karen D; Davidson, Richard J; Pollak, Seth D

2017-07-01

Children who experience early adversity often develop emotion regulatory problems, but little is known about the mechanisms that mediate this relation. We tested whether general associative learning processes contribute to associations between adversity, in the form of child maltreatment, and negative behavioral outcomes. Eighty-one participants between 12 and 17 years of age were recruited for this study and completed a probabilistic learning Task. Forty-one of these participants had been exposed to physical abuse, a form of early adversity. Forty additional participants without any known history of maltreatment served as a comparison group. All participants (and their parents) also completed portions of the Youth Life Stress Interview to understand adolescent's behavior. We calculated measures of associative learning, and also constructed mathematical models of learning. We found that adolescents exposed to high levels of adversity early in their lives had lower levels of associative learning than comparison adolescents. In addition, we found that impaired associative learning partially explained the higher levels of behavioral problems among youth who suffered early adversity. Using mathematical models, we also found that two components of learning were specifically affected in children exposed to adversity: choice variability and biases in their beliefs about the likelihood of rewards in the environment. Participants who had been exposed to early adversity were less able than their peers to correctly learn which stimuli were likely to result in reward, even after repeated feedback. These individuals also used information about known rewards in their environments less often. In addition, individuals exposed to adversity made decisions early in the learning process as if rewards were less consistent and occurred more at random. These data suggest one mechanism through which early life experience shapes behavioral development. © 2017 Association for Child and

Classification and Validation of Behavioral Subtypes of Learning-Disabled Children.

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Speece, Deborah L.; And Others

1985-01-01

Using the Classroom Behavior Inventory, teachers rated the behaviors of 63 school-identified, learning-disabled first and second graders. Hierarchical cluster analysis techniques identified seven distinct behavioral subtypes. Internal validation techniques indicated that the subtypes were replicable and had profile patterns different from a sample…

A learning-style theory for understanding autistic behaviors

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Ning eQian

2011-08-01

Full Text Available Understanding autism’s ever-expanding array of behaviors, from sensation to cognition, is a major challenge. We posit that autistic and typically-developing brains implement different algorithms that are better suited to learn, represent, and process different tasks; consequently, they develop different interests and behaviors. Computationally, a continuum of algorithms exists, from lookup-table (LUT learning, which aims to store experiences precisely, to interpolation (INT learning, which focuses on extracting underlying statistical structure (regularities from experiences. We hypothesize that autistic and typical brains, respectively, are biased toward LUT and INT learning, in low and high dimensional feature spaces, possibly because of their narrow and broad tuning functions. The LUT style is good at learning relationships that are local, precise, rigid, and contain little regularity for generalization (e.g., the name-number association in a phonebook. However, it is poor at learning relationships that are context dependent, noisy, flexible, and do contain regularities for generalization (e.g., associations between gaze direction and intention, language and meaning, sensory input and interpretation, motor-control signal and movement, and social situation and proper response. The LUT style poorly compresses information, resulting in inefficiency, sensory overload (overwhelm, restricted interests, and resistance to change. It also leads to poor prediction and anticipation, frequent surprises and over-reaction (hyper-sensitivity, impaired attentional selection and switching, concreteness, strong local focus, weak adaptation, and superior and inferior performances on simple and complex tasks. The spectrum nature of autism can be explained by different degrees of LUT learning among different individuals, and in different systems of the same individual. Our theory suggests that therapy should focus on training autistic LUT algorithm to learn

A Learning-Style Theory for Understanding Autistic Behaviors

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Qian, Ning; Lipkin, Richard M.

2011-01-01

Understanding autism's ever-expanding array of behaviors, from sensation to cognition, is a major challenge. We posit that autistic and typically developing brains implement different algorithms that are better suited to learn, represent, and process different tasks; consequently, they develop different interests and behaviors. Computationally, a continuum of algorithms exists, from lookup table (LUT) learning, which aims to store experiences precisely, to interpolation (INT) learning, which focuses on extracting underlying statistical structure (regularities) from experiences. We hypothesize that autistic and typical brains, respectively, are biased toward LUT and INT learning, in low- and high-dimensional feature spaces, possibly because of their narrow and broad tuning functions. The LUT style is good at learning relationships that are local, precise, rigid, and contain little regularity for generalization (e.g., the name–number association in a phonebook). However, it is poor at learning relationships that are context dependent, noisy, flexible, and do contain regularities for generalization (e.g., associations between gaze direction and intention, language and meaning, sensory input and interpretation, motor-control signal and movement, and social situation and proper response). The LUT style poorly compresses information, resulting in inefficiency, sensory overload (overwhelm), restricted interests, and resistance to change. It also leads to poor prediction and anticipation, frequent surprises and over-reaction (hyper-sensitivity), impaired attentional selection and switching, concreteness, strong local focus, weak adaptation, and superior and inferior performances on simple and complex tasks. The spectrum nature of autism can be explained by different degrees of LUT learning among different individuals, and in different systems of the same individual. Our theory suggests that therapy should focus on training autistic LUT algorithm to learn regularities

An interactive approach for new careers: The role of learning opportunities and learning behavior

OpenAIRE

van der Sluis, E.C.; Peiperl, M.A.

2000-01-01

This study examined the learning process at work from an individual perspective. Different kinds of learning opportunities and learning behavior were examined as (a) predictors of career development and (b) moderators of the development process on the job. Survey data from early-career MBAs were analyzed by performing hierarchical regressions and difference-of-means tests. Results indicated that the total amount of developmental job opportunities has a positive influence on individual percept...

Science curiosity in learning environments: developing an attitudinal scale for research in schools, homes, museums, and the community

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Weible, Jennifer L.; Toomey Zimmerman, Heather

2016-05-01

Although curiosity is considered an integral aspect of science learning, researchers have debated how to define, measure, and support its development in individuals. Prior measures of curiosity include questionnaire type scales (primarily for adults) and behavioral measures. To address the need to measure scientific curiosity, the Science Curiosity in Learning Environments (SCILE) scale was created and validated as a 12-item scale to measure scientific curiosity in youth. The scale was developed through (a) adapting the language of the Curiosity and Exploration Inventory-II [Kashdan, T. B., Gallagher, M. W., Silvia, P. J., Winterstein, B. P., Breen, W. E., Terhar, D., & Steger, M. F. (2009). The curiosity and exploration inventory-II: Development, factor structure, and psychometrics. Journal of Research in Personality, 43(6), 987-998] for youth and (b) crafting new items based on scientific practices drawn from U.S. science standards documents. We administered a preliminary set of 30 items to 663 youth ages 8-18 in the U.S.A. Exploratory and confirmatory factor analysis resulted in a three-factor model: stretching, embracing, and science practices. The findings indicate that the SCILE scale is a valid measure of youth's scientific curiosity for boys and girls as well as elementary, middle school, and high school learners.

Validation of the bipolar disorder etiology scale based on psychological behaviorism theory and factors related to the onset of bipolar disorder.

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Park, Jae Woo; Park, Kee Hwan

2014-01-01

The aim of this study was to identify psychosocial factors related to the onset of bipolar I disorder (BD). To do so, the Bipolar Disorder Etiology Scale (BDES), based on psychological behaviorism, was developed and validated. Using the BDES, common factors related to both major depressive disorder (MDD) and BD and specific factors related only to BD were investigated. The BDES, which measures 17 factors based on psychological behaviorism hypotheses, was developed and validated. This scale was administered to 113 non-clinical control subjects, 30 subjects with MDD, and 32 people with BD. ANOVA and post hoc analyses were conducted. Subscales on which MDD and BD groups scored higher than controls were classified as common factors, while those on which the BD group scored higher than MDD and control groups were classified as specific factors. The BDES has acceptable reliability and validity. Twelve common factors influence both MDD and BD and one specific factor influences only BD. Common factors include the following: learning grandiose self-labeling, learning dangerous behavior, reinforcing impulsive behavior, exposure to irritability, punishment of negative emotional expression, lack of support, sleep problems, antidepressant problems, positive arousal to threat, lack of social skills, and pursuit of short-term pleasure. The specific factor is manic emotional response. Manic emotional response was identified as a specific factor related to the onset of BD, while parents' grandiose labeling is a candidate for a specific factor. Many factors are related to the onset of both MDD and BD.

Extended child and caregiver benefits of behavior-based child contingency learning games.

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Dunst, Carl J; Raab, Melinda; Trivette, Carol M; Wilson, Linda L; Hamby, Deborah W; Parkey, Cindy

2010-08-01

Findings from 2 studies of the relationship between response-contingent child behavior and child, caregiver-child, and caregiver behavior not directly associated with child contingency learning are described. The participants were 19 children with significant developmental delays and their mothers in 1 study and 22 children with significant developmental delays and their teachers in the second study. Caregivers engaged the children in learning games characterized by behavior-based contingencies for 15 weeks. Research staff observed the children and their caregivers in everyday routines and activities and rated child and caregiver behavior while the children and caregivers were not playing the games. Results from both studies showed that the degree of response-contingent responding during the games was related to child and caregiver behavior, not the focus of the contingency learning opportunities afforded the children. Implications for practice are described.

Profiling medical school learning environments in Malaysia: a validation study of the Johns Hopkins Learning Environment Scale

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Sean Tackett

2015-07-01

Full Text Available Purpose: While a strong learning environment is critical to medical student education, the assessment of medical school learning environments has confounded researchers. Our goal was to assess the validity and utility of the Johns Hopkins Learning Environment Scale (JHLES for preclinical students at three Malaysian medical schools with distinct educational and institutional models. Two schools were new international partnerships, and the third was school leaver program established without international partnership. Methods: First- and second-year students responded anonymously to surveys at the end of the academic year. The surveys included the JHLES, a 28-item survey using five-point Likert scale response options, the Dundee Ready Educational Environment Measure (DREEM, the most widely used method to assess learning environments internationally, a personal growth scale, and single-item global learning environment assessment variables. Results: The overall response rate was 369/429 (86%. After adjusting for the medical school year, gender, and ethnicity of the respondents, the JHLES detected differences across institutions in four out of seven domains (57%, with each school having a unique domain profile. The DREEM detected differences in one out of five categories (20%. The JHLES was more strongly correlated than the DREEM to two thirds of the single-item variables and the personal growth scale. The JHLES showed high internal reliability for the total score (α=0.92 and the seven domains (α, 0.56-0.85. Conclusion: The JHLES detected variation between learning environment domains across three educational settings, thereby creating unique learning environment profiles. Interpretation of these profiles may allow schools to understand how they are currently supporting trainees and identify areas needing attention.

Development and Examination of Personal and Social Responsibility Behaviors Scale

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Bijen FİLİZ

2018-03-01

Full Text Available In this study, “Personal and Social Responsibility Behaviors Scale (PSRB-S” was developed in order to determine students’ responsibility behaviors in accordance with “Personal and Social Responsibility” model developed by Don Hellison and students’ personal and social responsibility levels were examined in terms of gender, age and years of sport practice through this scale. Pertaining to personal and social dimension of responsibility, four-category Likert type trial scale consisting of 52 items and Exploratory Factor Analysis (EFA were applied to 330 high-school students. Items that did not apply as a result of the analysis were omitted from 52-item trial scale and the scale was reduced to 14 items. A final scale consisting of two factors was created. Obtained scale was applied to different 250 high-school students for Confirmatory Factor Analysis (CFA. It has been determined that EFA and CFA results of two-factor PSRB-S and reliability and validity of internal consistency coefficients are at an acceptable level. It was not detected a significance difference in total scores of athlete students’ responsibility behaviors in terms of gender and age variables while there were significant difference in their total scores of years of sport practice.

Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning

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Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…

Ontogeny of Classical and Operant Learning Behaviors in Zebrafish

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Valente, Andre; Huang, Kuo-Hua; Portugues, Ruben; Engert, Florian

2012-01-01

The performance of developing zebrafish in both classical and operant conditioning assays was tested with a particular focus on the emergence of these learning behaviors during development. Strategically positioned visual cues paired with electroshocks were used in two fully automated assays to investigate both learning paradigms. These allow the…

Combining fMRI and behavioral measures to examine the process of human learning.

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Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N

2014-03-01

Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.

Multi-scale learning based segmentation of glands in digital colonrectal pathology images.

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Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

2016-02-01

Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

Setting Learning Analytics in Context: Overcoming the Barriers to Large-Scale Adoption

Science.gov (United States)

Ferguson, Rebecca; Macfadyen, Leah P.; Clow, Doug; Tynan, Belinda; Alexander, Shirley; Dawson, Shane

2014-01-01

A core goal for most learning analytic projects is to move from small-scale research towards broader institutional implementation, but this introduces a new set of challenges because institutions are stable systems, resistant to change. To avoid failure and maximize success, implementation of learning analytics at scale requires explicit and…

Learning Contracts in Undergraduate Courses: Impacts on Student Behaviors and Academic Performance

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Frank, Timothy; Scharf, Lauren F. V

2013-01-01

This project studied the effect of individualized, voluntary learning contracts for 18 students who performed poorly in the first part of the semester. Contracts were hypothesized to increase commitment and motivation, and lead to changes in behaviors and course performance. Self-reported prioritization and learning-related behaviors (completion…

Factor validation of the portuguese version of the social skills scale of the Preschool and Kindergarten Behavior Scales

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Maria João Seabra-Santos

2014-05-01

Full Text Available The assessment of preschoolers’ social skills represents a topic of growing importance in research recently developed in the field. The purpose of this article is to present confirmatory factor analyses studies for the Social Skills scale of the Preschool and Kindergarten Behavior Scales – Second Edition (PKBS-2, a behavior rating scale that evaluates social skills and problem behaviors, adapted and validated for Portuguese preschool children. The 34 items of the Social Skills scale, distributed on three subscales (Social Cooperation/Adjustment, Social Interaction/Empathy and Social Independence/Assertiveness, were grouped into item-parcels. Model adjustment was analyzed for the total sample (N = 2000 and the analyses were replicated for the subsamples collected in the home (n = 1000 and school settings (n = 1000. The factor structure was very stable for the three samples, with high internal consistency levels and correlations between parcels/scales. The results highlight the utility/validity of the Social Skills scale of the PKBS-2 (Portuguese version.

Effects of cooperative learning strategy on undergraduate kinesiology students' learning styles.

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Meeuwsen, Harry J; King, George A; Pederson, Rockie

2005-10-01

A growing body of research supports cooperative learning as an effective teaching strategy. A specific cooperative learning strategy, Team-based Learning, was applied to a convenience sample of four undergraduate sophomore-level motor behavior courses over four semesters from Fall 2002 to Spring 2004 to examine whether this strategy would affect students' learning styles. The data from the Grasha-Reichmann Student Learning Style Scales indicated that this teaching strategy was associated with a significant decrease in the negative Avoidant and Dependent learning styles and an improvement in the positive Participant learning style.

e-Learning quality: Scale development and validation in Indian context

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Arun Kumar Agariya

2012-12-01

Full Text Available The aim of this paper is to develop a reliable and valid e-learning quality measurement scales from the learner as well as faculty perspectives in Indian context. Exploratory factor analysis followed by confirmatory factor analysis was done which is presented in two forms; covariance model and the structural model. The covariance model shows that the factors namely collaboration, industry acceptance and value addition are important from the learner’s point of view whereas the factors namely transparency in assessment, technical know-how and engagement (from students are important from faculty point of view. Factors namely course content and design structures (technology/website design are found equally important for learner’s as well as faculty’s perspective. The structural models validate the previously extracted factors along with their indicators. The findings of this study validate the long held belief that e-learning quality is a multidimensional construct and serves as a critical success factor. The proposed scale will help in identifying issues that contribute towards e-learning quality in Indian context and thereby formulating strategies accordingly, resulting in efficient (in terms of cost and effective (outcomes e-learning practices, which is the necessity of the hour for the economic development of the country. A fair amount of literature on e-learning dealt with identifying factors explaining the constructs of quality, perceived value and satisfaction. But there is paucity of research pertaining to e-learning quality scale development and validation from the learner as well as faculty perspective. This study is an attempt to bridge this gap in the existing literature.

Beliefs and Behaviors in Learning Critical Thinking Skills

OpenAIRE

Octavian REPOLSCHI

2015-01-01

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...

Strong anticipation: Multifractal cascade dynamics modulate scaling in synchronization behaviors

International Nuclear Information System (INIS)

Stephen, Damian G.; Dixon, James A.

2011-01-01

Research highlights: → We investigated anticipatory behaviors in response to chaotic metronomes. → We assessed multifractal structure in tap intervals and onset intervals. → Strength of multifractality in tap intervals appears to match that in onset intervals. - Abstract: Previous research on anticipatory behaviors has found that the fractal scaling of human behavior may attune to the fractal scaling of an unpredictable signal [Stephen DG, Stepp N, Dixon JA, Turvey MT. Strong anticipation: Sensitivity to long-range correlations in synchronization behavior. Physica A 2008;387:5271-8]. We propose to explain this attunement as a case of multifractal cascade dynamics [Schertzer D, Lovejoy S. Generalised scale invariance in turbulent phenomena. Physico-Chem Hydrodyn J 1985;6:623-5] in which perceptual-motor fluctuations are coordinated across multiple time scales. This account will serve to sharpen the contrast between strong and weak anticipation: whereas the former entails a sensitivity to the intermittent temporal structure of an unpredictable signal, the latter simply predicts sensitivity to an aggregate description of an unpredictable signal irrespective of actual sequence. We pursue this distinction through a reanalysis of Stephen et al.'s data by examining the relationship between the widths of singularity spectra for intertap interval time series and for each corresponding interonset interval time series. We find that the attunement of fractal scaling reported by Stephen et al. was not the trivial result of sensitivity to temporal structure in aggregate but reflected a subtle sensitivity to the coordination across multiple time scales of fluctuation in the unpredictable signal.

College students with Internet addiction decrease fewer Behavior Inhibition Scale and Behavior Approach Scale when getting online.

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Ko, Chih-Hung; Wang, Peng-Wei; Liu, Tai-Ling; Yen, Cheng-Fang; Chen, Cheng-Sheng; Yen, Ju-Yu

2015-09-01

The aim of the study is to compare the reinforcement sensitivity between online and offline interaction. The effect of gender, Internet addiction, depression, and online gaming on the difference of reinforcement sensitivity between online and offline were also evaluated. The subjects were 2,258 college students (1,066 men and 1,192 women). They completed the Behavior Inhibition Scale and Behavior Approach Scale (BIS/BAS) according to their experience online or offline. Internet addiction, depression, and Internet activity type were evaluated simultaneously. The results showed that reinforcement sensitivity was lower when interacting online than when interacting offline. College students with Internet addiction decrease fewer score on BIS and BAS after getting online than did others. The higher reward and aversion sensitivity are associated with the risk of Internet addiction. The fun seeking online might contribute to the maintenance of Internet addiction. This suggests that reinforcement sensitivity would change after getting online and would contribute to the risk and maintenance of Internet addiction. © 2014 Wiley Publishing Asia Pty Ltd.

Facilitating behavioral learning and habit change in voice therapy—theoretic premises and practical strategies

DEFF Research Database (Denmark)

Iwarsson, Jenny

2014-01-01

A typical goal of voice therapy is a behavioral change in the patient’s everyday speech. The SLP’s plan for voice therapy should therefore optimally include strategies for automatization. The aim of the present study was to identify and describe factors that promote behavioral learning and habit...... are described and discussed from a learning theory perspective. Nine factors that seem to be relevant to facilitate behavioral learning and habit change in voice therapy are presented, together with related practical strategies and theoretical underpinnings. These are: 1) Cue-altering; 2) Attention exercises; 3...... change in voice behavior and have the potential to affect patient compliance and thus therapy outcome. Research literature from the areas of motor and behavioral learning, habit formation, and habit change was consulted. Also, specific elements from personal experience of clinical voice therapy...

Scaling behavior of an airplane-boarding model.

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Brics, Martins; Kaupužs, Jevgenijs; Mahnke, Reinhard

2013-04-01

An airplane-boarding model, introduced earlier by Frette and Hemmer [Phys. Rev. E 85, 011130 (2012)], is studied with the aim of determining precisely its asymptotic power-law scaling behavior for a large number of passengers N. Based on Monte Carlo simulation data for very large system sizes up to N=2(16)=65536, we have analyzed numerically the scaling behavior of the mean boarding time and other related quantities. In analogy with critical phenomena, we have used appropriate scaling Ansätze, which include the leading term as some power of N (e.g., [proportionality]N(α) for ), as well as power-law corrections to scaling. Our results clearly show that α=1/2 holds with a very high numerical accuracy (α=0.5001±0.0001). This value deviates essentially from α=/~0.69, obtained earlier by Frette and Hemmer from data within the range 2≤N≤16. Our results confirm the convergence of the effective exponent α(eff)(N) to 1/2 at large N as observed by Bernstein. Our analysis explains this effect. Namely, the effective exponent α(eff)(N) varies from values about 0.7 for small system sizes to the true asymptotic value 1/2 at N→∞ almost linearly in N(-1/3) for large N. This means that the variation is caused by corrections to scaling, the leading correction-to-scaling exponent being θ≈1/3. We have estimated also other exponents: ν=1/2 for the mean number of passengers taking seats simultaneously in one time step, β=1 for the second moment of t(b), and γ≈1/3 for its variance.

Facilitating behavioral learning and habit change in voice therapy--theoretic premises and practical strategies.

Science.gov (United States)

Iwarsson, Jenny

2015-12-01

A typical goal of voice therapy is a behavioral change in the patient's everyday speech. The SLP's plan for voice therapy should therefore optimally include strategies for automatization. The aim of the present study was to identify and describe factors that promote behavioral learning and habit change in voice behavior and have the potential to affect patient compliance and thus therapy outcome. Research literature from the areas of motor and behavioral learning, habit formation, and habit change was consulted. Also, specific elements from personal experience of clinical voice therapy are described and discussed from a learning theory perspective. Nine factors that seem to be relevant to facilitate behavioral learning and habit change in voice therapy are presented, together with related practical strategies and theoretical underpinnings. These are: 1) Cue-altering; 2) Attention exercises; 3) Repetition; 4) Cognitive activation; 5) Negative practice; 6) Inhibition through interruption; 7) Decomposing complex behavior; 8) The 'each time-every time' principle; and 9) Successive implementation of automaticity.

E-Learning Turkish Language and Grammar: Analyzing Learners' Behavior

Science.gov (United States)

Georgalas, Panagiotis

2012-01-01

This study analyses the behavior and the preferences of the Greek learners of Turkish language, who use a particular e-learning website in parallel with their studies, namely: http://turkish.pgeorgalas.gr. The website offers free online material in Greek and English language for learning the Turkish language and grammar. The traffic of several…

Parent Behavior Importance Questionnaire-Revised: Scale Development and Psychometric Characteristics

Science.gov (United States)

Mowder, Barbara A.; Shamah, Renee

2011-01-01

This paper reports the scale development and psychometric characteristics of the Parent Behavior Importance Questionnaire-Revised (PBIQ-R). To develop this measure, 502 subject matter experts (SMEs) evaluated 91 parenting behaviors in terms of parenting behavior specificity (e.g., bonding, discipline), importance level, and appropriateness for…

Prototype Vector Machine for Large Scale Semi-Supervised Learning

Energy Technology Data Exchange (ETDEWEB)

Zhang, Kai; Kwok, James T.; Parvin, Bahram

2009-04-29

Practicaldataminingrarelyfalls exactlyinto the supervisedlearning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised learning (SSL). We note that the computationalintensivenessofgraph-based SSLarises largely from the manifold or graph regularization, which in turn lead to large models that are dificult to handle. To alleviate this, we proposed the prototype vector machine (PVM), a highlyscalable,graph-based algorithm for large-scale SSL. Our key innovation is the use of"prototypes vectors" for effcient approximation on both the graph-based regularizer and model representation. The choice of prototypes are grounded upon two important criteria: they not only perform effective low-rank approximation of the kernel matrix, but also span a model suffering the minimum information loss compared with the complete model. We demonstrate encouraging performance and appealing scaling properties of the PVM on a number of machine learning benchmark data sets.

Online Behavior Analysis-Based Student Profile for Intelligent E-Learning

OpenAIRE

Liang, Kun; Zhang, Yiying; He, Yeshen; Zhou, Yilin; Tan, Wei; Li, Xiaoxia

2017-01-01

With the development of mobile platform, such as smart cellphone and pad, the E-Learning model has been rapidly developed. However, due to the low completion rate for E-Learning platform, it is very necessary to analyze the behavior characteristics of online learners to intelligently adjust online education strategy and enhance the quality of learning. In this paper, we analyzed the relation indicators of E-Learning to build the student profile and gave countermeasures. Adopting the similarit...

Chaotic behavior learning of Chua's circuit

International Nuclear Information System (INIS)

Sun Jian-Cheng

2012-01-01

Least-square support vector machines (LS-SVM) are applied for learning the chaotic behavior of Chua's circuit. The system is divided into three multiple-input single-output (MISO) structures and the LS-SVM are trained individually. Comparing with classical approaches, the proposed one reduces the structural complexity and the selection of parameters is avoided. Some parameters of the attractor are used to compare the chaotic behavior of the reconstructed and the original systems for model validation. Results show that the LS-SVM combined with the MISO can be trained to identify the underlying link among Chua's circuit state variables, and exhibit the chaotic attractors under the autonomous working mode

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Students’ Motivation for Learning in Virtual Learning Environments

Directory of Open Access Journals (Sweden)

Andrea Carvalho Beluce

2015-04-01

Full Text Available The specific characteristics of online education require of the student engagement and autonomy, factors which are related to motivation for learning. This study investigated students’ motivation in virtual learning environments (VLEs. For this, it used the Teaching and Learning Strategy and Motivation to Learn Scale in Virtual Learning Environments (TLSM-VLE. The scale presented 32 items and six dimensions, three of which aimed to measure the variables of autonomous motivation, controlled motivation, and demotivation. The participants were 572 students from the Brazilian state of Paraná, enrolled on higher education courses on a continuous education course. The results revealed significant rates for autonomous motivational behavior. It is considered that the results obtained may provide contributions for the educators and psychologists who work with VLEs, leading to further studies of the area providing information referent to the issue investigated in this study.

Validation of the bipolar disorder etiology scale based on psychological behaviorism theory and factors related to the onset of bipolar disorder.

Directory of Open Access Journals (Sweden)

Jae Woo Park

Full Text Available OBJECTIVES: The aim of this study was to identify psychosocial factors related to the onset of bipolar I disorder (BD. To do so, the Bipolar Disorder Etiology Scale (BDES, based on psychological behaviorism, was developed and validated. Using the BDES, common factors related to both major depressive disorder (MDD and BD and specific factors related only to BD were investigated. METHOD: The BDES, which measures 17 factors based on psychological behaviorism hypotheses, was developed and validated. This scale was administered to 113 non-clinical control subjects, 30 subjects with MDD, and 32 people with BD. ANOVA and post hoc analyses were conducted. Subscales on which MDD and BD groups scored higher than controls were classified as common factors, while those on which the BD group scored higher than MDD and control groups were classified as specific factors. RESULTS: The BDES has acceptable reliability and validity. Twelve common factors influence both MDD and BD and one specific factor influences only BD. Common factors include the following: learning grandiose self-labeling, learning dangerous behavior, reinforcing impulsive behavior, exposure to irritability, punishment of negative emotional expression, lack of support, sleep problems, antidepressant problems, positive arousal to threat, lack of social skills, and pursuit of short-term pleasure. The specific factor is manic emotional response. CONCLUSIONS: Manic emotional response was identified as a specific factor related to the onset of BD, while parents' grandiose labeling is a candidate for a specific factor. Many factors are related to the onset of both MDD and BD.

Data concerning the psychometric properties of the Behavioral Inhibition/Behavioral Activation Scales for the Portuguese population.

Science.gov (United States)

Moreira, Diana; Almeida, Fernando; Pinto, Marta; Segarra, Pilar; Barbosa, Fernando

2015-09-01

The behavioral inhibition/behavioral activation (BIS/BAS) scales (Carver & White, 1994), which allow rating the Gray's motivational systems, were translated and adapted into Portuguese. In this study, the authors present the procedure and the psychometric analyses of the Portuguese version of the scales, which included basic item and scales psychometric characteristics, as well as confirmatory and exploratory factor analyses. After the psychometric analyses provided evidence for the quality of the Portuguese version of the scales, the normative data was provided by age and school grade. The confirmatory factor analysis of the BIS/BAS scales that the authors performed did not demonstrate satisfactory fit for the 2- or 4-factor solution. The authors also tested the more recent 5-factor model, but the fit indices remained inadequate. As fit indices were not satisfactory they proceeded with an exploratory factor analysis to examine the structure of the Portuguese scales. These psychometric analyses provided evidence of a successful translation of the original scales. Therefore these scales can now be used in future research with Portuguese or Brazilian population. (c) 2015 APA, all rights reserved.

Validity & reliability of the Persian version of Grasha-Richmann student learning styles scale

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ALI REZA BANESHI

2013-10-01

Full Text Available Introduction: The present study aimed to investigate the psychometric properties of Grasha-Riechmann Student Learning Styles Scale. Method: The participants included 1039 students (421 students in human and 618 students in technical sciences, selected through the stratified sampling method from Tehran University. They answered the Grasha-Riechmann student learning style scale and the data was analyzed with exploratory and confirmatory factor analyses. Results: The findings acquired from exploratory factor analysis (n=561, using principal components analysis with varimax rotation showed that Grasha- Riechmann Student Learning Styles Scale includes six factors: Avoidant, Collaborative, Participative, Dependent, Competitive, and Independent. The factors acquired from confirmatory factor analysis (n=478, as model fit indices indicated, was confirmed by indices in exploratory factor analysis. The internal consistency of each subscale, ranging from 0.58 to 0.80, was at an acceptable level. Conclusion: According to the findings, it seems that Participative Styles Scale to be an instrument qualifying validity and reliability for measuring learning interactive styles.

A SCALE-UP Mock-Up: Comparison of Student Learning Gains in High- and Low-Tech Active-Learning Environments.

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Soneral, Paula A G; Wyse, Sara A

2017-01-01

Student-centered learning environments with upside-down pedagogies (SCALE-UP) are widely implemented at institutions across the country, and learning gains from these classrooms have been well documented. This study investigates the specific design feature(s) of the SCALE-UP classroom most conducive to teaching and learning. Using pilot survey data from instructors and students to prioritize the most salient SCALE-UP classroom features, we created a low-tech "Mock-up" version of this classroom and tested the impact of these features on student learning, attitudes, and satisfaction using a quasi--experimental setup. The same instructor taught two sections of an introductory biology course in the SCALE-UP and Mock-up rooms. Although students in both sections were equivalent in terms of gender, grade point average, incoming ACT, and drop/fail/withdraw rate, the Mock-up classroom enrolled significantly more freshmen. Controlling for class standing, multiple regression modeling revealed no significant differences in exam, in-class, preclass, and Introduction to Molecular and Cellular Biology Concept Inventory scores between the SCALE-UP and Mock-up classrooms. Thematic analysis of student comments highlighted that collaboration and whiteboards enhanced the learning experience, but technology was not important. Student satisfaction and attitudes were comparable. These results suggest that the benefits of a SCALE-UP experience can be achieved at lower cost without technology features. © 2017 P. A. G. Soneral and S. A. Wyse. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Scaling behavior of an airplane-boarding model

Science.gov (United States)

Brics, Martins; Kaupužs, Jevgenijs; Mahnke, Reinhard

2013-04-01

An airplane-boarding model, introduced earlier by Frette and Hemmer [Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.85.011130 85, 011130 (2012)], is studied with the aim of determining precisely its asymptotic power-law scaling behavior for a large number of passengers N. Based on Monte Carlo simulation data for very large system sizes up to N=216=65536, we have analyzed numerically the scaling behavior of the mean boarding time and other related quantities. In analogy with critical phenomena, we have used appropriate scaling Ansätze, which include the leading term as some power of N (e.g., ∝Nα for ), as well as power-law corrections to scaling. Our results clearly show that α=1/2 holds with a very high numerical accuracy (α=0.5001±0.0001). This value deviates essentially from α≃0.69, obtained earlier by Frette and Hemmer from data within the range 2≤N≤16. Our results confirm the convergence of the effective exponent αeff(N) to 1/2 at large N as observed by Bernstein. Our analysis explains this effect. Namely, the effective exponent αeff(N) varies from values about 0.7 for small system sizes to the true asymptotic value 1/2 at N→∞ almost linearly in N-1/3 for large N. This means that the variation is caused by corrections to scaling, the leading correction-to-scaling exponent being θ≈1/3. We have estimated also other exponents: ν=1/2 for the mean number of passengers taking seats simultaneously in one time step, β=1 for the second moment of tb, and γ≈1/3 for its variance.

Measuring strategies for learning regulation in medical education: scale reliability and dimensionality in a Swedish sample.

Science.gov (United States)

Edelbring, Samuel

2012-08-15

The degree of learners' self-regulated learning and dependence on external regulation influence learning processes in higher education. These regulation strategies are commonly measured by questionnaires developed in other settings than in which they are being used, thereby requiring renewed validation. The aim of this study was to psychometrically evaluate the learning regulation strategy scales from the Inventory of Learning Styles with Swedish medical students (N = 206). The regulation scales were evaluated regarding their reliability, scale dimensionality and interrelations. The primary evaluation focused on dimensionality and was performed with Mokken scale analysis. To assist future scale refinement, additional item analysis, such as item-to-scale correlations, was performed. Scale scores in the Swedish sample displayed good reliability in relation to published results: Cronbach's alpha: 0.82, 0.72, and 0.65 for self-regulation, external regulation and lack of regulation scales respectively. The dimensionalities in scales were adequate for self-regulation and its subscales, whereas external regulation and lack of regulation displayed less unidimensionality. The established theoretical scales were largely replicated in the exploratory analysis. The item analysis identified two items that contributed little to their respective scales. The results indicate that these scales have an adequate capacity for detecting the three theoretically proposed learning regulation strategies in the medical education sample. Further construct validity should be sought by interpreting scale scores in relation to specific learning activities. Using established scales for measuring students' regulation strategies enables a broad empirical base for increasing knowledge on regulation strategies in relation to different disciplinary settings and contributes to theoretical development.

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

Science.gov (United States)

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Genetic dissection of behavioral flexibility: reversal learning in mice.

Science.gov (United States)

Laughlin, Rick E; Grant, Tara L; Williams, Robert W; Jentsch, J David

2011-06-01

Behavioral inflexibility is a feature of schizophrenia, attention-deficit/hyperactivity disorder, and behavior addictions that likely results from heritable deficits in the inhibitory control over behavior. Here, we investigate the genetic basis of individual differences in flexibility, measured using an operant reversal learning task. We quantified discrimination acquisition and subsequent reversal learning in a cohort of 51 BXD strains of mice (2-5 mice/strain, n = 176) for which we have matched data on sequence, gene expression in key central nervous system regions, and neuroreceptor levels. Strain variation in trials to criterion on acquisition and reversal was high, with moderate heritability (∼.3). Acquisition and reversal learning phenotypes did not covary at the strain level, suggesting that these traits are effectively under independent genetic control. Reversal performance did covary with dopamine D2 receptor levels in the ventral midbrain, consistent with a similar observed relationship between impulsivity and D2 receptors in humans. Reversal, but not acquisition, is linked to a locus on mouse chromosome 10 with a peak likelihood ratio statistic at 86.2 megabase (p work demonstrates the clear trait independence between, and genetic control of, discrimination acquisition and reversal and illustrates how globally coherent data sets for a single panel of highly related strains can be interrogated and integrated to uncover genetic sources and molecular and neuropharmacological candidates of complex behavioral traits relevant to human psychopathology. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

The Fragile X Syndrome: Behavioral Phenotype and Learning Disabilities

Directory of Open Access Journals (Sweden)

Claudia GRAU RUBIO

2016-04-01

Full Text Available In this article, we describe the behavioral phenotype of individuals with Fragile X Syndrome and its impact in the educational scope. This syndrome is characterized by difficulties in sensory integration, cognitive deficits (verbal reasoning, abstract/ visual and cuantitative skills, short term memory, sequential processing, attention and executive processes, language disorders (phonetic-phonologicals, semanticals, morphosyntacticals and pragmaticals and communication disorders, social anxiety, general hyperarousal, autism, non autistic social difficulties, attention deficit and hyperactivity, and learning disabilities. The behavioral phenotype is highly variable and depends on sex, age, and mutation status (full mutation or premutation. The behavioural phenotype has important repercussions in education, as it enables us to understand the learning disabilities and to develop specific intervention strategies.

Deep Feature Learning and Cascaded Classifier for Large Scale Data

DEFF Research Database (Denmark)

Prasoon, Adhish

from data rather than having a predefined feature set. We explore deep learning approach of convolutional neural network (CNN) for segmenting three dimensional medical images. We propose a novel system integrating three 2D CNNs, which have a one-to-one association with the xy, yz and zx planes of 3D......This thesis focuses on voxel/pixel classification based approaches for image segmentation. The main application is segmentation of articular cartilage in knee MRIs. The first major contribution of the thesis deals with large scale machine learning problems. Many medical imaging problems need huge...... amount of training data to cover sufficient biological variability. Learning methods scaling badly with number of training data points cannot be used in such scenarios. This may restrict the usage of many powerful classifiers having excellent generalization ability. We propose a cascaded classifier which...

How the challenge of explaining learning influenced the origins and development of John B. Watson's behaviorism.

Science.gov (United States)

Rilling, M

2000-01-01

Before he invented behaviorism, John B. Watson considered learning one of the most important topics in psychology. Watson conducted excellent empirical research on animal learning. He developed behaviorism in part to promote research and elevate the status of learning in psychology. Watson was much less successful in the adequacy and originality of the mechanisms he proposed to explain learning. By assimilating the method of classical conditioning and adopting Pavlov's theory of stimulus substitution, Watson linked behaviorism with a new method that could compete with both Titchener's method of introspection and Freud's methods of psychoanalysis. Watson's interest in explaining psychopathology led to the discovery of conditioned emotional responses and a behavioristic explanation for the learning of phobic behavior. Watson established learning as a central topic for basic research and application in American psychology.

Modeling the behavioral substrates of associate learning and memory - Adaptive neural models

Science.gov (United States)

Lee, Chuen-Chien

1991-01-01

Three adaptive single-neuron models based on neural analogies of behavior modification episodes are proposed, which attempt to bridge the gap between psychology and neurophysiology. The proposed models capture the predictive nature of Pavlovian conditioning, which is essential to the theory of adaptive/learning systems. The models learn to anticipate the occurrence of a conditioned response before the presence of a reinforcing stimulus when training is complete. Furthermore, each model can find the most nonredundant and earliest predictor of reinforcement. The behavior of the models accounts for several aspects of basic animal learning phenomena in Pavlovian conditioning beyond previous related models. Computer simulations show how well the models fit empirical data from various animal learning paradigms.

Quality assurance of the clinical learning environment in Austria: Construct validity of the Clinical Learning Environment, Supervision and Nurse Teacher Scale (CLES+T scale).

Science.gov (United States)

Mueller, Gerhard; Mylonas, Demetrius; Schumacher, Petra

2018-04-21

Within nursing education, the clinical learning environment is of a high importance in regards to the development of competencies and abilities. The organization, atmosphere, and supervision in the clinical learning environment are only a few factors that influence this development. In Austria there is currently no valid instrument available for the evaluation of influencing factors. The aim of the study was to test the construct validity with principal component analysis as well as the internal consistency of the German Clinical Learning Environment, Supervision and Teacher Scale (CLES+T scale) in Austria. The present validation study has a descriptive-quantitative cross-sectional design. The sample consisted of 385 nursing students from thirteen training institutions in Austria. The data collection was carried out online between March and April 2016. Starting with a polychoric correlation matrix, a parallel analysis with principal component extraction and promax rotation was carried out due to the ordinal data. The exploratory ordinal factor analysis supported a four-component solution and explained 73% of the total variance. The internal consistency of all 25 items reached a Cronbach's α of 0.95 and the four components ranged between 0.83 and 0.95. The German version of the CLES+T scale seems to be a useful instrument for identifying potential areas of improvement in clinical practice in order to derive specific quality measures for the practical learning environment. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Study of Developing an Attitude Scale towards Authentic Learning Environments and Evaluation

Science.gov (United States)

Çetinkaya, Murat

2018-01-01

The aim of the research is to improve a valid and reliable attributing scale which identifies authentic learning environments and evaluation attributes of the science teacher candidates. The study has been designed on the base of validity and reliability of the scale developed to evaluate the authentic learning environments. The research group is…

Treatment of avoidance behavior as an adjunct to exposure therapy: Insights from modern learning theory.

Science.gov (United States)

Treanor, Michael; Barry, Tom J

2017-09-01

Pathological avoidance of benign stimuli is a hallmark of anxiety and related disorders, and exposure-based treatments have often encouraged the removal of avoidance, or safety behaviors, due to their negative effects on extinction learning. Unfortunately, empirical evidence suggests that avoidance behaviors can persist following treatment, and the mere availability of avoidance behavior can be sufficient to renew fear following successful extinction learning. The present paper critically examines the function of avoidance behavior through the lens of modern learning theory, and speculates on novel behavioral and pharmacological strategies for targeting avoidance as an adjunct to current evidence-based treatments. Copyright © 2017. Published by Elsevier Ltd.

Scaling behaviors of magnetoconductivity in amorphous indium oxide near the metal-insulator transition

CERN Document Server

Lee, Y J; Kim, Y S

2000-01-01

Magnetoconductivity is measured in an amorphous indium-oxide sample which is in the microscopic region. Two different scaling behaviors are observed for the magnetoconductivity The scaling behavior is determined by either the localization or the electron correlation effects, whichever becomes stronger more rapidly at a given temperature and magnetic field. Qualitative explanations are given for the observed scaling behaviors. A curve of a function of H/T sup 2 sup / sup 3 exists on which all our magnetoconductivity data lie.

Measuring strategies for learning regulation in medical education: Scale reliability and dimensionality in a Swedish sample

Directory of Open Access Journals (Sweden)

Edelbring Samuel

2012-08-01

Full Text Available Abstract Background The degree of learners’ self-regulated learning and dependence on external regulation influence learning processes in higher education. These regulation strategies are commonly measured by questionnaires developed in other settings than in which they are being used, thereby requiring renewed validation. The aim of this study was to psychometrically evaluate the learning regulation strategy scales from the Inventory of Learning Styles with Swedish medical students (N = 206. Methods The regulation scales were evaluated regarding their reliability, scale dimensionality and interrelations. The primary evaluation focused on dimensionality and was performed with Mokken scale analysis. To assist future scale refinement, additional item analysis, such as item-to-scale correlations, was performed. Results Scale scores in the Swedish sample displayed good reliability in relation to published results: Cronbach’s alpha: 0.82, 0.72, and 0.65 for self-regulation, external regulation and lack of regulation scales respectively. The dimensionalities in scales were adequate for self-regulation and its subscales, whereas external regulation and lack of regulation displayed less unidimensionality. The established theoretical scales were largely replicated in the exploratory analysis. The item analysis identified two items that contributed little to their respective scales. Discussion The results indicate that these scales have an adequate capacity for detecting the three theoretically proposed learning regulation strategies in the medical education sample. Further construct validity should be sought by interpreting scale scores in relation to specific learning activities. Using established scales for measuring students’ regulation strategies enables a broad empirical base for increasing knowledge on regulation strategies in relation to different disciplinary settings and contributes to theoretical development.

Organic Determinants of Learning and Behavioral Disorders.

Science.gov (United States)

Philpott, William H.; And Others

Theories regarding organic determinants of learning and behavior disorders are reviewed historically. Cases illustrating how a bio-ecologic examination can isolate the substances to which a person reacts and some of the reasons for those reactions are presented; and the role of various disorders in relation to the central nervous system is…

Applications of operant learning theory to the management of challenging behavior after traumatic brain injury.

Science.gov (United States)

Wood, Rodger Ll; Alderman, Nick

2011-01-01

For more than 3 decades, interventions derived from learning theory have been delivered within a neurobehavioral framework to manage challenging behavior after traumatic brain injury with the aim of promoting engagement in the rehabilitation process and ameliorating social handicap. Learning theory provides a conceptual structure that facilitates our ability to understand the relationship between challenging behavior and environmental contingencies, while accommodating the constraints upon learning imposed by impaired cognition. Interventions derived from operant learning theory have most frequently been described in the literature because this method of associational learning provides good evidence for the effectiveness of differential reinforcement methods. This article therefore examines the efficacy of applying operant learning theory to manage challenging behavior after TBI as well as some of the limitations of this approach. Future developments in the application of learning theory are also considered.

Different behaviors of epidemic spreading in scale-free networks with identical degree sequence

Energy Technology Data Exchange (ETDEWEB)

Chu Xiangwei; Guan Jihong [School of Electronics and Information, Tongji University, 4800 Cao' an Road, Shanghai 201804 (China); Zhang Zhongzhi; Zhou Shuigeng [School of Computer Science, Fudan University, Shanghai 200433 (China); Li Mo, E-mail: zhangzz@fudan.edu.c, E-mail: jhguan@tongj.edu.c, E-mail: sgzhou@fudan.edu.c [Software School, Fudan University, Shanghai 200433 (China)

2010-02-12

Recently, the study of dynamical behaviors of the susceptible-infected (SI) disease model in complex networks, especially in Barabasi-Albert (BA) scale-free networks, has attracted much attention. Although some interesting phenomena have been observed, the formative reasons for those particular dynamical behaviors are still not well understood, despite the speculation that topological properties (for example the degree distribution) have a strong impact on epidemic spreading. In this paper, we study the evolution behaviors of epidemic spreading on a class of scale-free networks sharing identical degree sequence, and observe significantly different evolution behaviors in the whole family of networks. We show that the power-law degree distribution does not suffice to characterize the dynamical behaviors of disease diffusion on scale-free networks.

Different behaviors of epidemic spreading in scale-free networks with identical degree sequence

International Nuclear Information System (INIS)

Chu Xiangwei; Guan Jihong; Zhang Zhongzhi; Zhou Shuigeng; Li Mo

2010-01-01

Recently, the study of dynamical behaviors of the susceptible-infected (SI) disease model in complex networks, especially in Barabasi-Albert (BA) scale-free networks, has attracted much attention. Although some interesting phenomena have been observed, the formative reasons for those particular dynamical behaviors are still not well understood, despite the speculation that topological properties (for example the degree distribution) have a strong impact on epidemic spreading. In this paper, we study the evolution behaviors of epidemic spreading on a class of scale-free networks sharing identical degree sequence, and observe significantly different evolution behaviors in the whole family of networks. We show that the power-law degree distribution does not suffice to characterize the dynamical behaviors of disease diffusion on scale-free networks.

Social Learning Theory and Behavioral Therapy: Considering Human Behaviors within the Social and Cultural Context of Individuals and Families.

Science.gov (United States)

McCullough Chavis, Annie

2011-01-01

This article examines theoretical thoughts of social learning theory and behavioral therapy and their influences on human behavior within a social and cultural context. The article utilizes two case illustrations with applications for consumers. It points out the abundance of research studies concerning the effectiveness of social learning theory, and the paucity of research studies regarding effectiveness and evidence-based practices with diverse groups. Providing a social and cultural context in working with diverse groups with reference to social learning theory adds to the literature for more cultural considerations in adapting the theory to women, African Americans, and diverse groups.

Anomalous Scaling Behaviors in a Rice-Pile Model with Two Different Driving Mechanisms

International Nuclear Information System (INIS)

Zhang Duanming; Sun Hongzhang; Li Zhihua; Pan Guijun; Yu Boming; Li Rui; Yin Yanping

2005-01-01

The moment analysis is applied to perform large scale simulations of the rice-pile model. We find that this model shows different scaling behavior depending on the driving mechanism used. With the noisy driving, the rice-pile model violates the finite-size scaling hypothesis, whereas, with fixed driving, it shows well defined avalanche exponents and displays good finite size scaling behavior for the avalanche size and time duration distributions.

Scaling up graph-based semisupervised learning via prototype vector machines.

Science.gov (United States)

Zhang, Kai; Lan, Liang; Kwok, James T; Vucetic, Slobodan; Parvin, Bahram

2015-03-01

When the amount of labeled data are limited, semisupervised learning can improve the learner's performance by also using the often easily available unlabeled data. In particular, a popular approach requires the learned function to be smooth on the underlying data manifold. By approximating this manifold as a weighted graph, such graph-based techniques can often achieve state-of-the-art performance. However, their high time and space complexities make them less attractive on large data sets. In this paper, we propose to scale up graph-based semisupervised learning using a set of sparse prototypes derived from the data. These prototypes serve as a small set of data representatives, which can be used to approximate the graph-based regularizer and to control model complexity. Consequently, both training and testing become much more efficient. Moreover, when the Gaussian kernel is used to define the graph affinity, a simple and principled method to select the prototypes can be obtained. Experiments on a number of real-world data sets demonstrate encouraging performance and scaling properties of the proposed approach. It also compares favorably with models learned via l1 -regularization at the same level of model sparsity. These results demonstrate the efficacy of the proposed approach in producing highly parsimonious and accurate models for semisupervised learning.

Behaviorism, latent learning, and cognitive maps: needed revisions in introductory psychology textbooks.

Science.gov (United States)

Jensen, Robert

2006-01-01

This paper critically assesses the scholarship in introductory psychology textbooks in relation to the topic of latent learning. A review of the treatment of latent learning in 48 introductory psychology textbooks published between 1948 and 2004, with 21 of these texts published since 1999, reveals that the scholarship on the topic of latent learning demonstrated in introductory textbooks warrants improvement. Errors that persist in textbooks include the assertion that the latent learning experiments demonstrate unequivocally that reinforcement was not necessary for learning to occur, that behavioral theories could not account for the results of the latent learning experiments, that B. F. Skinner was an S-R association behaviorist who argued that reinforcement is necessary for learning to occur, and that because behavioral theories (including that of B. F. Skinner) were unable explain the results of the latent learning experiments the cognitive map invoked by Edward Tolman is the only explanation for latent learning. Finally, the validity of the cognitive map is typically accepted without question. Implications of the presence of these errors for students and the discipline are considered. Lastly, remedies are offered to improve the scholarship found in introductory psychology textbooks.

A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns

Science.gov (United States)

Kinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam

2013-01-01

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

Effects of Group Awareness and Self-Regulation Level on Online Learning Behaviors

Science.gov (United States)

Lin, Jian-Wei; Szu, Yu-Chin; Lai, Ching-Neng

2016-01-01

Group awareness can affect student online learning while self-regulation also can substantially influence student online learning. Although some studies identify that these two variables may partially determine learning behavior, few empirical studies or thorough analyses elucidate the simultaneous impact of these two variables (group awareness…

Development of leadership behaviors in undergraduate nursing students: a service-learning approach.

Science.gov (United States)

Foli, Karen J; Braswell, Melanie; Kirkpatrick, Jane; Lim, Eunjung

2014-01-01

The purpose of this study was to determine leadership behaviors developed by nursing students and peers before and after a service-learning experience. Nurses have been called to fill growing needs in the health care setting, rendering care to vulnerable and diverse populations in a wide range of organizations. Leadership behaviors are therefore essential. Baccalaureate students (N = 65) completed the Student Leadership Practices Inventory-Self at the beginning and end of the semester. The students also rated peers using the Leadership Practices Inventory-Observer and answered six questions about service-learning. Repeated measures of analysis of variance for pre- and posttests revealed that leadership behaviors improved (p leadership course is an effective approach to the development of leadership behaviors.

Crayfish Behavior: Observing Arthropods to Learn about Science & Scientific Inquiry

Science.gov (United States)

Rop, Charles J.

2010-01-01

This is a set of animal behavior investigations in which students will practice scientific inquiry as they observe crayfish, ask questions, and discuss territoriality, social interactions, and other behaviors. In doing this, they hone their skills of observation, learn to record and analyze data, control for variables, write hypotheses, make…

A Proposed Framework to Understand the Intrinsic Motivation Factors on University Students’ Behavioral Intention to Use a Mobile Application for Learning

Directory of Open Access Journals (Sweden)

Ronnie H. Shroff

2017-04-01

Full Text Available Aim/Purpose: By integrating a motivational perspective into the Technology Acceptance Model, the goal of this study is to empirically test the causal relationship of intrinsic motivational factors on students’ behavioral intention to use (BIU a mobile application for learning. Background:\tAlthough the Technology Acceptance Model is a significant model, it largely remains incomplete as it does not take into consideration the motivation factors and/or outside influences in the adoption of new technology. Methodology: A Mobile Application Motivation Instrument (MAMI was developed from a comprehensive review of literature on intrinsic motivation and verified using a formalized card sorting procedure. Four intrinsic motivation scales were developed: perceived competence (COM, perceived challenge (CHA, perceived choice (CHO, and perceived interest (INT. Consequently, a scale to assess students’ behavioral intention (BIU to use mobile applications was developed using existing scales from prior TAM instruments. Contribution: Incorporating the motivational factors into TAM may provide better explanation and prediction of student acceptance and usage of mobile applications. A potential contribution of this study is the development of a reliable and valid instrument that could be further used by a growing community of researchers, instructional designers, and instructors. Findings: Data were collected from 193 participants to test the causal relationship of perceived competence (COM, perceived challenge (CHA, perceived choice (CHO, and perceived interest (INT on students’ behavioral intention to use (BIU a mobile application, using a structural equation modeling approach. The structural path model indicated that perceived competence (COM, perceived challenge (CHA, perceived choice (CHO, and perceived interest (INT had a significant influence on students’ behavioral intention to use (BIU a mobile application for learning. Implications of this study

Probabilistic Simulation of Multi-Scale Composite Behavior

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Chamis, Christos C.

2012-01-01

A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time.

Assessment of Readiness to Participate in Distance Learning of the Certified Florida Behavioral Workforce

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Baston, George R.

2011-01-01

This research study explored perceptions of readiness to participate in distance learning among the certified behavioral workforce in Florida. The study sought to determine if there were significant differences in perception of readiness to participate in distance learning between certified behavioral health professionals at the administrator…

Cooperative learning benefits scale: construction and validation studies

Directory of Open Access Journals (Sweden)

José Lopes

2014-07-01

Full Text Available The aim of this study was to develop and validate a scale of benefits of the Cooperative Learning (SBCL given the exiguity of instruments that evaluate these outputs of the method. The study resorted to a convenience sample comprised of 162 students, males and females, aged between 11 and 18 years. The final instrument has 23 items in a two-dimensional factor structure: psychological and academic benefits and social benefits. The results indicate that the SBCL present good psychometric properties (construct and discriminant validity and reliability. The results are discussed in light of the model of cooperative learning.

Examining Culture's Impact on the Learning Behaviors of International Students from Confucius Culture Studying in Western Online Learning Context

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Kang, Haijun; Chang, Bo

2016-01-01

There is a lack of shared understanding of how culture impacts learning in online environment. Utilizing document analysis, the authors in this research study culture's impact on the learning behaviors of student sojourners from Confucius culture studying in Western online learning context. The shared understandings of Confucius culture and…

Learning in an estimated medium-scale DSGE model

Czech Academy of Sciences Publication Activity Database

Slobodyan, Sergey; Wouters, R.

2012-01-01

Roč. 36, č. 1 (2012), s. 26-46 ISSN 0165-1889 R&D Projects: GA ČR(CZ) GCP402/11/J018 Institutional support: PRVOUK-P23 Keywords : constant-gain adaptive learning * medium-scale DSGE model * DSGE- VAR Subject RIV: AH - Economics Impact factor: 0.807, year: 2012

EGameFlow: A Scale to Measure Learners' Enjoyment of E-Learning Games

Science.gov (United States)

Fu, Fong-Ling; Su, Rong-Chang; Yu, Sheng-Chin

2009-01-01

In an effective e-learning game, the learner's enjoyment acts as a catalyst to encourage his/her learning initiative. Therefore, the availability of a scale that effectively measures the enjoyment offered by e-learning games assist the game designer to understanding the strength and flaw of the game efficiently from the learner's points of view.…

The Relationships among Learning Behaviors, Major Satisfaction, and Study Skills of First-Year Medical Students.

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Park, Minjung

2011-06-01

This study aims at increasing our understanding of first-year medical students' learning behaviors, major satisfaction, and study skills. We investigate different features of freshmen's behavior in relation to learning and explore the extent to which freshmen were satisfied with their major and perceived their study skills. A total of 106 freshmen participated in this study. At midyear, first-year medical students were asked to complete a questionnaire that included the learning behaviors, major satisfaction, and study skills. The data collected from the survey were analyzed using t-test, ANOVA, chi-square test, correlation analysis, and multiple regression analysis. The study reported that most of freshmen had a lot of difficulties in studying at medical school by lack of prior learning. Despite first-year students, they were studying hard their major. Freshmen spent studying an average of 1 hour or less than 2 hours every day. The study also indicated that of major satisfaction, the overall satisfaction of the department was the highest and the satisfaction in learning environment was the lowest. There were significant differences among the freshmen on the major satisfaction due to admission process, academic performance, and housing type. Of 11 study skills, while freshman highly perceived their teamwork, stress management, and reading skills, their weak study skills identified in this study were writing, note taking, time management, and test taking skills. There were significant differences among the freshmen on the study skills due to gender and academic performance. Finally, freshmen's learning behaviors and major satisfaction were significantly associated with some of study skills. This study may have implications for the academic adjustment and learning processes in the first year. We need to consider variables such as learning behaviors, major satisfaction, and study skills, when discussing about how to maximize the learning potential of medical students

The Pennsylvania Positive Behavior Support Network: Describing Our Scale-Up

Science.gov (United States)

Runge, Timothy J.; Longwill, Douglas A.; Staszkiewicz, Mark J.; Palmiero, James; Lawson, Tina M.

2016-01-01

Pennsylvania began scaling up high-fidelity implementation of SchoolWide Positive Behavioral Interventions and Supports (SWPBIS) in 2006-2007 due to converging regulatory, legal, ethical, and practical influences. The Pennsylvania Community of Practice on School-Based Behavioral Health adopted Algozzine et al.'s (2010) blueprint to describe and…

Experience the city : analysis of space-time behavior and spatial learning

NARCIS (Netherlands)

Moiseeva, A.

2013-01-01

Learning plays an important role by coding information into individual cognitive maps that can be used to make decisions concerning individual behavior in space. Through traveling people learn about the urban environment and update their knowledge. In this regard, the growing concern in the field of

Hierarchical Learning of Tree Classifiers for Large-Scale Plant Species Identification.

Science.gov (United States)

Fan, Jianping; Zhou, Ning; Peng, Jinye; Gao, Ling

2015-11-01

In this paper, a hierarchical multi-task structural learning algorithm is developed to support large-scale plant species identification, where a visual tree is constructed for organizing large numbers of plant species in a coarse-to-fine fashion and determining the inter-related learning tasks automatically. For a given parent node on the visual tree, it contains a set of sibling coarse-grained categories of plant species or sibling fine-grained plant species, and a multi-task structural learning algorithm is developed to train their inter-related classifiers jointly for enhancing their discrimination power. The inter-level relationship constraint, e.g., a plant image must first be assigned to a parent node (high-level non-leaf node) correctly if it can further be assigned to the most relevant child node (low-level non-leaf node or leaf node) on the visual tree, is formally defined and leveraged to learn more discriminative tree classifiers over the visual tree. Our experimental results have demonstrated the effectiveness of our hierarchical multi-task structural learning algorithm on training more discriminative tree classifiers for large-scale plant species identification.

Maternal intraguild predation risk affects offspring anti-predator behavior and learning in mites

Science.gov (United States)

Seiter, Michael; Schausberger, Peter

2015-01-01

Predation risk is a strong selective force shaping prey morphology, life history and behavior. Anti-predator behaviors may be innate, learned or both but little is known about the transgenerational behavioral effects of maternally experienced predation risk. We examined intraguild predation (IGP) risk-induced maternal effects on offspring anti-predator behavior, including learning, in the predatory mite Phytoseiulus persimilis. We exposed predatory mite mothers during egg production to presence or absence of the IG predator Amblyseius andersoni and assessed whether maternal stress affects the anti-predator behavior, including larval learning ability, of their offspring as protonymphs. Protonymphs emerging from stressed or unstressed mothers, and having experienced IGP risk as larvae or not, were subjected to choice situations with and without IG predator traces. Predator-experienced protonymphs from stressed mothers were the least active and acted the boldest in site choice towards predator cues. We argue that the attenuated response of the protonymphs to predator traces alone represents optimized risk management because no immediate risk existed. Such behavioral adjustment could reduce the inherent fitness costs of anti-predator behaviors. Overall, our study suggests that P. persimilis mothers experiencing IGP risk may prime their offspring to behave more optimally in IGP environments. PMID:26449645

Using findings in multimedia learning to inform technology-based behavioral health interventions.

Science.gov (United States)

Aronson, Ian David; Marsch, Lisa A; Acosta, Michelle C

2013-09-01

Clinicians and researchers are increasingly using technology-based behavioral health interventions to improve intervention effectiveness and to reach underserved populations. However, these interventions are rarely informed by evidence-based findings of how technology can be optimized to promote acquisition of key skills and information. At the same time, experts in multimedia learning generally do not apply their findings to health education or conduct research in clinical contexts. This paper presents an overview of some key aspects of multimedia learning research that may allow those developing health interventions to apply informational technology with the same rigor as behavioral science content. We synthesized empirical multimedia learning literature from 1992 to 2011. We identified key findings and suggested a framework for integrating technology with educational and behavioral science theory. A scientific, evidence-driven approach to developing technology-based interventions can yield greater effectiveness, improved fidelity, increased outcomes, and better client service.

Behavioral similarity measurement based on image processing for robots that use imitative learning

Science.gov (United States)

Sterpin B., Dante G.; Martinez S., Fernando; Jacinto G., Edwar

2017-02-01

In the field of the artificial societies, particularly those are based on memetics, imitative behavior is essential for the development of cultural evolution. Applying this concept for robotics, through imitative learning, a robot can acquire behavioral patterns from another robot. Assuming that the learning process must have an instructor and, at least, an apprentice, the fact to obtain a quantitative measurement for their behavioral similarity, would be potentially useful, especially in artificial social systems focused on cultural evolution. In this paper the motor behavior of both kinds of robots, for two simple tasks, is represented by 2D binary images, which are processed in order to measure their behavioral similarity. The results shown here were obtained comparing some similarity measurement methods for binary images.

The Learning Loss Scale as an Assessment Tool: An Empirical Examination of Convergent Validity with Performative Measures

Science.gov (United States)

Hooker, John; Denker, Katherine

2014-01-01

Higher education has placed an increasingly greater value on assessment. The Learning Loss Scale may be an appropriate tool to assess learning across disciplines. In this paper, we review the culture of assessment, conceptualizations of cognitive learning, the Learning Loss Scale, and a theoretical explanation, and then we test this measure to…

Semi-supervised eigenvectors for large-scale locally-biased learning

DEFF Research Database (Denmark)

Hansen, Toke Jansen; Mahoney, Michael W.

2014-01-01

improved scaling properties. We provide several empirical examples demonstrating how these semi-supervised eigenvectors can be used to perform locally-biased learning; and we discuss the relationship between our results and recent machine learning algorithms that use global eigenvectors of the graph......In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks nearby that prespecified target region. For example, one might......-based machine learning and data analysis tools. At root, the reason is that eigenvectors are inherently global quantities, thus limiting the applicability of eigenvector-based methods in situations where one is interested in very local properties of the data. In this paper, we address this issue by providing...

NCS-1 dependent learning bonus and behavior outputs of self-directed exploration

Science.gov (United States)

Mun, Ho-Suk

Animals explore a new environment and learn about their surroundings. "Exploration" refers to all activities that increase the information obtained from an animal. For this study, I determined a molecule that mediates self-directed exploration, with a particular focus on rearing behavior and vocalization. Rearing can be either self-directed exploration or escape-oriented exploration. Self-directed exploration can be driven by the desire to gather information about environments while escape-oriented exploration can be driven by fear or anxiety. To differentiate between these two concepts, I compared rearing and other behaviors in three different conditions 1) novel dim (safe environment), which induces exploration based rearing; 2) novel bright (fearful environment), which elicits fear driven rearing; and 3) familiar environment as a control. First, I characterized the effects on two distinct types of environment in exploratory behavior and its effect on learning. From this, I determined that self-directed exploration enhances spatial learning while escape-oriented exploration does not produce a learning bonus. Second, I found that NCS-1 is involved in exploration, as well as learning and memory, by testing mice with reduced levels of Ncs-1 by point mutation and also siRNA injection. Finally, I illustrated other behavior outputs and neural substrate activities, which co-occurred during either self-directed or escape-oriented exploration. I found that high-frequency ultrasonic vocalizations occurred during self-directed exploration while low-frequency calls were emitted during escape-oriented exploration. Also, with immediate early gene imaging techniques, I found hippocampus and nucleus accumbens activation in self-directed exploration. This study is the first comprehensive molecular analysis of learning bonus in self-directed exploration. These results may be beneficial for studying underlying mechanisms of neuropsychiatric disease, and also reveal therapeutic

Vicarious trial-and-error behavior and hippocampal cytochrome oxidase activity during Y-maze discrimination learning in the rat.

Science.gov (United States)

Hu, Dan; Xu, Xiaojuan; Gonzalez-Lima, Francisco

2006-03-01

The present study investigated whether more vicarious trial-and-error (VTE) behavior, defined by head movement from one stimulus to another at a choice point during simultaneous discriminations, led to better visual discrimination learning in a Y-maze, and whether VTE behavior was a function of the hippocampus by measuring regional brain cytochrome oxidase (C.O.) activity, an index of neuronal metabolic activity. The results showed that the more VTEs a rat made, the better the rat learned the visual discrimination. Furthermore, both learning and VTE behavior during learning were correlated to C.O. activity in the hippocampus, suggesting that the hippocampus plays a role in VTE behavior during discrimination learning.

Self-Regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison between Professional Training and English Learning

Science.gov (United States)

Tseng, Min-chen; Chen, Chia-cheng

2017-01-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between…

Mirror neuron system and observational learning: behavioral and neurophysiological evidence.

Science.gov (United States)

Lago-Rodriguez, Angel; Lopez-Alonso, Virginia; Fernández-del-Olmo, Miguel

2013-07-01

Three experiments were performed to study observational learning using behavioral, perceptual, and neurophysiological data. Experiment 1 investigated whether observing an execution model, during physical practice of a transitive task that only presented one execution strategy, led to performance improvements compared with physical practice alone. Experiment 2 investigated whether performing an observational learning protocol improves subjects' action perception. In experiment 3 we evaluated whether the type of practice performed determined the activation of the Mirror Neuron System during action observation. Results showed that, compared with physical practice, observing an execution model during a task that only showed one execution strategy does not provide behavioral benefits. However, an observational learning protocol allows subjects to predict more precisely the outcome of the learned task. Finally, intersperse observation of an execution model with physical practice results in changes of primary motor cortex activity during the observation of the motor pattern previously practiced, whereas modulations in the connectivity between primary and non primary motor areas (PMv-M1; PPC-M1) were not affected by the practice protocol performed by the observer. Copyright © 2013 Elsevier B.V. All rights reserved.

Geometric scaling behavior of the scattering amplitude for DIS with nuclei

Science.gov (United States)

Kormilitzin, Andrey; Levin, Eugene; Tapia, Sebastian

2011-12-01

The main question, that we answer in this paper, is whether the initial condition can influence on the geometric scaling behavior of the amplitude for DIS at high energy. We re-write the non-linear Balitsky-Kovchegov equation in the form which is useful for treating the interaction with nuclei. Using the simplified BFKL kernel, we find the analytical solution to this equation with the initial condition given by the McLerran-Venugopalan formula. This solution does not show the geometric scaling behavior of the amplitude deeply in the saturation region. On the other hand, the BFKL Pomeron calculus with the initial condition at x=1/mR given by the solution to Balitsky-Kovchegov equation, leads to the geometric scaling behavior. The McLerran-Venugopalan formula is the natural initial condition for the Color Glass Condensate (CGC) approach. Therefore, our result gives a possibility to check experimentally which approach: CGC or BFKL Pomeron calculus, is more satisfactory.

Geometric scaling behavior of the scattering amplitude for DIS with nuclei

International Nuclear Information System (INIS)

Kormilitzin, Andrey; Levin, Eugene; Tapia, Sebastian

2011-01-01

The main question, that we answer in this paper, is whether the initial condition can influence on the geometric scaling behavior of the amplitude for DIS at high energy. We re-write the non-linear Balitsky–Kovchegov equation in the form which is useful for treating the interaction with nuclei. Using the simplified BFKL kernel, we find the analytical solution to this equation with the initial condition given by the McLerran–Venugopalan formula. This solution does not show the geometric scaling behavior of the amplitude deeply in the saturation region. On the other hand, the BFKL Pomeron calculus with the initial condition at x A =1/mR A given by the solution to Balitsky–Kovchegov equation, leads to the geometric scaling behavior. The McLerran–Venugopalan formula is the natural initial condition for the Color Glass Condensate (CGC) approach. Therefore, our result gives a possibility to check experimentally which approach: CGC or BFKL Pomeron calculus, is more satisfactory.

RHEOLOGY AND SCALING BEHAVIOR OF SWELLING CLAY DISPERSIONS

Directory of Open Access Journals (Sweden)

S. Chaoui

2015-07-01

Full Text Available The microstructure and scaling of rheological properties of colloidal gels of bentonite investigated as a function of volume fraction and strength of interparticle interaction over a range of volume fractions, elastic modulus is well described with a scaling law functions of volume fractions, while the role of interparticle attractions can be accounted for by expressing these rheological properties as (f/fg-1n, where fg captures the strength of particle interaction and n the microstructure. The scaling variable (fp/fpc-1, suggested in percolation theory to describe rheological behavior near percolation transition, acts to collapse G’ data suggesting that along lines of constant (f/fg-1 these gels are rheologically identical.

RHEOLOGY AND SCALING BEHAVIOR OF SWELLING CLAY DISPERSIONS

Directory of Open Access Journals (Sweden)

S. CHAOUI

2012-12-01

Full Text Available The microstructure and scaling of rheological properties of colloidal gels of bentonite investigated as a function of volume fraction and strength of interparticle interaction over a range of volume fractions, elastic modulus is well described with a scaling law functions of volume fractions, while the role of interparticle attractions can be accounted for by expressing these rheological properties as (/g-1n, where g captures the strength of particle interaction and n the microstructure.The scaling variable (p/pc-1, suggested in percolation theory to describe rheological behavior near percolation transition, acts to collapse G’ data suggesting that along lines of constant (/g-1 these gels are rheologically identical.

Evaluation of the Problem Behavior Frequency Scale-Teacher Report Form for Assessing Behavior in a Sample of Urban Adolescents.

Science.gov (United States)

Farrell, Albert D; Goncy, Elizabeth A; Sullivan, Terri N; Thompson, Erin L

2018-02-01

This study evaluated the structure and validity of the Problem Behavior Frequency Scale-Teacher Report Form (PBFS-TR) for assessing students' frequency of specific forms of aggression and victimization, and positive behavior. Analyses were conducted on two waves of data from 727 students from two urban middle schools (Sample 1) who were rated by their teachers on the PBFS-TR and the Social Skills Improvement System (SSIS), and on data collected from 1,740 students from three urban middle schools (Sample 2) for whom data on both the teacher and student report version of the PBFS were obtained. Confirmatory factor analyses supported first-order factors representing 3 forms of aggression (physical, verbal, and relational), 3 forms of victimization (physical, verbal and relational), and 2 forms of positive behavior (prosocial behavior and effective nonviolent behavior), and higher-order factors representing aggression, victimization, and positive behavior. Strong measurement invariance was established over gender, grade, intervention condition, and time. Support for convergent validity was found based on correlations between corresponding scales on the PBFS-TR and teacher ratings on the SSIS in Sample 1. Significant correlations were also found between teacher ratings on the PBFS-TR and student ratings of their behavior on the Problem Behavior Frequency Scale-Adolescent Report (PBFS-AR) and a measure of nonviolent behavioral intentions in Sample 2. Overall the findings provided support for the PBFS-TR and suggested that teachers can provide useful data on students' aggressive and prosocial behavior and victimization experiences within the school setting. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The combustion behavior of large scale lithium titanate battery

Science.gov (United States)

Huang, Peifeng; Wang, Qingsong; Li, Ke; Ping, Ping; Sun, Jinhua

2015-01-01

Safety problem is always a big obstacle for lithium battery marching to large scale application. However, the knowledge on the battery combustion behavior is limited. To investigate the combustion behavior of large scale lithium battery, three 50 Ah Li(NixCoyMnz)O2/Li4Ti5O12 batteries under different state of charge (SOC) were heated to fire. The flame size variation is depicted to analyze the combustion behavior directly. The mass loss rate, temperature and heat release rate are used to analyze the combustion behavior in reaction way deeply. Based on the phenomenon, the combustion process is divided into three basic stages, even more complicated at higher SOC with sudden smoke flow ejected. The reason is that a phase change occurs in Li(NixCoyMnz)O2 material from layer structure to spinel structure. The critical temperatures of ignition are at 112–121°C on anode tab and 139 to 147°C on upper surface for all cells. But the heating time and combustion time become shorter with the ascending of SOC. The results indicate that the battery fire hazard increases with the SOC. It is analyzed that the internal short and the Li+ distribution are the main causes that lead to the difference. PMID:25586064

Sex differences in vicarious trial-and-error behavior during radial arm maze learning.

Science.gov (United States)

Bimonte, H A; Denenberg, V H

2000-02-01

We investigated sex differences in VTE behavior in rats during radial arm maze learning. Females made more VTEs than males, although there were no sex differences in learning. Further, VTEs and errors were positively correlated during the latter testing sessions in females, but not in males. This sex difference may be a reflection of differences between the sexes in conflict behavior or cognitive strategy while solving the maze.

Scaling behavior in first-order quark-hadron phase transition

International Nuclear Information System (INIS)

Hwa, R.C.

1994-01-01

It is shown that in the Ginzburg-Landau description of first-order quark-hadron phase transition the normalized factorial moments exhibit scaling behavior. The scaling exponent ν depends on only one effective parameter g, which characterizes the strength of the transition. For a strong first-order transition, we find ν=1.45. For weak transition it is 1.30 in agreement with the earlier result on second-order transition

Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects

International Nuclear Information System (INIS)

Yu, C.F.; van Sark, W.G.J.H.M.; Alsema, E.A.

2011-01-01

In a large number of energy models, the use of learning curves for estimating technological improvements has become popular. This is based on the assumption that technological development can be monitored by following cost development as a function of market size. However, recent data show that in some stages of photovoltaic technology (PV) production, the market price of PV modules stabilizes even though the cumulative capacity increases. This implies that no technological improvement takes place in these periods: the cost predicted by the learning curve in the PV study is lower than the market one. We propose that this bias results from ignoring the effects of input prices and scale effects, and that incorporating the input prices and scale effects into the learning curve theory is an important issue in making cost predictions more reliable. In this paper, a methodology is described to incorporate the scale and input-prices effect as the additional variables into the one factor learning curve, which leads to the definition of the multi-factor learning curve. This multi-factor learning curve is not only derived from economic theories, but also supported by an empirical study. The results clearly show that input prices and scale effects are to be included, and that, although market prices are stabilizing, learning is still taking place. (author)

The Culture of Academic Medicine: Faculty Behaviors Impacting the Learning Environment.

Science.gov (United States)

Moutier, Christine; Wingard, Deborah; Gudea, Monica; Jeste, Dilip; Goodman, Seneca; Reznik, Vivian

2016-12-01

The culture of academic medical institutions impacts trainee education, among many other faculty and patient outcomes. Disrespectful behavior by faculty is one of the most challenging and common problems that, left unattended, disrupts healthy work and learning environments. Conversely, a respectful environment facilitates learning, creates a sense of safety, and rewards professionalism. The authors developed surveys and an intervention in an effort to better understand and improve climate concerns among health sciences faculty at the University of California, San Diego (UCSD), a research-intense, public, academic medical center. An online "climate survey" of all UC San Diego health sciences faculty was conducted in 2011-2012. A strategic campaign to address the behavioral issues identified in the initial survey was subsequently launched. In 2015, the climate was re-evaluated in order to assess the effectiveness of the intervention. A total of 478 faculty members (223 women, 235 men, 35 % of faculty) completed the baseline survey, reporting relatively low levels of observed sexual harassment (7 %). However, faculty reported concerning rates of other disruptive behaviors: derogatory comments (29 %), anger outbursts (25 %), and hostile communication (25 %). Women and mid-level faculty were more likely to report these behavioral concerns than men and junior or senior colleagues. Three years after an institutional strategy was initiated, 729 faculty members (50 % of the faculty) completed a follow-up survey. The 2015 survey results indicate significant improvement in numerous climate factors, including overall respectful behaviors, as well as behaviors related to gender. In order to enhance a culture of respect in the learning environment, institutions can effectively engage academic leaders and faculty at all levels to address disruptive behavior and enhance positive climate factors.

Evidence of Validity of the Job Crafting Behaviors Scale

Directory of Open Access Journals (Sweden)

Renata Silva de Carvalho Chinelato

2015-12-01

Full Text Available AbstractJob crafting behavior refers to the changes made by workers in their job context for adjusting their activities to their preferences. We sought to adapt and collect validity evidences of the Job Crafting Behaviors Scale for the Brazilian context, in a sample of 491 workers, with a mean age of 26.7 years. Factor analysis revealed that the final instrument consisted of three dimensions (increasing structural job resources, increasing social job resources, increasing challenging job demands, which showed good internal consistency indexes. These dimensions showed low or moderate correlations with work engagement, positive psychological capital, positive job affect, and in-role performance. The scale showed evidence of validity, the use of which is recommended for future research on the changes that people make in their jobs.

STDP-based behavior learning on the TriBot robot

Science.gov (United States)

Arena, P.; De Fiore, S.; Patané, L.; Pollino, M.; Ventura, C.

2009-05-01

This paper describes a correlation-based navigation algorithm, based on an unsupervised learning paradigm for spiking neural networks, called Spike Timing Dependent Plasticity (STDP). This algorithm was implemented on a new bio-inspired hybrid mini-robot called TriBot to learn and increase its behavioral capabilities. In fact correlation based algorithms have been found to explain many basic behaviors in simple animals. The main interesting consequence of STDP is that the system is able to learn high-level sensor features, based on a set of basic reflexes, depending on some low-level sensor inputs. TriBot is composed of 3 modules, the first two being identical and inspired by the Whegs hybrid robot. The peculiar characteristics of the robot consists in the innovative shape of the three-spoke appendages that allow to increase stability of the structure. The last module is composed of two standard legs with 3 degrees of freedom each. Thanks to the cooperation among these modules, TriBot is able to face with irregular terrains overcoming potential deadlock situations, to climb high obstacles compared to its size and to manipulate objects. Robot experiments will be reported to demonstrate the potentiality and the effectiveness of the approach.

A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

Science.gov (United States)

Bassett, Danielle S; Mattar, Marcelo G

2017-04-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impact of sequential disorder on the scaling behavior of airplane boarding time

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Baek, Yongjoo; Ha, Meesoon; Jeong, Hawoong

2013-05-01

Airplane boarding process is an example where disorder properties of the system are relevant to the emergence of universality classes. Based on a simple model, we present a systematic analysis of finite-size effects in boarding time, and propose a comprehensive view of the role of sequential disorder in the scaling behavior of boarding time against the plane size. Using numerical simulations and mathematical arguments, we find how the scaling behavior depends on the number of seat columns and the range of sequential disorder. Our results show that new scaling exponents can arise as disorder is localized to varying extents.

Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control.

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Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms.

[Scale of organizational learning in schools. Organizational learning is a key element for the development of organizations].

Science.gov (United States)

López, Verónica; Ahumada, Luis; Olivares, Rodrigo; González, Alvaro

2012-05-01

Organizational learning is a key element for the development of organizations. School organizations are not exempt from this challenge and they currently face a highly dynamic and demanding context of education policies that emphasize the school's ability to learn. Thus, research on organizational learning in educational contexts requires valid instruments that are sensitive to the specifics of schools as organizations. In this study, we adapted and validated a scale of organizational learning in a sample of 119 Chilean municipal schools (N= 1,545). The results suggest a structural model made up of three factors: culture of learning, strategic clarity, and group learning. These factors predicted dimensions of educational achievement, as measured through the National Assessment System of Educational Achievement (SNED). Results are discussed in view of the literature on school improvement.

Overcoming Deception in Evolution of Cognitive Behaviors

DEFF Research Database (Denmark)

Lehman, Joel; Miikkulainen, Risto

2014-01-01

When scaling neuroevolution to complex behaviors, cognitive capabilities such as learning, communication, and memory become increasingly important. However, successfully evolving such cognitive abilities remains difficult. This paper argues that a main cause for such difficulty is deception, i.......e. evolution converges to a behavior unrelated to the desired solution. More specifically, cognitive behaviors often require accumulating neural structure that provides no immediate fitness benefit, and evolution often thus converges to non-cognitive solutions. To investigate this hypothesis, a common...... evolutionary robotics T-Maze domain is adapted in three separate ways to require agents to communicate, remember, and learn. Indicative of deception, evolution driven by objective-based fitness often converges upon simple non- cognitive behaviors. In contrast, evolution driven to explore novel behaviors, i...

Ubiquitous learning model using interactive internet messenger group (IIMG) to improve engagement and behavior for smart campus

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Umam, K.; Mardi, S. N. S.; Hariadi, M.

2017-01-01

The recent popularity of internet messenger based smartphone technologies has motivated some university lecturers to use them for educational activities. These technologies have enormous potential to enhance the teaching and ubiquitous learning experience for smart campus development. However, the design ubiquitous learning model using interactive internet messenger group (IIMG) and empirical evidence that would favor a broad application of mobile and ubiquitous learning in smart campus settings to improve engagement and behavior is still limited. In addition, the expectation that mobile learning could improve engagement and behavior on smart campus cannot be confirmed because the majority of the reviewed studies followed instructions paradigms. This article aims to present ubiquitous learning model design and showing learners’ experiences in improved engagement and behavior using IIMG for learner-learner and learner-lecturer interactions. The method applied in this paper includes design process and quantitative analysis techniques, with the purpose of identifying scenarios of ubiquitous learning and realize the impressions of learners and lecturers about engagement and behavior aspect, and its contribution to learning.

The causes of variation in learning and behavior: Why individual differences matter

Directory of Open Access Journals (Sweden)

Bruno eSauce

2013-07-01

Full Text Available In a seminal paper written five decades ago, Cronbach discussed the two highly distinct approaches to scientific psychology: experimental and correlational. Today, although these two approaches are fruitfully implemented and embraced across some fields of psychology, this synergy is largely absent from other areas, such as in the study of learning and behavior. Both Tolman and Hull, in a rare case of agreement, stated that the correlational approach held little promise for the understanding of behavior. Interestingly, this dismissal of the study of individual differences was absent in the biologically-oriented branches of behavior analysis, namely, behavioral genetics and ethology. Here we propose that the distinction between causation and causes of variation (with its origins in the field of genetics reveal the potential value of the correlational approach in understanding the full complexity of learning and behavior. Although the experimental approach can illuminate the causal variables that modulate learning, the analysis of individual differences can elucidate how much and in which way variables interact to support variations in learning in complex natural environments. For example, understanding that a past experience with a stimulus influences its associability provides little insight into how individual predispositions interact to modulate this influence on associability. In this new light, we discuss examples from studies of individual differences in animals’ performance in the Morris Water Maze and from our own work on individual differences in general intelligence in mice. These studies illustrate that, opposed to what Underwood famously suggested, studies of individual differences can do much more to psychology than merely providing preliminary indications of cause-effect relationships.

Real-time assessment of perioperative behaviors in children and parents: development and validation of the perioperative adult child behavioral interaction scale.

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Sadhasivam, Senthilkumar; Cohen, Lindsey L; Hosu, Liana; Gorman, Kristin L; Wang, Yu; Nick, Todd G; Jou, Jing Fang; Samol, Nancy; Szabova, Alexandra; Hagerman, Nancy; Hein, Elizabeth; Boat, Anne; Varughese, Anna; Kurth, Charles Dean; Willging, J Paul; Gunter, Joel B

2010-04-01

Behavior in response to distressful events during outpatient pediatric surgery can contribute to postoperative maladaptive behaviors, such as temper tantrums, nightmares, bed-wetting, and attention seeking. Currently available perioperative behavioral assessment tools have limited utility in guiding interventions to ameliorate maladaptive behaviors because they cannot be used in real time, are only intended to be used during 1 phase of the experience (e.g., perioperative), or provide only a static assessment of the child (e.g., level of anxiety). A simple, reliable, real-time tool is needed to appropriately identify children and parents whose behaviors in response to distressful events at any point in the perioperative continuum could benefit from timely behavioral intervention. Our specific aims were to (1) refine the Perioperative Adult Child Behavioral Interaction Scale (PACBIS) to improve its reliability in identifying perioperative behaviors and (2) validate the refined PACBIS against several established instruments. The PACBIS was used to assess the perioperative behaviors of 89 children aged 3 to 12 years presenting for adenotonsillectomy and their parents. Assessments using the PACBIS were made during perioperative events likely to prove distressing to children and/or parents (perioperative measurement of blood pressure, induction of anesthesia, and removal of the IV catheter before discharge). Static measurements of perioperative anxiety and behavioral compliance during anesthetic induction were made using the modified Yale Preoperative Anxiety Scale and the Induction Compliance Checklist (ICC). Each event was videotaped for later scoring using the Child-Adult Medical Procedure Interaction Scale-Short Form (CAMPIS-SF) and Observational Scale of Behavioral Distress (OSBD). Interrater reliability using linear weighted kappa (kappa(w)) and multiple validations using Spearman correlation coefficients were analyzed. The PACBIS demonstrated good to excellent

Identifying Dental Anxiety in Children's Drawings and correlating It with Frankl's Behavior Rating Scale.

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Mathur, Jyoti; Diwanji, Amish; Sarvaiya, Bhumi; Sharma, Dipal

2017-01-01

To develop a simple method to assess the level of anxiety by using children's drawings and correlating them with Frankl's behavior rating scale. A total of 178 patients aged of 3 to 14 years were handed out two-page forms which contained three sections on coloring and drawing, along with general information, and Frankl's behavior rating scale for the visit. The three types of drawing exercises given to the patients were geometric copy drawings, coloring a nonthreatening figure, and an empty sheet for freehand drawing. Out of 178 patients, 60 showed definitely positive behavior, 73 exhibited positive behavior, 37 showed negative behavior, and 8 were definitely negative on Frankl's behavior rating scale; 133 children had none or, 1 stress marker and 45 exhibited 2 or 3 stress markers in their drawings. Chi-square (χ 2 ) analysis was done with a 2 × 2 contingency table. Observed χ 2 value was 46.166, which at 1 degree of freedom was much greater than that at 0.995 percentile. Therefore, the result was highly significant. Children requiring specialized behavioral techniques can be identified by the presence of stress markers in their drawings. This nonverbal activity by itself can have an overall positive effect on the behavior displayed in the dental clinic. Mathur J, Diwanji A, Sarvaiya B, Sharma D. Identifying Dental Anxiety in Children's Drawings and correlating It with Frankl's Behavior Rating Scale. Int J Clin Pediatr Dent 2017;10(1):24-28.

A learning theory account of depression.

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Ramnerö, Jonas; Folke, Fredrik; Kanter, Jonathan W

2015-06-11

Learning theory provides a foundation for understanding and deriving treatment principles for impacting a spectrum of functional processes relevant to the construct of depression. While behavioral interventions have been commonplace in the cognitive behavioral tradition, most often conceptualized within a cognitive theoretical framework, recent years have seen renewed interest in more purely behavioral models. These modern learning theory accounts of depression focus on the interchange between behavior and the environment, mainly in terms of lack of reinforcement, extinction of instrumental behavior, and excesses of aversive control, and include a conceptualization of relevant cognitive and emotional variables. These positions, drawn from extensive basic and applied research, cohere with biological theories on reduced reward learning and reward responsiveness and views of depression as a heterogeneous, complex set of disorders. Treatment techniques based on learning theory, often labeled Behavioral Activation (BA) focus on activating the individual in directions that increase contact with potential reinforcers, as defined ideographically with the client. BA is considered an empirically well-established treatment that generalizes well across diverse contexts and populations. The learning theory account is discussed in terms of being a parsimonious model and ground for treatments highly suitable for large scale dissemination. © 2015 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Using Ants, Animal Behavior & the Learning Cycle to Investigate Scientific Processes

Science.gov (United States)

Ligon, Russell A.; Dolezal, Adam G.; Hicks, Michael R.; Butler, Michael W.; Morehouse, Nathan I.; Ganesh, Tirupalavanam G.

2014-01-01

The behavior of animals is an intrinsically fascinating topic for students from a wide array of backgrounds. We describe a learning experience using animal behavior that we created for middle school students as part of a graduate-student outreach program, Graduate Partners in Science Education, at Arizona State University in collaboration with a…

Childhood Fish Consumption and Learning and Behavioral Disorders

Directory of Open Access Journals (Sweden)

Jenny L. Carwile

2016-11-01

Full Text Available Fish is a major source of nutrients critical for brain development during early life. The importance of childhood fish consumption is supported by several studies reporting associations of n-3 polyunsaturated fatty acid (n-3 PUFA supplementation with better behavior and school performance. However, fish may have a different effect than n-3 PUFA alone due to the neurotoxic effects of methylmercury, a frequent contaminant. We investigated associations of childhood fish consumption with learning and behavioral disorders in birth cohort study of the neurotoxic effects of early life exposure to solvent-contaminated drinking water. Childhood (age 7–12 years fish consumption and learning and behavioral problems were reported in self-administered questionnaires (age 23–41 at questionnaire completion. Fish consumption was not meaningfully associated with repeating a grade, tutoring, attending summer school, special class placement, or low educational attainment. However, participants who ate fish several times a week had an elevated odds of Attention Deficit Disorder/Attention Deficit Hyperactivity Disorder (odds ratio: 5.2; 95% confidence interval: 1.5–18 compared to participants who did not eat fish. While these findings generally support the safety of the observed level of fish consumption, the absence of a beneficial effect may be attributed to insufficient fish intake or the choice of relatively low n-3 PUFA fish.

Classroom Behavior Patterns of EMH, LD, and EH Students.

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McKinney, James D.; Forman, Susan G.

1982-01-01

Investigated whether classroom teachers could differentiate among educable mentally handicapped (EMH), learning disabled (LD), and emotionally handicapped (EH) students based on perceptions of classroom behavior patterns. Ratings from classroom behavior inventory scales revealed that EMH students were distinguished by low intelligence, creativity,…

Large-scale machine learning and evaluation platform for real-time traffic surveillance

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Eichel, Justin A.; Mishra, Akshaya; Miller, Nicholas; Jankovic, Nicholas; Thomas, Mohan A.; Abbott, Tyler; Swanson, Douglas; Keller, Joel

2016-09-01

In traffic engineering, vehicle detectors are trained on limited datasets, resulting in poor accuracy when deployed in real-world surveillance applications. Annotating large-scale high-quality datasets is challenging. Typically, these datasets have limited diversity; they do not reflect the real-world operating environment. There is a need for a large-scale, cloud-based positive and negative mining process and a large-scale learning and evaluation system for the application of automatic traffic measurements and classification. The proposed positive and negative mining process addresses the quality of crowd sourced ground truth data through machine learning review and human feedback mechanisms. The proposed learning and evaluation system uses a distributed cloud computing framework to handle data-scaling issues associated with large numbers of samples and a high-dimensional feature space. The system is trained using AdaBoost on 1,000,000 Haar-like features extracted from 70,000 annotated video frames. The trained real-time vehicle detector achieves an accuracy of at least 95% for 1/2 and about 78% for 19/20 of the time when tested on ˜7,500,000 video frames. At the end of 2016, the dataset is expected to have over 1 billion annotated video frames.

Analysis of Learning Behavior in a Flipped Programing Classroom Adopting Problem-Solving Strategies

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Chiang, Tosti Hsu-Cheng

2017-01-01

Programing is difficult for beginners because they need to learn the new language of computers. Developing software, especially complex software, is bound to result in problems, frustration, and the need to think in new ways. Identifying the learning behavior behind programing by way of empirical studies can help beginners learn more easily. In…

Behavioral analysis of differential Hebbian learning in closed-loop systems

DEFF Research Database (Denmark)

Kulvicius, Tomas; Kolodziejski, Christoph; Tamosiunaite, Minija

2010-01-01

Understanding closed loop behavioral systems is a non-trivial problem, especially when they change during learning. Descriptions of closed loop systems in terms of information theory date back to the 1950s, however, there have been only a few attempts which take into account learning, mostly...... measuring information of inputs. In this study we analyze a specific type of closed loop system by looking at the input as well as the output space. For this, we investigate simulated agents that perform differential Hebbian learning (STDP). In the first part we show that analytical solutions can be found...

Extinction of avoidance behavior by safety learning depends on endocannabinoid signaling in the hippocampus.

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Micale, Vincenzo; Stepan, Jens; Jurik, Angela; Pamplona, Fabricio A; Marsch, Rudolph; Drago, Filippo; Eder, Matthias; Wotjak, Carsten T

2017-07-01

The development of exaggerated avoidance behavior is largely responsible for the decreased quality of life in patients suffering from anxiety disorders. Studies using animal models have contributed to the understanding of the neural mechanisms underlying the acquisition of avoidance responses. However, much less is known about its extinction. Here we provide evidence in mice that learning about the safety of an environment (i.e., safety learning) rather than repeated execution of the avoided response in absence of negative consequences (i.e., response extinction) allowed the animals to overcome their avoidance behavior in a step-down avoidance task. This process was context-dependent and could be blocked by pharmacological (3 mg/kg, s.c.; SR141716) or genetic (lack of cannabinoid CB1 receptors in neurons expressing dopamine D1 receptors) inactivation of CB1 receptors. In turn, the endocannabinoid reuptake inhibitor AM404 (3 mg/kg, i.p.) facilitated safety learning in a CB1-dependent manner and attenuated the relapse of avoidance behavior 28 days after conditioning. Safety learning crucially depended on endocannabinoid signaling at level of the hippocampus, since intrahippocampal SR141716 treatment impaired, whereas AM404 facilitated safety learning. Other than AM404, treatment with diazepam (1 mg/kg, i.p.) impaired safety learning. Drug effects on behavior were directly mirrored by drug effects on evoked activity propagation through the hippocampal trisynaptic circuit in brain slices: As revealed by voltage-sensitive dye imaging, diazepam impaired whereas AM404 facilitated activity propagation to CA1 in a CB1-dependent manner. In line with this, systemic AM404 enhanced safety learning-induced expression of Egr1 at level of CA1. Together, our data render it likely that AM404 promotes safety learning by enhancing information flow through the trisynaptic circuit to CA1. Copyright © 2017 Elsevier Ltd. All rights reserved.

From rapid place learning to behavioral performance: a key role for the intermediate hippocampus.

Directory of Open Access Journals (Sweden)

Tobias Bast

2009-04-01

Full Text Available Rapid place encoding by hippocampal neurons, as reflected by place-related firing, has been intensely studied, whereas the substrates that translate hippocampal place codes into behavior have received little attention. A key point relevant to this translation is that hippocampal organization is characterized by functional-anatomical gradients along the septotemporal axis: Whereas the ability of hippocampal neurons to encode accurate place information declines from the septal to temporal end, hippocampal connectivity to prefrontal and subcortical sites that might relate such place information to behavioral-control processes shows an opposite gradient. We examined in rats the impact of selective lesions to relevant parts of the hippocampus on behavioral tests requiring place learning (watermaze procedures and on in vivo electrophysiological models of hippocampal encoding (long-term potentiation [LTP], place cells. We found that the intermediate hippocampus is necessary and largely sufficient for behavioral performance based on rapid place learning. In contrast, a residual septal pole of the hippocampus, although displaying intact electrophysiological indices of rapid information encoding (LTP, precise place-related firing, and rapid remapping, failed to sustain watermaze performance based on rapid place learning. These data highlight the important distinction between hippocampal encoding and the behavioral performance based on such encoding, and suggest that the intermediate hippocampus, where substrates of rapid accurate place encoding converge with links to behavioral control, is critical to translate rapid (one-trial place learning into navigational performance.

Development and Validation of the Elder Learning Barriers Scale Among Older Chinese Adults.

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Wang, Renfeng; De Donder, Liesbeth; De Backer, Free; He, Tao; Van Regenmortel, Sofie; Li, Shihua; Lombaerts, Koen

2017-12-01

This study describes the development and validation of the Elder Learning Barriers (ELB) scale, which seeks to identify the obstacles that affect the level of educational participation of older adults. The process of item pool design and scale development is presented, as well as the testing and scale refinement procedure. The data were collected from a sample of 579 older Chinese adults (aged over 55) in the Xi'an region of China. After randomly splitting the sample for cross-validation purposes, the construct validity of the ELB scale was confirmed containing five dimensions: dispositional, informational, physical, situational, and institutional barriers. Furthermore, developmental differences in factor structure have been examined among older age groups. The results indicated that the scale demonstrated good reliability and validity. We conclude in general that the ELB scale appears to be a valuable instrument for examining the learning barriers that older Chinese citizens experience for participating in organized educational activities.

Facilitating Effective Digital Game-Based Learning Behaviors and Learning Performances of Students Based on a Collaborative Knowledge Construction Strategy

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Sung, Han-Yu; Hwang, Gwo-Jen

2018-01-01

Researchers have recognized the potential of educational computer games in improving students' learning engagement and outcomes; however, facilitating effective learning behaviors during the gaming process remains an important and challenging issue. In this paper, a collaborative knowledge construction strategy was incorporated into an educational…

Schools' mental health services and young children's emotions, behavior, and learning.

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Reback, Randall

2010-01-01

Recent empirical research has found that children's noncognitive skills play a critical role in their own success, young children's behavioral and psychological disorders can severely harm their future outcomes, and disruptive students harm the behavior and learning of their classmates. Yet relatively little is known about wide-scale interventions designed to improve children's behavior and mental health. This is the first nationally representative study of the provision, financing, and impact of school-site mental health services for young children. Elementary school counselors are school employees who provide mental health services to all types of students, typically meeting with students one-on-one or in small groups. Given counselors' nonrandom assignment to schools, it is particularly challenging to estimate the impact of these counselors on student outcomes. First, cross-state differences in policies provide descriptive evidence that students in states with more aggressive elementary counseling policies make greater test score gains and are less likely to report internalizing or externalizing problem behaviors compared to students with similar observed characteristics in similar schools in other states. Next, difference-in-differences estimates exploiting both the timing and the targeted grade levels of states' counseling policy changes provide evidence that elementary counselors substantially influence teachers' perceptions of school climate. The adoption of state-funded counselor subsidies or minimum counselor–student ratios reduces the fraction of teachers reporting that their instruction suffers due to student misbehavior and reduces the fractions reporting problems with students physically fighting each other, cutting class, stealing, or using drugs. These findings imply that there may be substantial public and private benefits derived from providing additional elementary school counselors.

An explorative analysis of the links between learning behavior and change orientation

NARCIS (Netherlands)

Sluis, van der E.C. (Lidewey); Caluwé, L.I.A.; Nistelrooij, van A.T.M.

2005-01-01

The article presents an explorative study on the links between learning behavior and change orientation of individuals. When reading literature on how to develop employees and organizations, it strikes one how less focus there is on learning and change needs of individuals. This paper deals with

The Learning Disabled Adolescent: Eriksonian Psychosocial Development, Self-Concept, and Delinquent Behavior.

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Pickar, Daniel B.; Tori, Christopher D.

1986-01-01

Using a developmental perspective, this study contrasted learning and nonlearning disabled adolescents on three variables: Erikson's stages of psychosocial development; self-concept; and delinquent behavior. The results indicated that the learning disabled subjects, due to years of failing, were unable to develop a sense of industry and…

The use of an active learning approach in a SCALE-UP learning space improves academic performance in undergraduate General Biology.

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Hacisalihoglu, Gokhan; Stephens, Desmond; Johnson, Lewis; Edington, Maurice

2018-01-01

Active learning is a pedagogical approach that involves students engaging in collaborative learning, which enables them to take more responsibility for their learning and improve their critical thinking skills. While prior research examined student performance at majority universities, this study focuses on specifically Historically Black Colleges and Universities (HBCUs) for the first time. Here we present work that focuses on the impact of active learning interventions at Florida A&M University, where we measured the impact of active learning strategies coupled with a SCALE-UP (Student Centered Active Learning Environment with Upside-down Pedagogies) learning environment on student success in General Biology. In biology sections where active learning techniques were employed, students watched online videos and completed specific activities before class covering information previously presented in a traditional lecture format. In-class activities were then carefully planned to reinforce critical concepts and enhance critical thinking skills through active learning techniques such as the one-minute paper, think-pair-share, and the utilization of clickers. Students in the active learning and control groups covered the same topics, took the same summative examinations and completed identical homework sets. In addition, the same instructor taught all of the sections included in this study. Testing demonstrated that these interventions increased learning gains by as much as 16%, and students reported an increase in their positive perceptions of active learning and biology. Overall, our results suggest that active learning approaches coupled with the SCALE-UP environment may provide an added opportunity for student success when compared with the standard modes of instruction in General Biology.

Scaling behavior of individual barkhausen avalanches in nucleation-mediated magnetization reversal processes

Energy Technology Data Exchange (ETDEWEB)

Im, Mi-Young; Fischer, Peter; Kim, Dong-Hyun; Shin, Sung-Chul

2009-11-09

We report the scaling behavior of Barkhausen avalanches along the hysteresis loop of a CoCrPt alloy film with perpendicular magnetic anisotropy for every field step of 200 Oe. Individual Barkhausen avalanches are directly observed via high-resolution soft X-ray microscopy with a spatial resolution of 15 nm. The Barkhausen avalanches exhibit a power-law scaling behavior, where the scaling exponent of the power-law distribution drastically changes from 1 {+-} 0.04 to 1.47 {+-} 0.03 as the applied magnetic field approaches the coercivity of the CoCrPt film. We infer that this is due to the coupling of adjacent domains.

How adolescents learn about risk perception and behavior in regards to alcohol use in light of social learning theory: a qualitative study in Bogotá, Colombia.

Science.gov (United States)

Trujillo, Elena María; Suárez, Daniel Enrique; Lema, Mariana; Londoño, Alicia

2015-02-01

In Colombia, the use of alcohol is one of the main risky behaviors carried out by adolescents, given that alcohol is the principal drug of abuse in this age group. Understanding how adolescents learn about risk and behavior is important in developing effective prevention programs. The Theory of Social learning underlines the importance of social interaction in the learning process. It suggests that learning can occur in three ways: a live model in which a person is enacting the desired behavior, verbal instruction when the desired behavior is described, and symbolic learning in which modeling occurs by influence of the media. This study explores these three forms of learning in the perception of risk and behavior related to the use of alcohol in a group of students between 12 and 14 years of age in Bogotá, Colombia. This is a qualitative research study, which is part of a larger study exploring the social representations of risk and alcohol use in adolescents and their communities. The sample group included 160 students from two middle schools (7th and 8th graders) in Bogotá, Colombia. Six sessions of participant observation, 12 semi-structured interviews, and 12 focus group discussions were conducted for data collection. Data were analyzed using the Atlas ti software (V7.0) (ATLAS.ti Scientific Software Development GmbH, London, UK), and categories of analysis were developed using a framework analysis approach. Adolescents can identify several risks related to the use of alcohol, which for the most part, appear to have been learned through verbal instruction. However, this risk recognition does not appear to correlate with their behavior. Parental modeling and messages conveyed by the media represent two other significant sources of learning that are constantly contradicting the messages relayed through verbal instruction and correlate to a greater extent with adolescent behavior. The three different forms of learning described by Social Learning Theory play a

Behavioral Ethics in Practice: Integrating Service Learning into a Graduate Business Ethics Course

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O'Brien, Kevin; Wittmer, Dennis; Ebrahimi, Bahman Paul

2017-01-01

Adopting a broad definition that distinguishes behavioral ethics as science and behavioral ethics in practice, we describe how service learning can be a meaningful component of a four-credit, one-quarter graduate business ethics course by blending both normative/prescriptive and behavioral/descriptive ethics. We provide a conceptual and…

Use of Peer Tutoring, Cooperative Learning, and Collaborative Learning: Implications for Reducing Anti-Social Behavior of Schooling Adolescents

Science.gov (United States)

Eskay, M.; Onu, V. C.; Obiyo, N.; Obidoa, M.

2012-01-01

The study investigated the use of peer tutoring, cooperative learning, and collaborative learning as strategies to reduce anti-social behavior among schooling adolescents. The study is a descriptive survey study. The area of study was Nsukka education zone in Enugu State of Nigeria. The sample of the study was 200 teachers randomly sampled from…

Effects of Locus of Control on Behavioral Intention and Learning Performance of Energy Knowledge in Game-Based Learning

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Yang, Jie Chi; Lin, Yi Lung; Liu, Yi-Chun

2017-01-01

Game-based learning has been gradually adopted in energy education as an effective learning tool because digital games have the potential to increase energy literacy and encourage behavior change. However, not every learner can benefit from this support. There is a need to examine how human factors affect learners' reactions to digital games for…

An Adolescent Nutrition Learning Model to Facilitate Behavior Change in Overweight Teens

Science.gov (United States)

Young, Kimberly J.; Ramsay, Samantha A.; Holyoke, Laura B.

2016-01-01

Understanding the process by which adolescents learn about nutrition is necessary for developing tailored education that leads to sustainable behavior change. Teens aged 15-17 participating in an obesity prevention program were interviewed. From the data, three themes emerged and informed development of an adolescent nutrition learning model. The…

Nonverbal cognitive development in children with cochlear implants: relationship between the Mullen Scales of Early Learning and later performance on the Leiter International Performance Scales-Revised.

Science.gov (United States)

Caudle, Susan E; Katzenstein, Jennifer M; Oghalai, John S; Lin, Jerry; Caudle, Donald D

2014-02-01

Methodologically, longitudinal assessment of cognitive development in young children has proven difficult because few measures span infancy through school age. This matter is further complicated when the child presents with a sensory deficit such as hearing loss. Few measures are validated in this population, and children who are evaluated for cochlear implantation are often reevaluated annually. The authors sought to evaluate the predictive validity of subscales of the Mullen Scales of Early Learning (MSEL) on Leiter International Performance Scales-Revised (LIPS-R) Full-Scale IQ scores. To further elucidate the relationship of these two measures, comparisons were also made with the Vineland Adaptive Behavior Scale-Second Edition (VABS), which provides a measure of adaptive functioning across the life span. Participants included 35 children (14 female, 21 male) who were evaluated both as part of the precandidacy process for cochlear implantation using the MSEL and VABS and following implantation with the LIPS-R and VABS. Hierarchical linear regression revealed that the MSEL Visual Reception subdomain score significantly predicted 52% of the variance in LIPS-R Full-Scale IQ scores at follow-up, F(1, 34) = 35.80, p < .0001, R (2) = .52, β = .72. This result suggests that the Visual Reception subscale offers predictive validity of later LIPS-R Full-Scale IQ scores. The VABS was also significantly correlated with cognitive variables at each time point.

Drosophila learn efficient paths to a food source

OpenAIRE

Stewart, James; Lim, Terrence; Claridge-Chang, Adam; Wang, Zhiping; Toh, Alicia; Rahman, Mashiur; Navawongse, Rapeechai; Raczkowska, Marlena; Choudhury, Deepak

2016-01-01

Elucidating the genetic, and neuronal bases for learned behavior is a central problem in neuroscience. A leading system for neurogenetic discovery is the vinegar fly Drosophila melanogaster; fly memory research has identified genes and circuits that mediate aversive and appetitive learning. However, methods to study adaptive food-seeking behavior in this animal have lagged decades behind rodent feeding analysis, largely due to the challenges presented by their small scale. There is currently ...

Rethinking Hearing Aid Fitting by Learning From Behavioral Patterns

DEFF Research Database (Denmark)

Johansen, Benjamin; Petersen, Michael Kai; Pontoppidan, Niels Henrik

2017-01-01

users to remotely enhance auditory focus and attenuate background noise to improve speech intelligibility. N=5, participants changed program settings and adjusted volume on their hearing instruments using their smartphones. We found that individual behavioral patterns affected the usage of the devices....... A significant difference between program usage, and weekdays versus weekends, were found. Users not only changed programs to modify aspects of directionality and noise reduction, but also continuously adjusted the volume. Rethinking hearing instruments as devices that adaptively learn behavioral patterns based...

The Interaction of Motivation, Self-Regulatory Strategies, and Autonomous Learning Behavior in Different Learner Groups

Science.gov (United States)

Kormos, Judit; Csizér, Kata

2014-01-01

Autonomous learning and effective self-regulatory strategies are increasingly important in foreign language learning; without these, students might not be able to exploit learning opportunities outside language classrooms. This study investigated the influence of motivational factors and self-regulatory strategies on autonomous learning behavior.…

The reliability and validity of three questionnaires: The Student Satisfaction and Self-Confidence in Learning Scale, Simulation Design Scale, and Educational Practices Questionnaire.

Science.gov (United States)

Unver, Vesile; Basak, Tulay; Watts, Penni; Gaioso, Vanessa; Moss, Jacqueline; Tastan, Sevinc; Iyigun, Emine; Tosun, Nuran

2017-02-01

The purpose of this study was to adapt the "Student Satisfaction and Self-Confidence in Learning Scale" (SCLS), "Simulation Design Scale" (SDS), and "Educational Practices Questionnaire" (EPQ) developed by Jeffries and Rizzolo into Turkish and establish the reliability and the validity of these translated scales. A sample of 87 nursing students participated in this study. These scales were cross-culturally adapted through a process including translation, comparison with original version, back translation, and pretesting. Construct validity was evaluated by factor analysis, and criterion validity was evaluated using the Perceived Learning Scale, Patient Intervention Self-confidence/Competency Scale, and Educational Belief Scale. Cronbach's alpha values were found as 0.77-0.85 for SCLS, 0.73-0.86 for SDS, and 0.61-0.86 for EPQ. The results of this study show that the Turkish versions of all scales are validated and reliable measurement tools.

Large-Scale Image Analytics Using Deep Learning

Science.gov (United States)

Ganguly, S.; Nemani, R. R.; Basu, S.; Mukhopadhyay, S.; Michaelis, A.; Votava, P.

2014-12-01

High resolution land cover classification maps are needed to increase the accuracy of current Land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) land cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agricultural Imaging Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~100 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. In order to perform image analytics in such a granular system, it is mandatory to devise an intelligent archiving and query system for image retrieval, file structuring, metadata processing and filtering of all available image scenes. Using the Open NASA Earth Exchange (NEX) initiative, which is a partnership with Amazon Web Services (AWS), we have developed an end-to-end architecture for designing the database and the deep belief network (following the distbelief computing model) to solve a grand challenge of scaling this process across quarter million NAIP tiles that cover the entire Continental United States. The

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

Science.gov (United States)

Halloran, John T; Rocke, David M

2018-05-04

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets. We show that by optimizing Percolator's original learning algorithm, l 2 -SVM-MFN, large-scale SVM learning requires nearly only a third of the original runtime. Furthermore, we show that by employing the widely used Trust Region Newton (TRON) algorithm instead of l 2 -SVM-MFN, large-scale Percolator SVM learning is reduced to nearly only a fifth of the original runtime. Importantly, these speedups only affect the speed at which Percolator converges to a global solution and do not alter recalibration performance. The upgraded versions of both l 2 -SVM-MFN and TRON are optimized within the Percolator codebase for multithreaded and single-thread use and are available under Apache license at bitbucket.org/jthalloran/percolator_upgrade .

Health education and multimedia learning: educational psychology and health behavior theory (Part 1).

Science.gov (United States)

Mas, Francisco G Soto; Plass, Jan; Kane, William M; Papenfuss, Richard L

2003-07-01

When health education researchers began to investigate how individuals make decisions related to health and the factors that influence health behaviors, they referred to frameworks shared by educational and learning research. Health education adopted the basic principles of the cognitive revolution, which were instrumental in advancing the field. There is currently a new challenge to confront: the widespread use of new technologies for health education. To better overcome this challenge, educational psychology and instructional technology theory should be considered. Unfortunately, the passion to incorporate new technologies too often overshadows how people learn or, in particular, how people learn through computer technologies. This two-part article explains how educational theory contributed to the early development of health behavior theory, describes the most relevant multimedia learning theories and constructs, and provides recommendations for developing multimedia health education programs and connecting theory and practice.

Neurobehavioral conditions and effects of gender, weight and severity in preterm infants according to the Neonatal Behavioral Assessment Scale

Directory of Open Access Journals (Sweden)

Alicia Álvarez-García

2015-10-01

Full Text Available The increasing number of preterm babies in recent years has raised interest in studying the consequences of prematurity as a risk factor. In the present paper, 30 preterm babies (at 40 weeks of gestational age were assessed using the Neonatal Behavioral Assessment Scale and the results were compared with those of a control group of 28 full term babies. Moreover, the influence of weight, sex and gestational age was analyzed considering the Brazelton results in the preterm group. The preterm group showed significantly lower scores than the control group for 9 of the 28 behavioral items in the Scale and for 2 of the 5 clusters. However, preterm babies performed better in habituation to disturbing stimuli (light and noise during sleep. In relation to the influence of sex, premature girls performed better in the Social-Interactive cluster. The preterm group has lower neurobehavioral conditions than the full term group, probably due to the abrupt interruption of their intrauterine maturation. In contrast, they showed a better ability of habituation, maybe as a consequence of a learning effect due to earlier additional extrauterine exposition.

Fine Scale Baleen Whale Behavior Observed Via Tagging Over Daily Time Scales

Science.gov (United States)

2014-09-30

system to do a comparison between the two. While at Wildlife Computers, I also asked for and they kindly provided a small change in how their MK10...cetacean behavior at intermediate daily time scales. Recent efforts to assess the impacts of sound on marine mammals and to estimate foraging ...efficiency have called for the need to measure daily activity budgets to quantify how much of each day an individual devotes to foraging , resting

Reversal learning as a measure of impulsive and compulsive behavior in addictions.

Science.gov (United States)

Izquierdo, Alicia; Jentsch, J David

2012-01-01

Our ability to measure the cognitive components of complex decision-making across species has greatly facilitated our understanding of its neurobiological mechanisms. One task in particular, reversal learning, has proven valuable in assessing the inhibitory processes that are central to executive control. Reversal learning measures the ability to actively suppress reward-related responding and to disengage from ongoing behavior, phenomena that are biologically and descriptively related to impulsivity and compulsivity. Consequently, reversal learning could index vulnerability for disorders characterized by impulsivity such as proclivity for initial substance abuse as well as the compulsive aspects of dependence. Though we describe common variants and similar tasks, we pay particular attention to discrimination reversal learning, its supporting neural circuitry, neuropharmacology and genetic determinants. We also review the utility of this task in measuring impulsivity and compulsivity in addictions. We restrict our review to instrumental, reward-related reversal learning studies as they are most germane to addiction. The research reviewed here suggests that discrimination reversal learning may be used as a diagnostic tool for investigating the neural mechanisms that mediate impulsive and compulsive aspects of pathological reward-seeking and -taking behaviors. Two interrelated mechanisms are posited for the neuroadaptations in addiction that often translate to poor reversal learning: frontocorticostriatal circuitry dysregulation and poor dopamine (D2 receptor) modulation of this circuitry. These data suggest new approaches to targeting inhibitory control mechanisms in addictions.

2012 THIN FILM AND SMALL SCALE MECHANICAL BEHAVIOR GRS/GRC, JULY 21-27, 2012

Energy Technology Data Exchange (ETDEWEB)

Balk, Thomas

2012-07-27

The mechanical behavior of materials with small dimension(s) is of both fundamental scientific interest and technological relevance. The size effects and novel properties that arise from changes in deformation mechanism have important implications for modern technologies such as thin films for microelectronics and MEMS devices, thermal and tribological coatings, materials for energy production and advanced batteries, etc. The overarching goal of the 2012 Gordon Research Conference on "Thin Film and Small Scale Mechanical Behavior" is to discuss recent studies and future opportunities regarding elastic, plastic and time-dependent deformation, as well as degradation and failure mechanisms such as fatigue, fracture and wear. Specific topics of interest include, but are not limited to: fundamental studies of physical mechanisms governing small-scale mechanical behavior; advances in test techniques for materials at small length scales, such as nanotribology and high-temperature nanoindentation; in-situ mechanical testing and characterization; nanomechanics of battery materials, such as swelling-induced phenomena and chemomechanical behavior; flexible electronics; mechanical properties of graphene and carbon-based materials; mechanical behavior of small-scale biological structures and biomimetic materials. Both experimental and computational work will be included in the oral and poster presentations at this Conference.

Development and Validation of the Transgender Inclusive Behavior Scale (TIBS).

Science.gov (United States)

Kattari, Shanna K; O'Connor, Ashley A; Kattari, Leonardo

2018-01-01

Transgender-inclusive behaviors are actions and communication supporting transgender individuals. Examples include using language not reinforcing the gender binary, asking for and using correct pronouns, creation of spaces that welcome members of the transgender community, and acknowledging cisgender (non-transgender) privilege. A survey was developed measuring this behavior in individuals to examine the impact of transgender-inclusive behavior and the potential effect of interventions on promoting inclusive behavior. Data were collected utilizing an online survey (N = 1,051). The sample was split in half to run two sets of cases in a principal components analysis. Analysis of the full sample showed Cronbach's alpha to be .93 (n = 918). Findings suggest that the Transgender Inclusive Behavior Scale (TIBS) may be a useful instrument for identifying behaviors related to being inclusive of transgender individuals, groups, and communities. It may also be used to measure behavior change before and after transgender-specific educational and behavioral interventions.

Evaluating the Chinese Revised Controlling Behaviors Scale.

Science.gov (United States)

Tiwari, Agnes; Fong, Daniel Yee Tak; Chan, Ko Ling; Yan, Elsie Chau Wai; Lam, Gloria Ling Lee; Tang, Debbie Hoi Ming; Graham-Kevan, Nicola

2015-01-01

The present study evaluated the utility of the Chinese version of the Revised Controlling Behaviors Scale (C-CBS-R) as a measure of controlling behaviors in violent Chinese intimate relationships. Using a mixed-methods approach, in-depth, individual interviews were conducted with 200 Chinese women survivors to elicit qualitative data about their personal experiences of control in intimate relationships. The use of controlling behaviors was also assessed using the C-CBS-R. Interview accounts suggested that the experiences of 91 of the women were consistent with the description of coercive control according to Dutton and Goodman's conceptualization of coercion. Using the split-half validation procedure, a receiver operating characteristics (ROC) curve analysis was conducted with the first half of the sample. The area under the curve (AUC) for using the C-CBS-R to identify high control was .99, and the cutoff score of 1.145 maximized both sensitivity and specificity. Applying the cutoff score to the second half gave a sensitivity of 96% and a specificity of 95%. Overall, the C-CBS-R has demonstrated utility as a measure of controlling behaviors with a cutoff score for distinguishing high from low levels of control in violent Chinese intimate relationships. © The Author(s) 2014.

The role of service-learning in college students' environmental literacy: Content knowledge, attitudes, and behaviors

Science.gov (United States)

Singletary, Joanna Lynn Bush

This study evaluated the relationship of environmental service-learning on environmental literacy in undergraduates. The subjects were 36 undergraduates at a small liberal arts university enrolled in an environmental biology course. To determine the role of environmental service-learning on college students' environmental knowledge, attitudes, behaviors, and environmental literacy, this study utilized concurrent mixed methods approach for qualitative and quantitative analysis. A quasi-experimental repeated measures approach was the design of the quantitative component of the study. Data were collected on attitude, behavior, and content knowledge aspects of environmental literacy as measured by the Environmental Literacy Survey (Kibert, 2000). Hypotheses were tested by independent samples ttests and repeated measures ANOVA. Repeated measures ANOVA conducted on participants' three subscales scores for the Environmental Literacy Survey (attitude, behavior, and knowledge) indicated that students who participated in environmental service-learning scored statistically significantly higher than those that did not initially participate in service-learning. Qualitative data collected in the form of journal reflections and portfolios were evaluated for themes of environmental attitudes or affective statements, environmentally positive behaviors and skills, and ecological content. Quantitative and qualitative data support the positive role of environmental service-learning in the development of environmental literacy in undergraduate students.

Development and testing of the CALDs and CLES+T scales for international nursing students' clinical learning environments.

Science.gov (United States)

Mikkonen, Kristina; Elo, Satu; Miettunen, Jouko; Saarikoski, Mikko; Kääriäinen, Maria

2017-08-01

The purpose of this study was to develop and test the psychometric properties of the new Cultural and Linguistic Diversity scale, which is designed to be used with the newly validated Clinical Learning Environment, Supervision and Nurse Teacher scale for assessing international nursing students' clinical learning environments. In various developed countries, clinical placements are known to present challenges in the professional development of international nursing students. A cross-sectional survey. Data were collected from eight Finnish universities of applied sciences offering nursing degree courses taught in English during 2015-2016. All the relevant students (N = 664) were invited and 50% chose to participate. Of the total data submitted by the participants, 28% were used for scale validation. The construct validity of the two scales was tested by exploratory factor analysis, while their validity with respect to convergence and discriminability was assessed using Spearman's correlation. Construct validation of the Clinical Learning Environment, Supervision and Nurse Teacher scale yielded an eight-factor model with 34 items, while validation of the Cultural and Linguistic Diversity scale yielded a five-factor model with 21 items. A new scale was developed to improve evidence-based mentorship of international nursing students in clinical learning environments. The instrument will be useful to educators seeking to identify factors that affect the learning of international students. © 2017 John Wiley & Sons Ltd.

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle.

Science.gov (United States)

Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C

2017-01-01

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs) . Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle

Science.gov (United States)

Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C.

2017-01-01

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs). Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages. PMID:28883801

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle

Directory of Open Access Journals (Sweden)

Rebeca Cerezo

2017-08-01

Full Text Available Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs. Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques.Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples.Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance.Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.

Locomotion-learning behavior relationship in Caenorhabditis elegans following γ-ray irradiation

International Nuclear Information System (INIS)

Sakashita, Tetsuya; Hamada, Nobuyuki; Suzuki, Michiyo; Kobayashi, Yasuhiko; Ikeda, Daisuke D.; Yanase, Sumino; Ishii, Naoaki

2008-01-01

Learning impairment following ionizing radiation (IR) exposure is an important potential risk in manned space missions. We previously reported the modulatory effects of IR on salt chemotaxis learning in Caenorhabditis elegans. However, little is known about the effects of IR on the functional relationship in the nervous system. In the present study, we investigated the effects of γ-ray exposure on the relationship between locomotion and salt chemotaxis learning behavior. We found that effects of pre-learning irradiation on locomotion were significantly correlated with the salt chemotaxis learning performance, whereas locomotion was not directly related to chemotaxis to NaCl. On the other hand, locomotion was positively correlated with salt chemotaxis of animals which were irradiated during learning, and the correlation disappeared with increasing doses. These results suggest an indirect relationship between locomotion and salt chemotaxis learning in C. elegans, and that IR inhibits the innate relationship between locomotion and chemotaxis, which is related to salt chemotaxis learning conditioning of C. elegans. (author)

Effect of behavior training on learning and memory of young rats with fetal growth restriction

Institute of Scientific and Technical Information of China (English)

Li Xuelan; Gou Wenli; Huang Pu; Li Chunfang; Sun Yunping

2008-01-01

Objective: To investigate the effect of behavior training on the learning and memory of young rats with fetal growth restriction (FGR). Methods: The model of FGR was established by passive smoking method to pregnant rats.The new-born rats were divided into FGR group and normal group, and then randomly subdivided into trained and untrained group respectively. Morris water maze behavior training was performed on postnatal months 2 and 4, then learning and memory abilities of young rats were measured by dark-avoidance testing and step-down testing. Results: In the dark-avoidance and step-down testing, the young rats' performance of FGR group was worse than that of control group, and the trained group was better than the untrained group significantly. Conclusion: FGR young rats have descended learning and memory abilities. Behavior training could improve the young rats' learning and memory abilities, especially for the FGR young rats.

Identifying Learning Behaviors by Contextualizing Differential Sequence Mining with Action Features and Performance Evolution

Science.gov (United States)

Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Our learning-by-teaching environment, Betty's Brain, captures a wealth of data on students' learning interactions as they teach a virtual agent. This paper extends an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs sequence mining techniques to…

The sustainability of improvements from continuing professional development in pharmacy practice and learning behaviors.

Science.gov (United States)

McConnell, Karen J; Delate, Thomas; Newlon, Carey L

2015-04-25

To assess the long-term sustainability of continuing professional development (CPD) training in pharmacy practice and learning behaviors. This was a 3-year posttrial survey of pharmacists who had participated in an unblinded randomized controlled trial of CPD. The online survey assessed participants' perceptions of pharmacy practice, learning behaviors, and sustainability of CPD. Differences between groups on the posttrial survey responses and changes from the trial's follow-up survey to the posttrial survey responses within the intervention group were compared. Of the 91 pharmacists who completed the original trial, 72 (79%) participated in the sustainability survey. Compared to control participants, a higher percentage of intervention participants reported in the sustainability survey that they had utilized the CPD concept (45.7% vs 8.1%) and identified personal learning objectives (68.6% vs 43.2%) during the previous year. Compared to their follow-up survey responses, lower percentages of intervention participants reported identifying personal learning objectives (94.3% vs 68.6%), documenting their learning plan (82.9% vs 22.9%) and participating in learning by doing (42.9% vs 14.3%) in the sustainability survey. In the intervention group, many of the improvements to pharmacy practice items were sustained over the 3-year period but were not significantly different from the control group. Sustainability of a CPD intervention over a 3-year varied. While CPD-trained pharmacists reported utilizing CPD concepts at a higher rate than control pharmacists, their CPD learning behaviors diminished over time.

Reappraising social insect behavior through aversive responsiveness and learning.

Science.gov (United States)

Roussel, Edith; Carcaud, Julie; Sandoz, Jean-Christophe; Giurfa, Martin

2009-01-01

The success of social insects can be in part attributed to their division of labor, which has been explained by a response threshold model. This model posits that individuals differ in their response thresholds to task-associated stimuli, so that individuals with lower thresholds specialize in this task. This model is at odds with findings on honeybee behavior as nectar and pollen foragers exhibit different responsiveness to sucrose, with nectar foragers having higher response thresholds to sucrose concentration. Moreover, it has been suggested that sucrose responsiveness correlates with responsiveness to most if not all other stimuli. If this is the case, explaining task specialization and the origins of division of labor on the basis of differences in response thresholds is difficult. To compare responsiveness to stimuli presenting clear-cut differences in hedonic value and behavioral contexts, we measured appetitive and aversive responsiveness in the same bees in the laboratory. We quantified proboscis extension responses to increasing sucrose concentrations and sting extension responses to electric shocks of increasing voltage. We analyzed the relationship between aversive responsiveness and aversive olfactory conditioning of the sting extension reflex, and determined how this relationship relates to division of labor. Sucrose and shock responsiveness measured in the same bees did not correlate, thus suggesting that they correspond to independent behavioral syndromes, a foraging and a defensive one. Bees which were more responsive to shock learned and memorized better aversive associations. Finally, guards were less responsive than nectar foragers to electric shocks, exhibiting higher tolerance to low voltage shocks. Consequently, foragers, which are more sensitive, were the ones learning and memorizing better in aversive conditioning. Our results constitute the first integrative study on how aversive responsiveness affects learning, memory and social

Reappraising social insect behavior through aversive responsiveness and learning.

Directory of Open Access Journals (Sweden)

Edith Roussel

Full Text Available The success of social insects can be in part attributed to their division of labor, which has been explained by a response threshold model. This model posits that individuals differ in their response thresholds to task-associated stimuli, so that individuals with lower thresholds specialize in this task. This model is at odds with findings on honeybee behavior as nectar and pollen foragers exhibit different responsiveness to sucrose, with nectar foragers having higher response thresholds to sucrose concentration. Moreover, it has been suggested that sucrose responsiveness correlates with responsiveness to most if not all other stimuli. If this is the case, explaining task specialization and the origins of division of labor on the basis of differences in response thresholds is difficult.To compare responsiveness to stimuli presenting clear-cut differences in hedonic value and behavioral contexts, we measured appetitive and aversive responsiveness in the same bees in the laboratory. We quantified proboscis extension responses to increasing sucrose concentrations and sting extension responses to electric shocks of increasing voltage. We analyzed the relationship between aversive responsiveness and aversive olfactory conditioning of the sting extension reflex, and determined how this relationship relates to division of labor.Sucrose and shock responsiveness measured in the same bees did not correlate, thus suggesting that they correspond to independent behavioral syndromes, a foraging and a defensive one. Bees which were more responsive to shock learned and memorized better aversive associations. Finally, guards were less responsive than nectar foragers to electric shocks, exhibiting higher tolerance to low voltage shocks. Consequently, foragers, which are more sensitive, were the ones learning and memorizing better in aversive conditioning.Our results constitute the first integrative study on how aversive responsiveness affects learning, memory and

Individual-Based Compulsive Sexual Behavior Scale: Its Development and Importance in Examining Compulsive Sexual Behavior.

Science.gov (United States)

Efrati, Yaniv; Mikulincer, Mario

2018-04-03

Compulsive sexual behavior comprises individual-based (e.g., sexual fantasies, compulsive sexual thoughts, masturbation) and partnered (e.g., interpersonal sexual conquests, repeated infidelity) facets. Most instruments for assessing compulsive sexual behavior, however, focus less on the individual-based facet and specifically on fantasies and compulsive thoughts. In the current research, we developed and validated an individual-based compulsive sexual behavior scale (I-CSB). In Study 1 (N = 492), the factorial structure of the I-CSB was examined. In Study 2 (N = 406), we assessed I-CSB's convergent validity. In Study 3 (N = 112), we examined whether the I-CSB differentiates between individuals who suffer from compulsive sexual behavior and those who do not. Results revealed a four-factor structure for individual-based compulsive sexual behavior that is associated with an intense inner conflict regarding sexuality (high arousal contrasting with high sexual anxiety), and that accounts for approximately 75% of the differences between people with compulsive sexual behavior and controls. Results are discussed in light of the need for a broader understanding of compulsive sexual behavior.

Middle School Teachers' Expectations of Organizational Behaviors of Students with Learning Disabilities

Science.gov (United States)

McMullen, Rebecca C.; Shippen, Margaret E.; Dangel, Harry L.

2007-01-01

The purpose of this pilot study was to investigate the specific classroom organizational behaviors that middle school inclusive teachers report as expectations for students with learning disabilities. Practicing middle school science and social studies teachers (n = 12) responded to a survey about organization behaviors of students with learning…

Assessing learning process of caring behavior among nursing students in Palembang, Indonesia

Directory of Open Access Journals (Sweden)

Ira Kusumawaty

2016-01-01

Full Text Available Background Caring as the heart of nursing profession should be learned by nursing students. However, in fact, to generate caring professional nurses is not an uncomplicated issue and there are some factors that can influence its achievement. Socio-cognitive theory which emphasizes on interaction between person, behavior, and environment in learning theory was used to assess caring behavior learning process. Objective The aims of the study are to assess characteristics of nursing students, to identify students’ preferences in choosing their profession, to pinpoint students’ perception and educators’ teaching methods used in caring behavior class and to determine students understanding of caring behavior. Methods A descriptive analysis was used to analyze data obtained through surveys and brief interviews.Samples are 232 nursing students from diploma III program (89, 66 and 77 students, respectively students at semester 2, 4 and 6, 3 nurse educators and 3 stakeholders from 2 hospitals, and 1 from organizational profession. Results Majority, of the students are female and, had chosen nursing as the first priority. However, more than 50% of their choice was not based on their preferences, but influenced by family’s desire. There are more students who have less understanding about caring than those who have good understanding. Teaching strategies were varied, but mostly consist of lectures and discussions. There were complaints from stakeholders related to communication, patience, and empathy as a part of caring behavior nurses who graduated with diploma III. Conclusion Nurse educators should provide an extensive understanding of the nursing profession and motivate students from the early semester. Improved motivation is crucially important to enhance students’ caring behavior.

Downscaling Coarse Scale Microwave Soil Moisture Product using Machine Learning

Science.gov (United States)

Abbaszadeh, P.; Moradkhani, H.; Yan, H.

2016-12-01

Soil moisture (SM) is a key variable in partitioning and examining the global water-energy cycle, agricultural planning, and water resource management. It is also strongly coupled with climate change, playing an important role in weather forecasting and drought monitoring and prediction, flood modeling and irrigation management. Although satellite retrievals can provide an unprecedented information of soil moisture at a global-scale, the products might be inadequate for basin scale study or regional assessment. To improve the spatial resolution of SM, this work presents a novel approach based on Machine Learning (ML) technique that allows for downscaling of the satellite soil moisture to fine resolution. For this purpose, the SMAP L-band radiometer SM products were used and conditioned on the Variable Infiltration Capacity (VIC) model prediction to describe the relationship between the coarse and fine scale soil moisture data. The proposed downscaling approach was applied to a western US basin and the products were compared against the available SM data from in-situ gauge stations. The obtained results indicated a great potential of the machine learning technique to derive the fine resolution soil moisture information that is currently used for land data assimilation applications.

Leader-Member Exchange, Learning Orientation and Innovative Work Behavior

Science.gov (United States)

Atitumpong, Aungkhana; Badir, Yuosre F.

2018-01-01

Purpose: This study aims to examine the effects of leader-member exchange (LMX) and employee learning orientation on employee innovative work behavior (IWB) through creative self-efficacy. Design/methodology/approach: Data have been collected from 337 employees and 137 direct managers from manufacturing sector. A hierarchical linear model has been…

Probability Learning: Changes in Behavior across Time and Development

Science.gov (United States)

Plate, Rista C.; Fulvio, Jacqueline M.; Shutts, Kristin; Green, C. Shawn; Pollak, Seth D.

2018-01-01

Individuals track probabilities, such as associations between events in their environments, but less is known about the degree to which experience--within a learning session and over development--influences people's use of incoming probabilistic information to guide behavior in real time. In two experiments, children (4-11 years) and adults…

Roles of Parents and Annotation Sharing in Children's Learning Behavior and Achievement Using E-Readers

Science.gov (United States)

Hwang, Wu-Yuin; Liu, Yi-Fan; Chen, Hon-Ren; Huang, Jian-Wun; Li, Jin-Yi

2015-01-01

Although previous studies have highlighted the advantages of using e-books for learning, most have compared learning achieved with traditional textbooks with that achieved with e-books in a classroom situation. These studies focused on individual learning instead of on interactions among learners, learning behavior using ebooks after school, and…

Chaotic exploration and learning of locomotion behaviors.

Science.gov (United States)

Shim, Yoonsik; Husbands, Phil

2012-08-01

We present a general and fully dynamic neural system, which exploits intrinsic chaotic dynamics, for the real-time goal-directed exploration and learning of the possible locomotion patterns of an articulated robot of an arbitrary morphology in an unknown environment. The controller is modeled as a network of neural oscillators that are initially coupled only through physical embodiment, and goal-directed exploration of coordinated motor patterns is achieved by chaotic search using adaptive bifurcation. The phase space of the indirectly coupled neural-body-environment system contains multiple transient or permanent self-organized dynamics, each of which is a candidate for a locomotion behavior. The adaptive bifurcation enables the system orbit to wander through various phase-coordinated states, using its intrinsic chaotic dynamics as a driving force, and stabilizes on to one of the states matching the given goal criteria. In order to improve the sustainability of useful transient patterns, sensory homeostasis has been introduced, which results in an increased diversity of motor outputs, thus achieving multiscale exploration. A rhythmic pattern discovered by this process is memorized and sustained by changing the wiring between initially disconnected oscillators using an adaptive synchronization method. Our results show that the novel neurorobotic system is able to create and learn multiple locomotion behaviors for a wide range of body configurations and physical environments and can readapt in realtime after sustaining damage.

High-Throughput Automatic Training System for Odor-Based Learned Behaviors in Head-Fixed Mice

Directory of Open Access Journals (Sweden)

Zhe Han

2018-02-01

Full Text Available Understanding neuronal mechanisms of learned behaviors requires efficient behavioral assays. We designed a high-throughput automatic training system (HATS for olfactory behaviors in head-fixed mice. The hardware and software were constructed to enable automatic training with minimal human intervention. The integrated system was composed of customized 3D-printing supporting components, an odor-delivery unit with fast response, Arduino based hardware-controlling and data-acquisition unit. Furthermore, the customized software was designed to enable automatic training in all training phases, including lick-teaching, shaping and learning. Using HATS, we trained mice to perform delayed non-match to sample (DNMS, delayed paired association (DPA, Go/No-go (GNG, and GNG reversal tasks. These tasks probed cognitive functions including sensory discrimination, working memory, decision making and cognitive flexibility. Mice reached stable levels of performance within several days in the tasks. HATS enabled an experimenter to train eight mice simultaneously, therefore greatly enhanced the experimental efficiency. Combined with causal perturbation and activity recording techniques, HATS can greatly facilitate our understanding of the neural-circuitry mechanisms underlying learned behaviors.

On the relationships among work characteristics and learning-related behavior : Does age matter?

NARCIS (Netherlands)

De Lange, Annet H.; Taris, Toon W.; Jansen, Paul; Kompier, Michiel A. J.; Houtman, Irene L. D.; Bongers, Paulien M.

2010-01-01

This 3-wave longitudinal study examined (a) the causal direction of the relationships among psychosocial work characteristics (e.g., job demands, job control, and supervisor support) and indicators of learning-related behavior (e.g., motivation to learn and active problem solving), and (b) whether

2010 Thin Film & Small Scale Mechanical Behavior Gordon Research Conference

Energy Technology Data Exchange (ETDEWEB)

Dr. Thomas Balk

2010-07-30

Over the past decades, it has been well established that the mechanical behavior of materials changes when they are confined geometrically at least in one dimension to small scale. It is the aim of the 2010 Gordon Conference on 'Thin Film and Small Scale Mechanical Behavior' to discuss cutting-edge research on elastic, plastic and time-dependent deformation as well as degradation mechanisms like fracture, fatigue and wear at small scales. As in the past, the conference will benefit from contributions from fundamental studies of physical mechanisms linked to material science and engineering reaching towards application in modern applications ranging from optical and microelectronic devices and nano- or micro-electrical mechanical systems to devices for energy production and storage. The conference will feature entirely new testing methodologies and in situ measurements as well as recent progress in atomistic and micromechanical modeling. Particularly, emerging topics in the area of energy conversion and storage, such as material for batteries will be highlighted. The study of small-scale mechanical phenomena in systems related to energy production, conversion or storage offer an enticing opportunity to materials scientists, who can provide new insight and investigate these phenomena with methods that have not previously been exploited.

Learning Methods for Dynamic Topic Modeling in Automated Behavior Analysis.

Science.gov (United States)

Isupova, Olga; Kuzin, Danil; Mihaylova, Lyudmila

2017-09-27

Semisupervised and unsupervised systems provide operators with invaluable support and can tremendously reduce the operators' load. In the light of the necessity to process large volumes of video data and provide autonomous decisions, this paper proposes new learning algorithms for activity analysis in video. The activities and behaviors are described by a dynamic topic model. Two novel learning algorithms based on the expectation maximization approach and variational Bayes inference are proposed. Theoretical derivations of the posterior estimates of model parameters are given. The designed learning algorithms are compared with the Gibbs sampling inference scheme introduced earlier in the literature. A detailed comparison of the learning algorithms is presented on real video data. We also propose an anomaly localization procedure, elegantly embedded in the topic modeling framework. It is shown that the developed learning algorithms can achieve 95% success rate. The proposed framework can be applied to a number of areas, including transportation systems, security, and surveillance.

Psychometric Testing of Two Chinese-Version Scales on Attitudes Toward and Caregiving Behaviors for End-of-Life Patients and Families.

Science.gov (United States)

Yang, Luke; Liu, Yung-Fang; Sun, Huey-Fang; Chiang, Hsien-Hsien; Tsai, Yu-Lun; Liaw, Jen-Jiuan

2017-03-01

The study purpose was to examine the validities and reliabilities of the Chinese-versions Frommelt Attitudes Toward Care of the Dying Scale (Attitudes Scale) and Caregiving Behaviors Scale for End-of-Life Patients and Families (Behaviors Scale). The scales were tested in a convenience sample of 318 nurses with ≥6 months work experience at three hospitals. Cronbach's alphas of the Attitudes and Behaviors Scales were .90 and .96, respectively. Each scale had Kaiser-Meyer-Olkin index >.85 and Bartlett's test of sphericity >4000 ( p < .001). Attitudes Scale loaded on three factors: respecting and caring for dying patients and families, avoiding care of the dying, and involving patients and families in end-of-life care. The Behaviors Scale loaded on two factors: supporting dying patients and families, and helping families cope with grief. Factor loadings for both scales were ≥.49. Both Attitudes and Behaviors Scales are reliable and valid for evaluating nurses' attitudes and caregiving behaviors for the dying.

[Validity and Reliability of the Korean Version Scale of the Clinical Learning Environment, Supervision and Nurse Teacher Evaluation Scale (CLES+T)].

Science.gov (United States)

Kim, Sun Hee; Yoo, So Yeon; Kim, Yae Young

2018-02-01

This study was conducted to evaluate the validity and reliability of the Korean version of the clinical learning environment, supervision and nurse teacher evaluation scale (CLES+T) that measures the clinical learning environment and the conditions associated with supervision and nurse teachers. The English CLES+T was translated into Korean with forward and back translation. Survey data were collected from 434 nursing students who had more than four days of clinical practice in Korean hospitals. Internal consistency reliability and construct validity using confirmatory and exploratory factor analysis were conducted. SPSS 20.0 and AMOS 22.0 programs were used for data analysis. The exploratory factor analysis revealed seven factors for the thirty three-item scale. Confirmatory factor analysis supported good convergent and discriminant validities. The Cronbach's alpha for the overall scale was .94 and for the seven subscales ranged from .78 to .94. The findings suggest that the 33-items Korean CLES+T is an appropriate instrument to measure Korean nursing students'clinical learning environment with good validity and reliability. © 2018 Korean Society of Nursing Science.

Differential Learning as a Key Training Approach to Improve Creative and Tactical Behavior in Soccer.

Science.gov (United States)

Santos, Sara; Coutinho, Diogo; Gonçalves, Bruno; Schöllhorn, Wolfgang; Sampaio, Jaime; Leite, Nuno

2018-03-01

The aim of this study was to identify the effects of a differential-learning program, embedded in small-sided games, on the creative and tactical behavior of youth soccer players. Forty players from under-13 (U13) and under-15 (U15) were allocated into control and experimental groups and were tested using a randomized pretest to posttest design using small-sided games situations. The experimental group participated in a 5-month differential-learning program embodied in small-sided games situations, while the control group participated in a typical small-sided games training program. In-game creativity was assessed through notational analyses of the creative components, and the players' positional data were used to compute tactical-derived variables. The findings suggested that differential learning facilitated the development of creative components, mainly concerning attempts (U13, small; U15, small), versatility (U13, moderate; U15, small), and originality (U13, unclear; U15, small) of players' actions. Likewise, the differential-learning approach provided a decrease in fails during the game in both experimental groups (moderate). Moreover, differential learning seemed to favor regularity in pitch-positioning behavior for the distance between players' dyads (U13, small; U15, small), the distance to the team target (U13, moderate; U15, small), and the distance to the opponent target (U13, moderate; U15, small). The differential-learning program stressed creative and positional behavior in both age groups with a distinct magnitude of effects, with the U13 players demonstrating higher improvements over the U15 players. Overall, these findings confirmed that the technical variability promoted by differential learning nurtures regularity of positioning behavior.

The reactor trainer: state-of-the-art classroom learning

International Nuclear Information System (INIS)

Stater, R.G.

1996-01-01

The Reactor Trainer is a professional, PC based, graphically enhanced, training resource specifically developed and customized for Class Room teaching of and learning about, reactor behavior. This unique, and focused, learning-target sets The Trainer apart from the panorama of the more common PC plant simulator. Its educational scope extends along a logical learning path, starting with important fundamental behavioral concepts of delayed neutrons, neutron multiplying factors, and reactor rate, moving to simple reactor transients in real time, and culminating with more complex operational evolutions. The Trainer empowers the Instructor with a dynamic Class Room demonstrator and the student with a superior hands-on learning tool. The Trainer's versatility encompasses a wide variety of educational needs, including initial operator training, requalification training, Shift Technical Advisor training, and other advanced or specialized training. In addition, The Reactor Trainer enhances prerequisite preparation of operator candidates for full-scale control room training and, in so doing, PC economics relieves full-scale simulator hours. (author)

A review of the Child and Adolescent Social Support Scale for Healthy Behaviors.

Science.gov (United States)

Cullum, Kristiana G H; Mayo, Ann M

2015-01-01

Assessing an instrument's psychometric properties to determine appropriateness for use can be a challenging process. Dissecting the statistical terminology may be even more perplexing. There are several instruments that evaluate adolescents' perceived social support, but a fairly new instrument related to this construct assesses not only the availability of social support but also support for healthy behaviors in this population. The Child and Adolescent Social Support Scale for Healthy Behaviors, first published in 2013, demonstrates adequate initial reliability and validity. The purpose of this article is to review the psychometric properties of the Child and Adolescent Social Support Scale for Healthy Behaviors and potential uses of the instrument.

Construct Validation of the Behavior and Instructional Management Scale

Science.gov (United States)

Martin, Nancy K.; Sass, Daniel A.

2010-01-01

Beliefs related to classroom management vary among teachers and play an important role in classrooms. Despite the importance of this construct, valid measures have proven difficult to develop. This study evaluated the psychometric properties of the Behavior and Instructional Management Scale (BIMS), a short but valid measure of teachers'…

Creating a brief rating scale for the assessment of learning disabilities using reliability and true score estimates of the scale's items based on the Rasch model.

Science.gov (United States)

Sideridis, Georgios; Padeliadu, Susana

2013-01-01

The purpose of the present studies was to provide the means to create brief versions of instruments that can aid the diagnosis and classification of students with learning disabilities and comorbid disorders (e.g., attention-deficit/hyperactivity disorder). A sample of 1,108 students with and without a diagnosis of learning disabilities took part in study 1. Using information from modern theory methods (i.e., the Rasch model), a scale was created that included fewer than one third of the original battery items designed to assess reading skills. This best item synthesis was then evaluated for its predictive and criterion validity with a valid external reading battery (study 2). Using a sample of 232 students with and without learning disabilities, results indicated that the brief version of the scale was equally effective as the original scale in predicting reading achievement. Analysis of the content of the brief scale indicated that the best item synthesis involved items from cognition, motivation, strategy use, and advanced reading skills. It is suggested that multiple psychometric criteria be employed in evaluating the psychometric adequacy of scales used for the assessment and identification of learning disabilities and comorbid disorders.

Reversal learning and resurgence of operant behavior in zebrafish (Danio rerio).

Science.gov (United States)

Kuroda, Toshikazu; Mizutani, Yuto; Cançado, Carlos R X; Podlesnik, Christopher A

2017-09-01

Zebrafish are used extensively as vertebrate animal models in biomedical research for having such features as a fully sequenced genome and transparent embryo. Yet, operant-conditioning studies with this species are scarce. The present study investigated reversal learning and resurgence of operant behavior in zebrafish. A target response (approaching a sensor) was reinforced in Phase 1. In Phase 2, the target response was extinguished while reinforcing an alternative response (approaching a different sensor). In Phase 3, extinction was in effect for the target and alternative responses. Reversal learning was demonstrated when responding tracked contingency changes between Phases 1 and 2. Moreover, resurgence occurred in 10 of 13 fish in Phase 3: Target response rates increased transiently and exceeded rates of an unreinforced control response. The present study provides the first evidence with zebrafish supporting reversal learning between discrete operant responses and a laboratory model of relapse. These findings open the possibility to assessing genetic influences of operant behavior generally and in models of relapse (e.g., resurgence, renewal, reinstatement). Copyright © 2017 Elsevier B.V. All rights reserved.

Characterizing multi-scale self-similar behavior and non-statistical properties of fluctuations in financial time series

Science.gov (United States)

Ghosh, Sayantan; Manimaran, P.; Panigrahi, Prasanta K.

2011-11-01

We make use of wavelet transform to study the multi-scale, self-similar behavior and deviations thereof, in the stock prices of large companies, belonging to different economic sectors. The stock market returns exhibit multi-fractal characteristics, with some of the companies showing deviations at small and large scales. The fact that, the wavelets belonging to the Daubechies’ (Db) basis enables one to isolate local polynomial trends of different degrees, plays the key role in isolating fluctuations at different scales. One of the primary motivations of this work is to study the emergence of the k-3 behavior [X. Gabaix, P. Gopikrishnan, V. Plerou, H. Stanley, A theory of power law distributions in financial market fluctuations, Nature 423 (2003) 267-270] of the fluctuations starting with high frequency fluctuations. We make use of Db4 and Db6 basis sets to respectively isolate local linear and quadratic trends at different scales in order to study the statistical characteristics of these financial time series. The fluctuations reveal fat tail non-Gaussian behavior, unstable periodic modulations, at finer scales, from which the characteristic k-3 power law behavior emerges at sufficiently large scales. We further identify stable periodic behavior through the continuous Morlet wavelet.

Low-Back Pain Patients Learn to Adapt Motor Behavior with Adverse Secondary Consequences

NARCIS (Netherlands)

van Dieën, Jaap H.; Flor, Herta; Hodges, Paul W.

2017-01-01

ABSTRACT: We hypothesize that changes in motor behavior in individuals with low-back pain are adaptations aimed at minimizing the real or perceived risk of further pain. Through reinforcement learning, pain and subsequent adaptions result in less dynamic motor behavior, leading to increased loading

Modeling individuals’ cognitive and affective responses in spatial learning behavior

NARCIS (Netherlands)

Han, Q.; Arentze, T.A.; Timmermans, H.J.P.; Janssens, D.; Wets, G.; Lo, H.P.; Leung, Stephen C.H.; Tan, Susanna M.L.

2008-01-01

Activity-based analysis has slowly shifted gear from analysis of daily activity patterns to analysis and modeling of dynamic activity-travel patterns. In this paper, we describe a dynamic model that is concerned with simulating cognitive and affective responses in spatial learning behavior for a

The Large Scale Machine Learning in an Artificial Society: Prediction of the Ebola Outbreak in Beijing

Directory of Open Access Journals (Sweden)

Peng Zhang

2015-01-01

Full Text Available Ebola virus disease (EVD distinguishes its feature as high infectivity and mortality. Thus, it is urgent for governments to draw up emergency plans against Ebola. However, it is hard to predict the possible epidemic situations in practice. Luckily, in recent years, computational experiments based on artificial society appeared, providing a new approach to study the propagation of EVD and analyze the corresponding interventions. Therefore, the rationality of artificial society is the key to the accuracy and reliability of experiment results. Individuals’ behaviors along with travel mode directly affect the propagation among individuals. Firstly, artificial Beijing is reconstructed based on geodemographics and machine learning is involved to optimize individuals’ behaviors. Meanwhile, Ebola course model and propagation model are built, according to the parameters in West Africa. Subsequently, propagation mechanism of EVD is analyzed, epidemic scenario is predicted, and corresponding interventions are presented. Finally, by simulating the emergency responses of Chinese government, the conclusion is finally drawn that Ebola is impossible to outbreak in large scale in the city of Beijing.

Psychometric Properties of the Dietary Salt Reduction Self-Care Behavior Scale.

Science.gov (United States)

Srikan, Pratsani; Phillips, Kenneth D

2014-07-01

Valid, reliable, and culturally-specific scales to measure salt reduction self-care behavior in older adults are needed. The purpose of this study was to develop the Dietary Salt Reduction Self-Care Behavior Scale (DSR-SCB) for use in hypertensive older adults with Orem's self-care deficit theory as a base. Exploratory factor analysis, Rasch modeling, and reliability were performed on data from 242 older Thai adults. Nine items loaded on one factor (factor loadings = 0.63 to 0.79) and accounted for 52.28% of the variance (Eigenvalue = 4.71). The Kaiser-Meyer-Olkin method of sampling adequacy was 0.89, and the Bartlett's test showed significance (χ 2 ( df =36 ) = 916.48, p < 0.0001). Infit and outfit mean squares ranged from 0.81 to 1.25, while infit and outfit standardized mean squares were located at ±2. Cronbach's alpha was 0.88. The 9-item DSR-SCB is a short and reliable scale. © The Author(s) 2014.

Combining agreement and frequency rating scales to optimize psychometrics in measuring behavioral health functioning.

Science.gov (United States)

Marfeo, Elizabeth E; Ni, Pengsheng; Chan, Leighton; Rasch, Elizabeth K; Jette, Alan M

2014-07-01

The goal of this article was to investigate optimal functioning of using frequency vs. agreement rating scales in two subdomains of the newly developed Work Disability Functional Assessment Battery: the Mood & Emotions and Behavioral Control scales. A psychometric study comparing rating scale performance embedded in a cross-sectional survey used for developing a new instrument to measure behavioral health functioning among adults applying for disability benefits in the United States was performed. Within the sample of 1,017 respondents, the range of response category endorsement was similar for both frequency and agreement item types for both scales. There were fewer missing values in the frequency items than the agreement items. Both frequency and agreement items showed acceptable reliability. The frequency items demonstrated optimal effectiveness around the mean ± 1-2 standard deviation score range; the agreement items performed better at the extreme score ranges. Findings suggest an optimal response format requires a mix of both agreement-based and frequency-based items. Frequency items perform better in the normal range of responses, capturing specific behaviors, reactions, or situations that may elicit a specific response. Agreement items do better for those whose scores are more extreme and capture subjective content related to general attitudes, behaviors, or feelings of work-related behavioral health functioning. Copyright © 2014 Elsevier Inc. All rights reserved.

A Driver Behavior Learning Framework for Enhancing Traffic Simulation

Directory of Open Access Journals (Sweden)

Ramona Maria Paven

2014-06-01

Full Text Available Traffic simulation provides an essential support for developing intelligent transportation systems. It allows affordable validation of such systems using a large variety of scenarios that involves massive data input. However, realistic traffic models are hard to be implemented especially for microscopic traffic simulation. One of the hardest problems in this context is to model the behavior of drivers, due the complexity of human nature. The work presented in this paper proposes a framework for learning driver behavior based on a Hidden Markov Model technique. Moreover, we propose also a practical method to inject this behavior in a traffic model used by the SUMO traffic simulator. To demonstrate the effectiveness of this method we present a case study involving real traffic collected from Timisoara city area.

Construction of scales to measure leadership behavior at nuclear power plants. 1

International Nuclear Information System (INIS)

Misumi, Jyuji; Yamada, Akira; Shinohara, Shinobu

1994-01-01

In order to construct scales to measure leadership behavior of managers and supervisors at nuclear power plants, we prepared questionnaire covering all the leadership behaviors of leaders and then had their subordinates fill out the questionnaire. We selected questionnaire items for use in measuring leadership behaviors, analyzing the responses by means of factor analysis, etc. For the section chiefs, five factors were named, i.e., 'consideration' and 'self-righteousness' that belong to group maintenance behavior and 'thorough dissemination of information', 'specialty, planning' and 'pressure' that belong to goal achievement behavior. For the maintenance subsection chiefs were found seven factors, i.e., 'example setting', 'appropriate handling of work', 'planning', 'rigidity', 'educational guidance' that belong to goal achievement behavior and 'consideration for work' and 'personal consideration' that belong to group maintenance behavior. For maintenance and repair foremen were named six factors, i.e., 'consideration' that belongs to group maintenance behavior and 'specialty, planning', 'reporting, liaison', 'adjustment, rigidity', 'paper work confirmation', and 'example setting' that belong to goal achievement behavior. For subcontractors' field leaders were named seven factors, i.e., 'example setting, specialty and planning', 'careful guidance', 'rigidity', 'observance of rules' and 'paper work handling' that belong to goal achievement behavior and, 'consideration', 'frank communication'. In order to examine the validity of these items, we analyzed relationship between the 'morale'-(satisfaction, etc.) variables of the company's regular employees and subcontractors' employees and their leadership. It was found that the three leadership behavior scales for the section chiefs, maintenance and repair subsection chiefs and subcontractor leaders were very much the same as those found in private sector. (J.P.N.)

Construction of scales to measure leadership behavior at nuclear power plants. 1

Energy Technology Data Exchange (ETDEWEB)

Misumi, Jyuji; Yamada, Akira [Institute of Nuclear Safety System Inc., Kyoto (Japan); Shinohara, Shinobu [and others

1994-05-01

In order to construct scales to measure leadership behavior of managers and supervisors at nuclear power plants, we prepared questionnaire covering all the leadership behaviors of leaders and then had their subordinates fill out the questionnaire. We selected questionnaire items for use in measuring leadership behaviors, analyzing the responses by means of factor analysis, etc. For the section chiefs, five factors were named, i.e., `consideration` and `self-righteousness` that belong to group maintenance behavior and `thorough dissemination of information`, `specialty, planning` and `pressure` that belong to goal achievement behavior. For the maintenance subsection chiefs were found seven factors, i.e., `example setting`, `appropriate handling of work`, `planning`, `rigidity`, `educational guidance` that belong to goal achievement behavior and `consideration for work` and `personal consideration` that belong to group maintenance behavior. For maintenance and repair foremen were named six factors, i.e., `consideration` that belongs to group maintenance behavior and `specialty, planning`, `reporting, liaison`, `adjustment, rigidity`, `paper work confirmation`, and `example setting` that belong to goal achievement behavior. For subcontractors` field leaders were named seven factors, i.e., `example setting, specialty and planning`, `careful guidance`, `rigidity`, `observance of rules` and `paper work handling` that belong to goal achievement behavior and, `consideration`, `frank communication`. In order to examine the validity of these items, we analyzed relationship between the `morale`-(satisfaction, etc.) variables of the company`s regular employees and subcontractors` employees and their leadership. It was found that the three leadership behavior scales for the section chiefs, maintenance and repair subsection chiefs and subcontractor leaders were very much the same as those found in private sector. (J.P.N.)

A Lifelong Learning Scale for Research and Evaluation of Teaching and Curricular Effectiveness

Science.gov (United States)

Wielkiewicz, Richard M.; Meuwissen, Alyssa S.

2014-01-01

A 16-item lifelong learning scale (LLS), appropriate for college students and others, was evaluated using a sample of 575 college students. The scale demonstrated excellent reliability and was correlated with college grade point average (GPA), agreeableness, conscientiousness, and intellect/imagination. Scores were higher for those who had studied…

Inescapable Stress Changes Walking Behavior in Flies - Learned Helplessness Revisited.

Science.gov (United States)

Batsching, Sophie; Wolf, Reinhard; Heisenberg, Martin

2016-01-01

Like other animals flies develop a state of learned helplessness in response to unescapable aversive events. To show this, two flies, one 'master', one 'yoked', are each confined to a dark, small chamber and exposed to the same sequence of mild electric shocks. Both receive these shocks when the master fly stops walking for more than a second. Behavior in the two animals is differently affected by the shocks. Yoked flies are transiently impaired in place learning and take longer than master flies to exit from the chamber towards light. After the treatment they walk more slowly and take fewer and shorter walking bouts. The low activity is attributed to the fly's experience that its escape response, an innate behavior to terminate the electric shocks, does not help anymore. Earlier studies using heat pulses instead of electric shocks had shown similar effects. This parallel supports the interpretation that it is the uncontrollability that induces the state.

Inescapable Stress Changes Walking Behavior in Flies - Learned Helplessness Revisited

Science.gov (United States)

Batsching, Sophie; Wolf, Reinhard; Heisenberg, Martin

2016-01-01

Like other animals flies develop a state of learned helplessness in response to unescapable aversive events. To show this, two flies, one 'master', one 'yoked', are each confined to a dark, small chamber and exposed to the same sequence of mild electric shocks. Both receive these shocks when the master fly stops walking for more than a second. Behavior in the two animals is differently affected by the shocks. Yoked flies are transiently impaired in place learning and take longer than master flies to exit from the chamber towards light. After the treatment they walk more slowly and take fewer and shorter walking bouts. The low activity is attributed to the fly's experience that its escape response, an innate behavior to terminate the electric shocks, does not help anymore. Earlier studies using heat pulses instead of electric shocks had shown similar effects. This parallel supports the interpretation that it is the uncontrollability that induces the state. PMID:27875580

Inescapable Stress Changes Walking Behavior in Flies - Learned Helplessness Revisited.

Directory of Open Access Journals (Sweden)

Sophie Batsching

Full Text Available Like other animals flies develop a state of learned helplessness in response to unescapable aversive events. To show this, two flies, one 'master', one 'yoked', are each confined to a dark, small chamber and exposed to the same sequence of mild electric shocks. Both receive these shocks when the master fly stops walking for more than a second. Behavior in the two animals is differently affected by the shocks. Yoked flies are transiently impaired in place learning and take longer than master flies to exit from the chamber towards light. After the treatment they walk more slowly and take fewer and shorter walking bouts. The low activity is attributed to the fly's experience that its escape response, an innate behavior to terminate the electric shocks, does not help anymore. Earlier studies using heat pulses instead of electric shocks had shown similar effects. This parallel supports the interpretation that it is the uncontrollability that induces the state.

THE IMPACT OF VISIONARY LEADERSHIP, LEARNING ORGANIZATION AND INNOVATIVE BEHAVIOR TO PERFORMANCE OF CUSTOMS AND EXCISE FUNCTIONAL

Directory of Open Access Journals (Sweden)

Muhammad Anshar

2017-12-01

Full Text Available This research aims to determine the impact of visionary leadership, learning organization, and innovative behavior on the performance of Functional Officers of Customs and Excise Inspectors at Tanjung Priok Customs and Excise Main Service Office. The research was conducted at Tanjung Priok Customs and Excise Service Office using the number of samples of 78 Functional Officers of Customs and Excise Inspectors. The sample was selected using simple random sampling technique. Data collection was done by using questionnaire and data analysis using path analysis. The results showed that 1 visionary leadership, learning organization and innovative behavior have a direct and positive impact on performance, 2 visionary leadership, and learning organization have a direct and positive impact on innovative behavior and 3 visionary leadership have a direct and positive impact on learning organization. The conclusion of this research is to improve the performance of Functional Officer of Customs and Excise Inspectors at TanjungPriok Customs and Excise Main Service Office, it is necessary to increase the aspect of visionary leadership from Head of Main Service Office, learning organization at Main Service Office and innovative behavior at Functional Officers of Customs and Excise Inspectors.

Mathematic anxiety, help seeking behavior and cooperative learning

OpenAIRE

Masoud Gholamali Lavasani; Farah Khandan

2011-01-01

Present project assess the effectiveness of cooperative learning over the mathematic anxiety and review the behavior of help seeking in first grade high school girl students. The experimental research procedure was in the form of pre-post tests after a period of 8 sessions of teaching. To measure the variables, the questionnaire of mathematic anxiety (Shokrani, 2002) and the questionnaire of help seeking technique (Ghadampour, 1998) were practiced (accepting or avoiding help seeking).To perfo...

Investigation of the relationship between organizational learning and organizational citizen behavior among the staff of teaching hospital.

Science.gov (United States)

Kiaei, Mohammad Zakaria; Hasanpoor, Edris; Sokhanvar, Mobin; Mohseni, Mohammad; Ziaiifar, Hajarbibi; Moradi, Mahin

2014-10-01

Today, the concept of organizational learning has attracted the attention of many managers and researchers in scientific and research circles as well as those in the organization-related studies. Taking the organizational learning into account might offer a means of organizational effectiveness that has gone unnoticed. Thus the present study aimed at investigating the relationship between the organizational learning in each of its four aspects as independent variables and organizational citizen behavior of the staff as constituting the dependent variable of the study. This was a descriptive-analytical study with a practical approach conducted in 2010. The sample included 167 staff members working in educational health centers affiliated with Qazvin University of Medical Sciences. The data were collected via both the organizational learning questionnaire and organizational citizen behavior questionnaire and analyzed by using SPSS software and Spearman test. The results indicated that the mean of organizational learning indicator was 2.9±0.648 and that of organizational citizen behavior 3.78±0.413. In addition, the spearman correlation coefficient ranging from 0.058 to 0.129 between the elements of the organizational learning and the organizational citizen behavior was not statistically significant (p>0.05). The findings also indicated that the correlation between them was average among the staff of Shahid Raja'ee Educational health center (0.319), thus the relationship between the two sets of variables proved significant (p=0.031). However, the same was not true in other centers. It was concluded that management commitment, open space, transfer of knowledge, and systemic vision could all enhance the level of organizational learning in hospitals which calls for focus on the elements of organizational citizen behavior.

Testing the Classroom Citizenship Behaviors Scale: Exploring the Association of Classroom Citizenship Behaviors and Student Traits

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Katt, James; Miller, Ann Neville; Brown, Tim

2017-01-01

This study investigated the reliability and validity of Myers and colleagues' Classroom Citizenship Behavior scale, as well as the relationship between student personality traits (extraversion, neuroticism, agreeableness, conscientiousness, openness, and communication apprehension) and CCBs. Two hundred and thirteen students completed…

Behavioral Objectives, the Cult of Efficiency, and Foreign Language Learning: Are They Compatible?

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Tumposky, Nancy Rennau

1984-01-01

Surveys the literature regarding the use of behavioral objectives in education and in foreign language instruction and examines the roots of the behavioral objectives movement in behaviorist psychology and the scientific management movement of the 1920s. Discusses implications for foreign and second language learning and provides suggestions for…

Behavioral patterns of environmental performance evaluation programs.

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Li, Wanxin; Mauerhofer, Volker

2016-11-01

During the past decades numerous environmental performance evaluation programs have been developed and implemented on different geographic scales. This paper develops a taxonomy of environmental management behavioral patterns in order to provide a practical comparison tool for environmental performance evaluation programs. Ten such programs purposively selected are mapped against the identified four behavioral patterns in the form of diagnosis, negotiation, learning, and socialization and learning. Overall, we found that schemes which serve to diagnose environmental abnormalities are mainly externally imposed and have been developed as a result of technical debates concerning data sources, methodology and ranking criteria. Learning oriented scheme is featured by processes through which free exchange of ideas, mutual and adaptive learning can occur. Scheme developed by higher authority for influencing behaviors of lower levels of government has been adopted by the evaluated to signal their excellent environmental performance. The socializing and learning classified evaluation schemes have incorporated dialogue, participation, and capacity building in program design. In conclusion we consider the 'fitness for purpose' of the various schemes, the merits of our analytical model and the future possibilities of fostering capacity building in the realm of wicked environmental challenges. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

Science.gov (United States)

Hong, Weizhe; Kennedy, Ann; Burgos-Artizzu, Xavier P; Zelikowsky, Moriel; Navonne, Santiago G; Perona, Pietro; Anderson, David J

2015-09-22

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new integrated hardware and software system that combines video tracking, depth sensing, and machine learning for automatic detection and quantification of social behaviors involving close and dynamic interactions between two mice of different coat colors in their home cage. We designed a hardware setup that integrates traditional video cameras with a depth camera, developed computer vision tools to extract the body "pose" of individual animals in a social context, and used a supervised learning algorithm to classify several well-described social behaviors. We validated the robustness of the automated classifiers in various experimental settings and used them to examine how genetic background, such as that of Black and Tan Brachyury (BTBR) mice (a previously reported autism model), influences social behavior. Our integrated approach allows for rapid, automated measurement of social behaviors across diverse experimental designs and also affords the ability to develop new, objective behavioral metrics.

The role of context in preschool learning: a multilevel examination of the contribution of context-specific problem behaviors and classroom process quality to low-income children's approaches to learning.

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Domínguez, Ximena; Vitiello, Virginia E; Fuccillo, Janna M; Greenfield, Daryl B; Bulotsky-Shearer, Rebecca J

2011-04-01

Research suggests that promoting adaptive approaches to learning early in childhood may help close the gap between advantaged and disadvantaged children. Recent research has identified specific child-level and classroom-level variables that are significantly associated with preschoolers' approaches to learning. However, further research is needed to understand the interactive effects of these variables and determine whether classroom-level variables buffer the detrimental effects of child-level risk variables. Using a largely urban and minority sample (N=275) of preschool children, the present study examined the additive and interactive effects of children's context-specific problem behaviors and classroom process quality dimensions on children's approaches to learning. Teachers rated children's problem behavior and approaches to learning and independent assessors conducted classroom observations to assess process quality. Problem behaviors in structured learning situations and in peer and teacher interactions were found to negatively predict variance in approaches to learning. Classroom process quality domains did not independently predict variance in approaches to learning. Nonetheless, classroom process quality played an important role in these associations; high emotional support buffered the detrimental effects of problem behavior, whereas high instructional support exacerbated them. The findings of this study have important implications for classroom practices aimed at helping children who exhibit problem behaviors. Copyright © 2010 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Up-scaling, formative phases, and learning in the historical diffusion of energy technologies

International Nuclear Information System (INIS)

Wilson, Charlie

2012-01-01

The 20th century has witnessed wholesale transformation in the energy system marked by the pervasive diffusion of both energy supply and end-use technologies. Just as whole industries have grown, so too have unit sizes or capacities. Analysed in combination, these unit level and industry level growth patterns reveal some consistencies across very different energy technologies. First, the up-scaling or increase in unit size of an energy technology comes after an often prolonged period of experimentation with many smaller-scale units. Second, the peak growth phase of an industry can lag these increases in unit size by up to 20 years. Third, the rate and timing of up-scaling at the unit level is subject to countervailing influences of scale economies and heterogeneous market demand. These observed patterns have important implications for experience curve analyses based on time series data covering the up-scaling phases of energy technologies, as these are likely to conflate industry level learning effects with unit level scale effects. The historical diffusion of energy technologies also suggests that low carbon technology policies pushing for significant jumps in unit size before a ‘formative phase’ of experimentation with smaller-scale units are risky. - Highlights: ► Comparative analysis of energy technology diffusion. ► Consistent pattern of sequential formative, up-scaling, and growth phases. ► Evidence for conflation of industry level learning effects with unit level up-scaling. ► Implications for experience curve analyses and technology policy.

Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

Science.gov (United States)

Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

2016-09-01

In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

Academic Competence and Social Adjustment of Boys with Learning Disabilities and Boys with Behavior Disorders.

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Margalit, Malka

1989-01-01

Comparison of 31 elementary grade boys with learning disabilities and 52 boys with behavior disorders who either did or did not also display hyperactive behavior found significant differences between groups on the Classroom Behavior Inventory in three areas: Hostility versus Consideration, Extroversion versus Introversion, and Independence versus…

Effects of novelty-reducing preparation on exploratory behavior and cognitive learning in a science museum setting

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Kubota, Carole A.; Olstad, Roger G.

The purpose of this study was to examine the relationships between (a) novelty and exploratory behavior, (b) novelty and cognitive learning, and (c) exploratory behavior and cognitive learning in science museums. Sixty-four sixth-grade public school students participated in a posttest-only control group design. The control group received a treatment designed to decrease the novelty of a field trip setting through a vicarious exposure while the placebo group received an informative but not novelty-reducing treatment. Both groups then visited the field site where they were videotaped. Statistical analyses were conducted on both dependent variables with socioeconomic status and academic achievement as covariates, novelty-reducing preparation as the independent variable, and gender as moderator variable. Exploratory behavior was shown to be positively correlated with cognitive learning. Significant differences were detected for exploratory behavior. For both dependent variables, gender by treatment group interaction was significant with novelty-reducing preparation shown to be highly effective on boys but having no effect on girls.

Demographic and Behavioral Characteristics of Osher Lifelong Learning Institute Members

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Hansen, Robert Jack; Brady, E. Michael; Thaxton, Steven P.

2016-01-01

The number of lifelong learning institutes (LLIs) is growing across the United States and it is important for educational planners and administrators to know about current demographic and behavioral characteristics of program participants. A 14-question survey was administered via SurveyMonkey to members who use computers in eight Osher Lifelong…

Animal behaviour learning environment: software to facilitate learning in canine and feline behavior therapy.

Science.gov (United States)

McGreevy, P D; Della Torre, P K; Evans, D L

2003-01-01

Interactive software has been developed on CD-ROM to facilitate learning of problem formulation, diagnostic methodology, and therapeutic options in dog and cat behavior problems. Students working in small groups are presented with a signalment, a case history, and brief description of the problem behavior as perceived by the client. Students then navigate through the case history by asking the client questions from an icon-driven question pad. Animated video responses to the questions are provided. Students are then required to rate the significance of the questions and answers with respect to the development of the unwelcome behavior. Links to online self-assessments and to resource materials about causation and treatment options are provided to assist students in their decision-making process. The activity concludes with a software-generated e-mail submission that includes the recorded history, diagnosis, and recommended treatment for assessment purposes.

The "drinking-buddy" scale as a measure of para-social behavior.

Science.gov (United States)

Powell, Larry; Richmond, Virginia P; Cantrell-Williams, Glenda

2012-06-01

Para-social behavior is a form of quasi-interpersonal behavior that results when audience members develop bonds with media personalities that can resemble interpersonal social interaction, but is not usually applied to political communication. This study tested whether the "Drinking-Buddy" Scale, a simple question frequently used in political communication, could be interpreted as a single-item measure of para-social behavior with respect to political candidates in terms of image judgments related to interpersonal attraction and perceived similarity to self. The participants were college students who had voted in the 2008 election. They rated the candidates, Obama or McCain, as drinking buddies and then rated the candidates' perceived similarity to themselves in attitude and background, and also the social and task attraction to the candidate. If the drinking-buddy rating serves as a proxy measure for para-social behavior, then it was expected that participants' ratings for all four kinds of similarity to and attraction toward a candidate would be higher for the candidate they chose as a drinking buddy. The directional hypotheses were supported for interpersonal attraction, but not for perceived similarity. These results indicate that the drinking-buddy scale predicts ratings of interpersonal attraction, while voters may view perceived similarity as an important but not essential factor in their candidate preference.

School promotion of healthful diet and physical activity: impact on learning outcomes and self-reported behavior.

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Parcel, G S; Simons-Morton, B; O'Hara, N M; Baranowski, T; Wilson, B

1989-01-01

The Go For Health Program included classroom health education and environmental changes in school lunch and physical education to foster healthful diet and exercise among elementary school children. Interventions were based on social learning theory and implementation was based on an organizational change strategy for school innovations. Two schools were assigned to intervention and two to control conditions. Cognitive measures (behavioral capability, self-efficacy, behavioral expectations) and self-reported diet and exercise behavior were assessed at baseline and following intervention. Data were analyzed by ANOVA using the student and then the school as the unit of analysis. Statistically significant changes were observed for diet behavioral capability, self-efficacy, and behavioral expectations, use of salt, and exercise behavioral capability (fourth grade), self-efficacy (fourth grade) and frequency of participation in aerobic activity. The results provide evidence for program impact on learning outcomes and student behavior.

Costs of Low-Scale Distance Learning Programs: A Case of Distance Learning Courses in the Aegean Islands.

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Costas Tsolakidis

2010-03-01

Full Text Available The advance of Information and Communication Technology (ICT and the reduction of cost in digital applications motivate course designers to develop new application of distance learning programs so as to meet the increasing educational needs in the knowledge-based society. As a consequence, distance learning courses are increasing in number, credibility and acceptability all over the world. The question is whether these programs are efficient in terms of costs. The main theme of this work is to investigate cost behaviour and estimate cost efficiency of distance learning courses applied in low-inhabited, remote islands. The target group consists of high school students of Grade I. The distance learning course that is designed uses several scenarios of the “what-if form” and reaches the conclusion that cost of such solutions is far lower than that of any traditional course, even at the absence of scale economies.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

Science.gov (United States)

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

A Review of Empirical Studies Investigating Antecedents and Consequences of Collective Learning Behaviors in Hospitals

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Florina D. Spânu

2013-01-01

Full Text Available This study is a systematic review of the field research conducted in medical settings investigating collective learning behaviors. The review was driven by several research foci. Our main interest was in identifying antecedents and consequences of collective learning in hospitals. We also report results on the types of research questions addressed, research designs used, and types of medical teams investigated. Twelve studies met our inclusion criteria. Our findings revealed that highly contextualized studies that use different ways of measuring learning, different ways of conceptualizing medical teams, and different research methodologies, discuss similar antecedents. Variables like leadership behaviors, unit interpersonal climate, and hierarchical position were found to play a role in explaining organizational learning in hospitals across studies. We also found that despite an intense public discourse on the link between collective learning processes and patients’ safety and medical organizations’ performance, few studies actually report empirical data supporting this relationship.

The Effect Of Islamic Education Learning Pai And Learning Results To Students Religious Behavior Of Stisip Widyapuri Mandiri Sukabumi Student

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U. Abdullah Mumin

2017-06-01

Full Text Available The purpose of this study is to measure the level of the effect of Islamic Education learning and learning result on religious behaviour in STISIP Widyapuri Mandiri Sukabumi. The method used in this research is quantitative analysis based on inferential statistical model. The data collection is done by using observation techniques interviews and questionnaires. The researcher analize the data by using logic analysis for qualitative and statistical analysis for quantitative data by using descriptive statistics regression and correlation. Based on the hypothesis test simultaneously PAI learning and learning result have a positive and significant effect on students religious behaviour. Partially only PAI learning alone has a positive and significant impact on religious behavior.

Long term treadmill exercise performed to chronic social isolated rats regulate anxiety behavior without improving learning.

Science.gov (United States)

Cevik, Ozge Selin; Sahin, Leyla; Tamer, Lulufer

2018-05-01

The type and duration of exposure to stress is an important influence on emotional and cognitive functions. Learning is the adaptive response of the central nervous system that occurs in hippocampus which affects from environmental factors like exercise. In this study, we investigated effects of long term treadmill exercise on learning and behavior on chronic social isolated rat. Male Wistar rats (n = 32) randomly assigned into four groups: control, exercised, social isolation, social isolation + exercise during postnatal days (PNDs) 21-34. Social isolation protocol was applied during 14 days by placing rat in a cage one by one. Rats were exercised during 5 days, days were chosen randomly for overall 4 weeks (20, 30, 50, 60 min respectively). Finally, learning performance was evaluated by Morris water maze (MWM). Anxiety behavior was evaluated by Open field and elevated plus maze test. At the end of learning and behavior tests, the rats were decapitated to collect blood samples via intracardiac puncture and corticosterone analysis was performed with ELISA method. Animal weights and water consumption did not change significantly but food intake differed among groups. Corticosterone level did not change between groups. The frequency of entering to the target quadrant increased in exercised rat significantly. However, there was no difference in learning and memory in rats. Treadmill exercise reduced anxiety behavior significantly. Taken together these findings may point out that, long term treadmill exercise did not change learning and memory but reduced anxiety level of rat without changing corticosterone level. Copyright © 2018 Elsevier Inc. All rights reserved.

Assessment of first-year medical students' perceptions of teaching and learning through team-based learning sessions.

Science.gov (United States)

Obad, Adam S; Peeran, Ahmed A; Shareef, Mohammad Abrar; Alsheikh, Wissal J; Kalagi, Dana A; AlAmodi, Abdulhadi A; Khan, Tehreem A; Shaikh, Abdul Ahad; Ganguly, Paul; Yaqinuddin, Ahmed

2016-12-01

Team-based learning (TBL) is an emerging teaching and learning strategy being employed in medical schools. The College of Medicine at Alfaisal University has adopted a TBL approach as an instructional method for first-year medical students. The aim of the present study was to describe the TBL method employed at Alfaisal University College of Medicine and to assess first-year medical students' perceptions of this learning modality for the anatomy- and physiology-based blocks/courses in organ systems form of curriculum. A five-point Likert scale questionnaire was structured based on Kirkpatrick's theory and assessed three major domains: reaction, learning, and behavior. Confirmatory factor analysis (CFA) and Cronbach's α-coefficient tests were used to assess the validity and reliability of the construct, respectively. CFA showed an adequate validity of the survey and Cronbach's α revealed an acceptable internal uniformity (0.69). A total of 185 respondents rated reaction, learning, and behavior toward introduction of TBL as 3.53 ± 1.01, 3.59 ± 1.12, and 3.57 ± 1.12, respectively. Excellent students rated TBL highly in all major domains compared with borderline students (reaction, behavior, and learning domains with P values of teaching and learning strategy for functional anatomy, and prior involvement in teamwork and academic performance correlates with higher ratings of TBL. Copyright © 2016 the American Physiological Society.

E-LEARNING TURKISH LANGUAGE AND GRAMMAR: Analyzing Learners' Behavior

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Panagiotis GEORGALAS

2012-01-01

Full Text Available This study analyses the behavior and the preferences of the Greek learners of Turkish language, who use a particular e-learning website in parallel with their studies, namely: http://turkish.pgeorgalas.gr. The website offers free online material in Greek and English language for learning the Turkish language and grammar. The traffic of several modules of the website has been measured, examined and analyzed. The research was carried out between the years 2010- 2011 and included the analysis of several million clicks. The results show particular attitudes, habits and preferences throughout the e-learning process. There is a preference of users to exercises against theory. Fast cross-link exercises are preferred to slower “fill in” ones. During the weekends, visitors tend to use less e-learning facilities and select more light activities than the rest days of the week. Society trends and fashions like TV serials have a serious impact to the number of people who decide to learn a new foreign language, in particular Turkish. There is a strong preference of the audience to use online TV against online radio facilities for language practice. The subjects that Greek learners of Turkish language spend more time are verbs conjugation and vocabulary learning. They focus on elementary grammar subjects like the Alphabet, the numbers and the formation of plural. Finally, they try to learn the syntax of Turkish language through sentence structure puzzles and give priority to special grammar issues like noun compounds that are not present in Greek language.

Psychometric appraisal of the Scale for Interpersonal Behavior (SIB) in France.

Science.gov (United States)

Bouvard, M; Arrindell, W A; Guérin, J; Bouchard, C; Rion, A C; Ducottet, E; Séchaud, M; Mollard, E; Grillet, P R; Dang, C; Cottraux, J

1999-08-01

The present study was carried out in France to evaluate the reliability and validity of the Scale for Interpersonal Behavior (SIB), a multidimensional measure of difficulty and distress in assertiveness that was originally developed in The Netherlands. This appraisal was conducted with a clinical sample (N = 166) and a general population sample (N = 150). The clinical series comprised 115 patients with social phobia and 51 patients with personality disorder, 28 of whom were of the avoidant type. Support was found for internal consistency and test-retest reliability of the French SIB. Compared to controls, both social phobics and patients with an avoidant personality disorder had significantly lower mean scores on all performance scales and significantly higher ones on all distress scales, with the social phobics occupying a position in between. Findings in relation to convergent and divergent validity were quite satisfactory. Sensitivity of the French SIB for detecting change was demonstrated in a subgroup of the clinical Ss who had undergone 15 sessions of cognitive-behavioral group therapy for underassertiveness.

Parameter study on dynamic behavior of ITER tokamak scaled model

International Nuclear Information System (INIS)

Nakahira, Masataka; Takeda, Nobukazu

2004-12-01

This report summarizes that the study on dynamic behavior of ITER tokamak scaled model according to the parametric analysis of base plate thickness, in order to find a reasonable solution to give the sufficient rigidity without affecting the dynamic behavior. For this purpose, modal analyses were performed changing the base plate thickness from the present design of 55 mm to 100 mm, 150 mm and 190 mm. Using these results, the modification plan of the plate thickness was studied. It was found that the thickness of 150 mm gives well fitting of 1st natural frequency about 90% of ideal rigid case. Thus, the modification study was performed to find out the adequate plate thickness. Considering the material availability, transportation and weldability, it was found that the 300mm thickness would be a limitation. The analysis result of 300mm thickness case showed 97% fitting of 1st natural frequency to the ideal rigid case. It was however found that the bolt length was too long and it gave additional twisting mode. As a result, it was concluded that the base plate thickness of 150mm or 190mm gives sufficient rigidity for the dynamic behavior of the scaled model. (author)

Validity and Reliability of Revised Inventory of Learning Processes.

Science.gov (United States)

Gadzella, B. M.; And Others

The Inventory of Learning Processes (ILP) was developed by Schmeck, Ribich, and Ramanaiah in 1977 as a self-report inventory to assess learning style through a behavioral-oriented approach. The ILP was revised by Schmeck in 1983. The Revised ILP contains six scales: (1) Deep Processing; (2) Elaborative Processing; (3) Shallow Processing; (4)…

Identification of animal behavioral strategies by inverse reinforcement learning.

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Shoichiro Yamaguchi

2018-05-01

Full Text Available Animals are able to reach a desired state in an environment by controlling various behavioral patterns. Identification of the behavioral strategy used for this control is important for understanding animals' decision-making and is fundamental to dissect information processing done by the nervous system. However, methods for quantifying such behavioral strategies have not been fully established. In this study, we developed an inverse reinforcement-learning (IRL framework to identify an animal's behavioral strategy from behavioral time-series data. We applied this framework to C. elegans thermotactic behavior; after cultivation at a constant temperature with or without food, fed worms prefer, while starved worms avoid the cultivation temperature on a thermal gradient. Our IRL approach revealed that the fed worms used both the absolute temperature and its temporal derivative and that their behavior involved two strategies: directed migration (DM and isothermal migration (IM. With DM, worms efficiently reached specific temperatures, which explains their thermotactic behavior when fed. With IM, worms moved along a constant temperature, which reflects isothermal tracking, well-observed in previous studies. In contrast to fed animals, starved worms escaped the cultivation temperature using only the absolute, but not the temporal derivative of temperature. We also investigated the neural basis underlying these strategies, by applying our method to thermosensory neuron-deficient worms. Thus, our IRL-based approach is useful in identifying animal strategies from behavioral time-series data and could be applied to a wide range of behavioral studies, including decision-making, in other organisms.

Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints

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Kun Li

2015-03-01

Full Text Available For a domestic personal robot, personalized services are as important as predesigned tasks, because the robot needs to adjust the home state based on the operator's habits. An operator's habits are composed of cues, behaviors, and rewards. This article introduces behavioral footprints to describe the operator's behaviors in a house, and applies the inverse reinforcement learning technique to extract the operator's habits, represented by a reward function. We implemented the proposed approach with a mobile robot on indoor temperature adjustment, and compared this approach with a baseline method that recorded all the cues and behaviors of the operator. The result shows that the proposed approach allows the robot to reveal the operator's habits accurately and adjust the environment state accordingly.

Temporal Memory Reinforcement Learning for the Autonomous Micro-mobile Robot Based-behavior

Institute of Scientific and Technical Information of China (English)

Yang Yujun(杨玉君); Cheng Junshi; Chen Jiapin; Li Xiaohai

2004-01-01

This paper presents temporal memory reinforcement learning for the autonomous micro-mobile robot based-behavior. Human being has a memory oblivion process, i.e. the earlier to memorize, the earlier to forget, only the repeated thing can be remembered firmly. Enlightening forms this, and the robot need not memorize all the past states, at the same time economizes the EMS memory space, which is not enough in the MPU of our AMRobot. The proposed algorithm is an extension of the Q-learning, which is an incremental reinforcement learning method. The results of simulation have shown that the algorithm is valid.

Acquisition of Lateralized Predation Behavior Associated with Development of Mouth Asymmetry in a Lake Tanganyika Scale-Eating Cichlid Fish.

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Yuichi Takeuchi

Full Text Available The scale-eating cichlid Perissodus microlepis with asymmetric mouth is an attractive model of behavioral laterality: each adult tears off scales from prey fishes' left or right flanks according to the direction in which its mouth is skewed. To investigate the development of behavioral laterality and mouth asymmetry, we analyzed stomach contents and lower jaw-bone asymmetry of various-sized P. microlepis (22 ≤ SL<115 mm sampled in Lake Tanganyika. The shapes of the pored scales found in each specimen's stomach indicated its attack side preference. Early-juvenile specimens (SL<45 mm feeding mainly on zooplankton exhibited slight but significant mouth asymmetry. As the fish acquired scale-eating (45 mm ≤ SL, attack side preference was gradually strengthened, as was mouth asymmetry. Among size-matched individuals, those with more skewed mouths ate more scales. These findings show that behavioral laterality in scale-eating P. microlepis is established in association with development of mouth asymmetry which precedes the behavioral acquisition, and that this synergistic interaction between physical and behavioral literalities may contribute to efficient scale-eating.

Analysis of learners’ behaviors and learning outcomes in a massive open online course

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Dong Liang

2014-09-01

Full Text Available This paper introduces a massive open online course (MOOC on educational technology, and studies the factors that may influence learners’ participation and performance in the MOOC. Students’ learning records captured in the course management system and students’ feedback collected from a questionnaire survey are explored. Regression analysis is adopted to examine the correlation among perceived learning experience, learning activities and learning outcomes; data mining is applied to optimize the correlation models. The findings suggest that learners’ perceived usefulness rather than perceived ease of use of the MOOC, positively influences learners’ use of the system, and consequentially, the learning outcome. In addition, learners’ previous MOOC experience is not found to have a significant impact on their learning behavior and learning outcome in general. However, the performance of less active learners is found to be influenced by their prior MOOC experience.

TensorFlow: A system for large-scale machine learning

OpenAIRE

Abadi, Martín; Barham, Paul; Chen, Jianmin; Chen, Zhifeng; Davis, Andy; Dean, Jeffrey; Devin, Matthieu; Ghemawat, Sanjay; Irving, Geoffrey; Isard, Michael; Kudlur, Manjunath; Levenberg, Josh; Monga, Rajat; Moore, Sherry; Murray, Derek G.

2016-01-01

TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general-purpose GPUs, and custom designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexib...

Behavioral and neurobiological mechanisms of extinction in Pavlovian and instrumental learning.

Science.gov (United States)

Todd, Travis P; Vurbic, Drina; Bouton, Mark E

2014-02-01

This article reviews research on the behavioral and neural mechanisms of extinction as it is represented in both Pavlovian and instrumental learning. In Pavlovian extinction, repeated presentation of a signal without its reinforcer weakens behavior evoked by the signal; in instrumental extinction, repeated occurrence of a voluntary action without its reinforcer weakens the strength of the action. In either case, contemporary research at both the behavioral and neural levels of analysis has been guided by a set of extinction principles that were first generated by research conducted at the behavioral level. The review discusses these principles and illustrates how they have informed the study of both Pavlovian and instrumental extinction. It shows that behavioral and neurobiological research efforts have been tightly linked and that their results are readily integrated. Pavlovian and instrumental extinction are also controlled by compatible behavioral and neural processes. Since many behavioral effects observed in extinction can be multiply determined, we suggest that the current close connection between behavioral-level and neural-level analyses will need to continue. Copyright © 2013 Elsevier Inc. All rights reserved.

Exploring the link between multiscale entropy and fractal scaling behavior in near-surface wind.

Directory of Open Access Journals (Sweden)

Miguel Nogueira

Full Text Available The equivalency between the power law behavior of Multiscale Entropy (MSE and of power spectra opens a promising path for interpretation of complex time-series, which is explored here for the first time for atmospheric fields. Additionally, the present manuscript represents a new independent empirical validation of such relationship, the first one for the atmosphere. The MSE-fractal relationship is verified for synthetic fractal time-series covering the full range of exponents typically observed in the atmosphere. It is also verified for near-surface wind observations from anemometers and CFSR re-analysis product. The results show a ubiquitous β ≈ 5/3 behavior inside the inertial range. A scaling break emerges at scales around a few seconds, with a tendency towards 1/f noise. The presence, extension and fractal exponent of this intermediate range are dependent on the particular surface forcing and atmospheric conditions. MSE shows an identical picture which is consistent with the turbulent energy cascade model: viscous dissipation at the small-scale end of the inertial range works as an information sink, while at the larger (energy-containing scales the multiple forcings in the boundary layer act as widespread information sources. Another scaling transition occurs at scales around 1-10 days, with an abrupt flattening of the spectrum. MSE shows that this transition corresponds to a maximum of the new information introduced, occurring at the time-scales of the synoptic features that dominate weather patterns. At larger scales, a scaling regime with flatter slopes emerges extending to scales larger than 1 year. MSE analysis shows that the amount of new information created decreases with increasing scale in this low-frequency regime. Additionally, in this region the energy injection is concentrated in two large energy peaks: daily and yearly time-scales. The results demonstrate that the superposition of these periodic signals does not destroy the

Exploring the link between multiscale entropy and fractal scaling behavior in near-surface wind.

Science.gov (United States)

Nogueira, Miguel

2017-01-01

The equivalency between the power law behavior of Multiscale Entropy (MSE) and of power spectra opens a promising path for interpretation of complex time-series, which is explored here for the first time for atmospheric fields. Additionally, the present manuscript represents a new independent empirical validation of such relationship, the first one for the atmosphere. The MSE-fractal relationship is verified for synthetic fractal time-series covering the full range of exponents typically observed in the atmosphere. It is also verified for near-surface wind observations from anemometers and CFSR re-analysis product. The results show a ubiquitous β ≈ 5/3 behavior inside the inertial range. A scaling break emerges at scales around a few seconds, with a tendency towards 1/f noise. The presence, extension and fractal exponent of this intermediate range are dependent on the particular surface forcing and atmospheric conditions. MSE shows an identical picture which is consistent with the turbulent energy cascade model: viscous dissipation at the small-scale end of the inertial range works as an information sink, while at the larger (energy-containing) scales the multiple forcings in the boundary layer act as widespread information sources. Another scaling transition occurs at scales around 1-10 days, with an abrupt flattening of the spectrum. MSE shows that this transition corresponds to a maximum of the new information introduced, occurring at the time-scales of the synoptic features that dominate weather patterns. At larger scales, a scaling regime with flatter slopes emerges extending to scales larger than 1 year. MSE analysis shows that the amount of new information created decreases with increasing scale in this low-frequency regime. Additionally, in this region the energy injection is concentrated in two large energy peaks: daily and yearly time-scales. The results demonstrate that the superposition of these periodic signals does not destroy the underlying

Sensorimotor learning biases choice behavior: a learning neural field model for decision making.

Directory of Open Access Journals (Sweden)

Christian Klaes

Full Text Available According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action

Cross-cultural validity of the scale for interpersonal behavior.

Science.gov (United States)

Nota, Laura; Arrindell, Willem A; Soresi, Salvatore; van der Ende, Jan; Sanavio, Ezio

2011-01-01

The Scale for Interpersonal Behavior (SIB) is a 50-item multidimensional measure of difficulty and distress in assertiveness. The SIB assesses negative assertion, expression of and dealing with personal limitations, initiating assertiveness and positive assertion. The SIB was originally developed in the Netherlands. The present study attempted to replicate the original factors with an Italian student sample (n = 995). The four distress and four performance factors were replicable across two methods of analysis (the multiple group method of confirmatory analysis and Tucker's coefficient of congruence (phi). The corresponding scales were internally consistent and showed predicted patterns of correlations with a measure of self-efficacy. Sex and age differences in assertiveness were generally negligible. Italian students had higher positive assertion-performance scores than the Dutch and comparable scores on other performance scales; by contrast, the Italian subjects had significantly higher scores on all SIB distress scales than their Dutch equivalents. This was ascribed to the stronger pressure on people in Italian society to behave assertively (Hofstede's National Masculinity score = 70) as opposed to the Dutch society (National Masculinity score = 14).

Neuromodulatory Adaptive Combination of Correlation-based Learning in Cerebellum and Reward-based Learning in Basal Ganglia for Goal-directed Behavior Control

DEFF Research Database (Denmark)

Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational...... and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role...... in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We...

The factor structure of the self-directed learning readiness scale | de ...

African Journals Online (AJOL)

The factor structure of the Self-Directed Learning Readiness Scale (SDLRS) was investigated for Afrikaans and English-speaking first-year university students. Five factors were extracted and rotated to oblique simple structure for both groups. Four of the five factors were satisfactorily replicated. The fifth factor appeared to ...

Neurodevelopmental Status and Adaptive Behaviors in Preschool Children with Chronic Kidney Disease

Science.gov (United States)

Duquette, Peter J.; Hooper, Stephen R.; Icard, Phil F.; Hower, Sarah J.; Mamak, Eva G.; Wetherington, Crista E.; Gipson, Debbie S.

2009-01-01

This study examines the early neurodevelopmental function of infants and preschool children who have chronic kidney disease (CKD). Fifteen patients with CKD are compared to a healthy control group using the "Mullen Scales of Early Learning" (MSEL) and the "Vineland Adaptive Behavior Scale" (VABS). Multivariate analysis reveals…

Influence of course characteristics, student characteristics, and behavior in learning management systems on student performance

NARCIS (Netherlands)

Conijn, Rianne; Kleingeld, Ad; Matzat, Uwe; Snijders, Chris; van Zaanen, Menno

2016-01-01

The use of learning management systems (LMS) in education make it possible to track students’ online behavior. This data can be used for educational data mining and learning analytics, for example, by predicting student performance. Although LMS data might contain useful predictors, course

Scaling behavior of spin gap of the bond alternating anisotropic spin-1/2 Heisenberg chain

Energy Technology Data Exchange (ETDEWEB)

Paul, Susobhan, E-mail: suso.phy.paul@gmail.com [Department of Physics, Scottish Church College, 1 & 3 Urquhart Square, Kolkata-700006 (India); Ghosh, Asim Kumar, E-mail: asimkumar96@yahoo.com [Department of Physics, Jadavpur University, 188 Raja S C Mallik Road, Kolkata-700032 (India)

2016-05-06

Scaling behavior of spin gap of a bond alternating spin-1/2 anisotropic Heisenberg chain has been studied both in ferromagnetic (FM) and antiferromagnetic (AFM) cases. Spin gap has been estimated by using exact diagonalization technique. All those quantities have been obtained for a region of anisotropic parameter Δ defined by 0≤Δ≤1. Spin gap is found to develop as soon as the non-uniformity in the alternating bond strength is introduced in the AFM regime which furthermore sustains in the FM regime as well. Scaling behavior of the spin gap has been studied by introducing scaling exponent. The variation of scaling exponents with Δ is fitted with a regular function.

Thermodynamic scaling behavior in genechips

Directory of Open Access Journals (Sweden)

Van Hummelen Paul

2009-01-01

Full Text Available Abstract Background Affymetrix Genechips are characterized by probe pairs, a perfect match (PM and a mismatch (MM probe differing by a single nucleotide. Most of the data preprocessing algorithms neglect MM signals, as it was shown that MMs cannot be used as estimators of the non-specific hybridization as originally proposed by Affymetrix. The aim of this paper is to study in detail on a large number of experiments the behavior of the average PM/MM ratio. This is taken as an indicator of the quality of the hybridization and, when compared between different chip series, of the quality of the chip design. Results About 250 different GeneChip hybridizations performed at the VIB Microarray Facility for Homo sapiens, Drosophila melanogaster, and Arabidopsis thaliana were analyzed. The investigation of such a large set of data from the same source minimizes systematic experimental variations that may arise from differences in protocols or from different laboratories. The PM/MM ratios are derived theoretically from thermodynamic laws and a link is made with the sequence of PM and MM probe, more specifically with their central nucleotide triplets. Conclusion The PM/MM ratios subdivided according to the different central nucleotides triplets follow qualitatively those deduced from the hybridization free energies in solution. It is shown also that the PM and MM histograms are related by a simple scale transformation, in agreement with what is to be expected from hybridization thermodynamics. Different quantitative behavior is observed on the different chip organisms analyzed, suggesting that some organism chips have superior probe design compared to others.

Experimental study on dynamic behavior of large scale foundation, 1

International Nuclear Information System (INIS)

Hanada, Kazufumi; Sawada, Yoshihiro; Esashi, Yasuyuki; Ueshima, Teruyuki; Nakamura, Hideharu

1983-01-01

The large-sized, high performance vibrating table in the Nuclear Power Engineering Test Center is installed on a large-scale concrete foundation of length 90.9 m, width 44.8 m and maximum thickness 21 m, weighing 150,000 tons. Through the experimental study on the behavior of the foundation, which is set on gravel ground, useful information should be obtained on the siting of a nuclear power plant on the Quaternary stratum ground. The objective of research is to grasp the vibration characteristics of the foundation during the vibration of the table to evaluate the interaction between the foundation and the ground, and to evaluate an analytical method for numerically simulating the vibration behavior. In the present study, the vibration behavior of the foundation was clarified by measurement, and in order to predict the vibration behavior, the semi-infinite theory of elasticity was applied. The accuracy of this analytical method was demonstrated by comparison with the measured results. (Mori, K.)

Engineering behavior of small-scale foundation piers constructed from alternative materials

Science.gov (United States)

Prokudin, Maxim Mikhaylovich

Testing small-scale prototype pier foundations to evaluate engineering behavior is an alternative to full-scale testing that facilitates testing of several piers and pier groups at relatively low cost. In this study, various pier systems and pier groups at one tenth scale were subjected to static vertical loading under controlled conditions to evaluate stiffness, bearing capacity, and group efficiency. Pier length, material properties and methods of installation were evaluated. Pier length to diameter ratios varied between four and eight. A unique soil pit with dimensions of 2.1 m in width, 1.5 m in length and 2.0 m in depth was designed to carry out this research. The test pit was filled with moisture conditioned and compacted Western Iowa loess. A special load test frame was designed and fabricated to provide up to 25,000 kg vertical reaction force for load testing. A load cell and displacement instrumentation was setup to capture the load test data. Alternative materials to conventional cement concrete were studied. The pier materials evaluated in this study included compacted aggregate, cement stabilized silt, cementitious grouts, and fiber reinforced silt. Key findings from this study demonstrated that (1) the construction method influences the behavior of aggregate piers, (2) the composition of the pier has a significant impact on the stiffness, (3) group efficiencies were found to be a function of pier length and pier material, (4) in comparison to full-scale testing the scaled piers were found to produce a stiffer response with load-settlement and bearing capacities to be similar. Further, although full-scale test results were not available for all pier materials, the small-scale testing provided a means for comparing results between pier systems. Finally, duplicate pier tests for a given length and material were found to be repeatable.

An examination of the impact of non-formal and informal learning on adult environmental knowledge, attitudes, and behaviors

Science.gov (United States)

Digby, Cynthia Louise Barrett

The purpose of this research is to consider the environmental knowledge, attitudes, and behaviors, of adults in Minnesota, and possible factors that influence environmental literacy. Specifically, this study is designed to: (1) measure the environmental literacy of Minnesota adults, (2) explore possible relationships between Minnesota adults, environmental literacy variables and their demographic, non-formal and informal learning, and (3) determine the relative contribution of demographic and learning variables for predicting environmental knowledge, attitudes and behaviors. This research was accomplished by conducting a secondary data analysis of The Third Minnesota Report Card on Environmental Literacy: A Survey of Adult Environmental Knowledge, Attitudes and Behavior (Murphy & Olson, 2008). Phone interviews were completed between August and November 2007 with one thousand adults throughout Minnesota. Findings indicated that for age, education, and income, there was a weak positive relationship with environmental knowledge, attitude and behavior scores. There was a significant effect for gender and environmental knowledge scores, with males receiving higher environmental knowledge scores than females. There was a significant effect for gender and environmental attitudes, and behavior scores as well, with females receiving slightly higher environmental attitude and behavior scores than males. After controlling for the effects of demographic variables on environmental knowledge, attitudes and behaviors, non-formal learning participation appears to be a moderate contributor to both environmental knowledge and environmental behaviors. After controlling for the effects of demographic variables on environmental knowledge, attitudes and behaviors, informal learning participation appears to be a slight contributor to environmental attitudes, and a moderate contributor to environmental knowledge and behaviors. Overall, the results of this study suggest that participation

Multi-scale analysis of deformation behavior at SCC crack tip (2). (Contract research)

International Nuclear Information System (INIS)

Kaji, Yoshiyuki; Miwa, Yukio; Tsukada, Takashi; Hayakawa, Masao; Nagashima, Nobuo

2007-03-01

This report describes a result of the research conducted by the Japan Atomic Energy Agency and the National Institute for Materials Science under contract with Japan Nuclear Energy Safety Organization (JNES) that was concerned with a multi-scale analysis of plastic deformation behavior at the crack tip of stress corrosion cracking (SCC). The research was carried out to evaluate the validity of the SCC growth data acquired in the intergranular SCC (IGSCC) project based on a mechanistic understanding of SCC. For the purpose, in this research, analyses of the plastic deformation behavior and microstructure around the crack tip were performed in a nano-order scale. The hardness measured in nano, meso and macro scales was employed as a common index of the strength, and the essential data necessary to understand the SCC propagation behavior were acquired and analyzed that are mainly a size of plastic deformation region and a microstructural information in the region, e.g. data of crystallografy, microscopic deformation and dislocations at the inside of grains and grain boundaries. In this year, we analyzed the state of plastic deformation region at the crack tip of IGSCC under various conditions and investigated relationship between crack growth behavior and stress intensity factor. Especially, we investigated in detail about two different hardened specimens used in the SCC growth tests in the IGSCC project. (J.P.N.)

The Effect of Education Level on Psychological Empowerment and Burnout-The Mediating Role of Workplace Learning Behaviors

OpenAIRE

Sarit Rashkovits; Yael Livne

2013-01-01

The study investigates the relationship between education level, workplace learning behaviors, psychological empowerment and burnout in a sample of 191 teachers. We hypothesized that education level will positively affect psychological state of increased empowerment and decreased burnout, and we purposed that these effects will be mediated by workplace learning behaviors. We used multiple regression analyses to test the model that included also the 6 following control var...

Learning of Behavior Trees for Autonomous Agents

OpenAIRE

Colledanchise, Michele; Parasuraman, Ramviyas; Ögren, Petter

2015-01-01

Definition of an accurate system model for Automated Planner (AP) is often impractical, especially for real-world problems. Conversely, off-the-shelf planners fail to scale up and are domain dependent. These drawbacks are inherited from conventional transition systems such as Finite State Machines (FSMs) that describes the action-plan execution generated by the AP. On the other hand, Behavior Trees (BTs) represent a valid alternative to FSMs presenting many advantages in terms of modularity, ...

Importance of associative learning processes for one-trial behavioral sensitization of preweanling rats.

Science.gov (United States)

McDougall, Sanders A; Pothier, Alexandria G; Der-Ghazarian, Taleen; Herbert, Matthew S; Kozanian, Olga O; Castellanos, Kevin A; Flores, Ana T

2011-10-01

During adulthood, associative learning is necessary for the expression of one-trial behavioral sensitization; however, it is uncertain whether the same associative processes are operative during the preweanling period. Two strategies were used to assess the importance of associative learning for one-trial behavioral sensitization of preweanling rats. In the initial experiments, we varied both the sequence and time interval between presentation of the conditioned stimulus (CS, novel environment) and unconditioned stimulus (US, cocaine). In the final experiment, we determined whether electroconvulsive shock-induced retrograde amnesia would disrupt one-trial behavioral sensitization. Results showed that robust-sensitized responding was apparent regardless of the sequence in which cocaine and the novel environment (the presumptive CS) were presented. Varying the time between CS and US presentation (0, 3, or 6 h) was also without effect. Results from experiment 3 showed that single or multiple electroconvulsive shock treatments did not alter the expression of the sensitized response. Therefore, these data indicated that one-trial behavioral sensitization of preweanling rats was exclusively mediated by nonassociative mechanisms and that associative processes did not modulate sensitized responding. These findings are in contrast to what is observed during adulthood, as adult rats exhibit one-trial behavioral sensitization only when associative processes are operative.

How does a specific learning and memory system in the mammalian brain gain control of behavior?

Science.gov (United States)

McDonald, Robert J; Hong, Nancy S

2013-11-01

This review addresses a fundamental, yet poorly understood set of issues in systems neuroscience. The issues revolve around conceptualizations of the organization of learning and memory in the mammalian brain. One intriguing, and somewhat popular, conceptualization is the idea that there are multiple learning and memory systems in the mammalian brain and they interact in different ways to influence and/or control behavior. This approach has generated interesting empirical and theoretical work supporting this view. One issue that needs to be addressed is how these systems influence or gain control of voluntary behavior. To address this issue, we clearly specify what we mean by a learning and memory system. We then review two types of processes that might influence which memory system gains control of behavior. One set of processes are external factors that can affect which system controls behavior in a given situation including task parameters like the kind of information available to the subject, types of training experience, and amount of training. The second set of processes are brain mechanisms that might influence what memory system controls behavior in a given situation including executive functions mediated by the prefrontal cortex; switching mechanisms mediated by ascending neurotransmitter systems, the unique role of the hippocampus during learning. The issue of trait differences in control of different learning and memory systems will also be considered in which trait differences in learning and memory function are thought to potentially emerge from differences in level of prefrontal influence, differences in plasticity processes, differences in ascending neurotransmitter control, differential access to effector systems like motivational and motor systems. Finally, we present scenarios in which different mechanisms might interact. This review was conceived to become a jumping off point for new work directed at understanding these issues. The outcome of

Data-Driven Design: Learning from Student Experiences and Behaviors

Science.gov (United States)

Horodyskyj, L.; Mead, C.; Buxner, S.; Semken, S. C.; Anbar, A. D.

2015-12-01

Good instructors know that lessons and courses change over time. Limitations in time and data often prevent instructors from making changes that will most benefit their students. For example, in traditional in-person classrooms an instructor may only have access to the final product of a student's thought processes (such as a term paper, homework assignment, or exam). The thought processes that lead to a given answer are opaque to the instructor, making future modifications to course content an exercise in trial-and-error and instinct. Modern online intelligent tutoring systems can provide insight into a student's behavior, providing transparency to a previously opaque process and providing the instructor with better information for course modification. Habitable Worlds is an introductory level online-only astrobiology lab course that has been offered at Arizona State University since Fall 2011. The course is built and offered through an intelligent tutoring system, Smart Sparrow's Adaptive eLearning Platform, which provides in-depth analytics that allow the instructor to investigate detailed student behavior, from time spent on question to number of attempts to patterns of answers. We will detail the process we employ of informed modification of course content, including time and trial comparisons between semesters, analysis of submitted answers, analysis of alternative learning pathways taken, and A/B testing.

Development and Standardization of the Diagnostic Adaptive Behavior Scale: Application of Item Response Theory to the Assessment of Adaptive Behavior

Science.gov (United States)

Tassé, Marc J.; Schalock, Robert L.; Thissen, David; Balboni, Giulia; Bersani, Henry, Jr.; Borthwick-Duffy, Sharon A.; Spreat, Scott; Widaman, Keith F.; Zhang, Dalun; Navas, Patricia

2016-01-01

The Diagnostic Adaptive Behavior Scale (DABS) was developed using item response theory (IRT) methods and was constructed to provide the most precise and valid adaptive behavior information at or near the cutoff point of making a decision regarding a diagnosis of intellectual disability. The DABS initial item pool consisted of 260 items. Using IRT…

Predicting the Motivation in College-Aged Learning Disabled Students Based on the Academic Motivation Scale

Science.gov (United States)

Luna, Alberto D.

2013-01-01

Given the paucity of research on factors associated with motivation in learning disabled college students, the present study investigated the motivation levels in college students with learning disabilities. The Academic Motivation Scale (AMS) has been validated cross-nationally and across all educational age groups of students having various…

Size-dependent elastic/inelastic behavior of enamel over millimeter and nanometer length scales.

Science.gov (United States)

Ang, Siang Fung; Bortel, Emely L; Swain, Michael V; Klocke, Arndt; Schneider, Gerold A

2010-03-01

The microstructure of enamel like most biological tissues has a hierarchical structure which determines their mechanical behavior. However, current studies of the mechanical behavior of enamel lack a systematic investigation of these hierarchical length scales. In this study, we performed macroscopic uni-axial compression tests and the spherical indentation with different indenter radii to probe enamel's elastic/inelastic transition over four hierarchical length scales, namely: 'bulk enamel' (mm), 'multiple-rod' (10's microm), 'intra-rod' (100's nm with multiple crystallites) and finally 'single-crystallite' (10's nm with an area of approximately one hydroxyapatite crystallite). The enamel's elastic/inelastic transitions were observed at 0.4-17 GPa depending on the length scale and were compared with the values of synthetic hydroxyapatite crystallites. The elastic limit of a material is important as it provides insights into the deformability of the material before fracture. At the smallest investigated length scale (contact radius approximately 20 nm), elastic limit is followed by plastic deformation. At the largest investigated length scale (contact size approximately 2 mm), only elastic then micro-crack induced response was observed. A map of elastic/inelastic regions of enamel from millimeter to nanometer length scale is presented. Possible underlying mechanisms are also discussed. (c) 2009 Elsevier Ltd. All rights reserved.

Learning Organization and Innovative Behavior: The Mediating Effect of Work Engagement

Science.gov (United States)

Park, Yu Kyoung; Song, Ji Hoon; Yoon, Seung Won; Kim, Jungwoo

2014-01-01

Purpose: The purpose of this study is to investigate the mediating effect of work engagement on the relationship between learning organization and innovative behavior. Design/methodology/approach: This study used surveys as a data collection tool and implemented structural equation modeling for empirically testing the proposed research model.…

Psychometric appraisal of the scale for interpersonal behavior (SIB) in France

NARCIS (Netherlands)

Bouvard, M; Arrindell, WA; Guerin, J; Bouchard, C; Rion, AC; Ducottet, E; Sechaud, M; Mollard, E; Grillet, PR; Dang, C; Cottraux, J

The present study was carried out in France to evaluate the reliability and validity of the Scale for Interpersonal Behavior (SIB), a multidimensional measure of difficulty and distress in assertiveness that was originally developed in The Netherlands. This appraisal was conducted with a

Motivation categories in college students’ learning engagement behaviors and outcomes in Taiwan: An application of cluster analysis

OpenAIRE

Tzu-Ling Hsieh

2016-01-01

This study explores how different motivation categories influence college students’ learning engagement behaviors and outcomes under the context of eastern culture. 178 junior college students were surveyed at a four-year research university in Taiwan. The study addressed two research questions: 1. Are there subgroups of students with significantly different motivation profiles? 2. If so, do these subgroups of students differ significantly in terms of their engagement behaviors and learning o...

Conception and validation of the Behavioral Intentions Scale of Organizational Citizenship (BISOC

Directory of Open Access Journals (Sweden)

Ana Cristina Passos Gomes Menezes

2016-01-01

Full Text Available Abstract This study aimed to construct and validate the Behavioral Intentions of Organizational Citizenship Scale (BISOC. Organizational citizenship consists of measures of voluntary behaviors, which are beneficial to organizations and are not explicit in employment contracts. To investigate the psychometric properties of BISOC, we selected 767 employees in different cities from the states of Bahia and Pernambuco (Brazil. The validation procedures adopted, which used techniques from both Classical Test Theory and Item Response Theory, showed that the BISOC has a unidimensional structure. From the initial set of 42 items, 35 items met the validation criteria. By presenting suitable psychometric parameters, BISOC is the first measure of organizational citizenship behaviors developed and validated to assess behavioral intentions.

Using the Personality Assessment Inventory Antisocial and Borderline Features Scales to Predict Behavior Change.

Science.gov (United States)

Penson, Brittany N; Ruchensky, Jared R; Morey, Leslie C; Edens, John F

2016-11-01

A substantial amount of research has examined the developmental trajectory of antisocial behavior and, in particular, the relationship between antisocial behavior and maladaptive personality traits. However, research typically has not controlled for previous behavior (e.g., past violence) when examining the utility of personality measures, such as self-report scales of antisocial and borderline traits, in predicting future behavior (e.g., subsequent violence). Examination of the potential interactive effects of measures of both antisocial and borderline traits also is relatively rare in longitudinal research predicting adverse outcomes. The current study utilizes a large sample of youthful offenders ( N = 1,354) from the Pathways to Desistance project to examine the separate effects of the Personality Assessment Inventory Antisocial Features (ANT) and Borderline Features (BOR) scales in predicting future offending behavior as well as trends in other negative outcomes (e.g., substance abuse, violence, employment difficulties) over a 1-year follow-up period. In addition, an ANT × BOR interaction term was created to explore the predictive effects of secondary psychopathy. ANT and BOR both explained unique variance in the prediction of various negative outcomes even after controlling for past indicators of those same behaviors during the preceding year.

Validity and reliability analysis of the planned behavior theory scale related to the testicular self-examination in a Turkish context.

Science.gov (United States)

Iyigun, Emine; Tastan, Sevinc; Ayhan, Hatice; Kose, Gulsah; Acikel, Cengizhan

2016-06-01

This study aimed to determine the validity and reliability levels of the Planned Behavior Theory Scale as related to a testicular self-examination. The study was carried out in a health-profession higher-education school in Ankara, Turkey, from April to June 2012. The study participants comprised 215 male students. Study data were collected by using a questionnaire, a planned behavior theory scale related to testicular self-examination, and Champion's Health Belief Model Scale (CHBMS). The sub-dimensions of the planned behavior theory scale, namely those of intention, attitude, subjective norms and self-efficacy, were found to have Cronbach's alpha values of between 0.81 and 0.89. Exploratory factor analysis showed that items of the scale had five factors that accounted for 75% of the variance. Of these, the sub-dimension of intention was found to have the highest level of contribution. A significant correlation was found between the sub-dimensions of the testicular self-examination planned behavior theory scale and those of CHBMS (p Planned Behavior Theory Scale is a valid and reliable measurement for Turkish society.

[The relationships among self-identity, self-esteem and attitude towards sexual behavior in university students].

Science.gov (United States)

Kuno, Takako; Tachi, Etsuko; Ogasawara, Akihiko; Shimokata, Hiroshi; Yamaguchi, Yoko

2002-10-01

"communication ability," "learning ability," and "acquisition ability." Significant differences were found in total and "Establishment" scales among males, and all scales among females. The score on the Rosenberg Self-Esteem Scale was significantly higher with "learning ability" among males, and with "communication ability" and "learning ability" among females. However, no significant relationship was found between actual contraceptive behavior and any of the scales. In dealing with contraception, a gap exists between university students' attitudes and actual behavior. The scores on the "Establishment of Self" scale and the Rosenberg Self-Esteem Scale were found to be significantly higher for those who exhibited higher values for components of contraceptive behavior.

MD Simulation on Collision Behavior Between Nano-Scale TiO₂ Particles During Vacuum Cold Spraying.

Science.gov (United States)

Yao, Hai-Long; Yang, Guan-Jun; Li, Chang-Jiu

2018-04-01

Particle collision behavior influences significantly inter-nano particle bonding formation during the nano-ceramic coating deposition by vacuum cold spraying (or aerosol deposition method). In order to illuminate the collision behavior between nano-scale ceramic particles, molecular dynamic simulation was applied to explore impact process between nano-scale TiO2 particles through controlling impact velocities. Results show that the recoil efficiency of the nano-scale TiO2 particle is decreased with the increase of the impact velocity. Nano-scale TiO2 particle exhibits localized plastic deformation during collision at low velocities, while it is intensively deformed by collision at high velocities. This intensive deformation promotes the nano-particle adhesion rather than rebounding off. A relationship between the adhesion energy and the rebound energy is established for the bonding formation of the nano-scale TiO2 particle. The adhesion energy required to the bonding formation between nano-scale ceramic particles can be produced by high velocity collision.

Capability Building and Learning: An Emergent Behavior Approach

Directory of Open Access Journals (Sweden)

Andreu Rafael

2014-12-01

Full Text Available Economics-based models of firms typically overlook management acts and capability development. We propose a model that analyzes the aggregate behavior of a population of firms resulting from both specific management decisions and learning processes, that induce changes in companies’ capabilities. Decisions are made under imperfect information and bounded rationality, and managers may sacrifice short-term performance in exchange for qualitative outcomes that affect their firm’s future potential. The proposed model provides a structured setting in which these issues -often discussed only informally- can be systematically analyzed through simulation, producing a variety of hard-to-anticipate emergent behaviors. Economic performance is quite sensitive to managers’ estimates of their firms’ capabilities, and companies willing to sacrifice short-run results for future potential appear to be more stable than the rest. Also, bounded rationality can produce chaotic dynamics reminiscent of real life situations.

Modeling eating behaviors: The role of environment and positive food association learning via a Ratatouille effect.

Science.gov (United States)

Murillo, Anarina L; Safan, Muntaser; Castillo-Chavez, Carlos; Phillips, Elizabeth D Capaldi; Wadhera, Devina

2016-08-01

Eating behaviors among a large population of children are studied as a dynamic process driven by nonlinear interactions in the sociocultural school environment. The impact of food association learning on diet dynamics, inspired by a pilot study conducted among Arizona children in Pre-Kindergarten to 8th grades, is used to build simple population-level learning models. Qualitatively, mathematical studies are used to highlight the possible ramifications of instruction, learning in nutrition, and health at the community level. Model results suggest that nutrition education programs at the population-level have minimal impact on improving eating behaviors, findings that agree with prior field studies. Hence, the incorporation of food association learning may be a better strategy for creating resilient communities of healthy and non-healthy eaters. A Ratatouille effect can be observed when food association learners become food preference learners, a potential sustainable behavioral change, which in turn, may impact the overall distribution of healthy eaters. In short, this work evaluates the effectiveness of population-level intervention strategies and the importance of institutionalizing nutrition programs that factor in economical, social, cultural, and environmental elements that mesh well with the norms and values in the community.

Partially satisfied to fully satisfied transitions in co-evolving inverse voter model and possible scaling behavior

International Nuclear Information System (INIS)

Choi, C.W.; Xu, C.; Hui, P.M.

2015-01-01

Understanding co-evolving networks characterized by the mutual influence of agents' actions and network structure remains a challenge. We study a co-evolving inverse voter model in which agents adapt to achieve a preferred environment with more opposite-opinion neighbors by rewiring their connections and switching opinion. Numerical studies reveal a transition from a dynamic partially satisfied phase to a frozen fully satisfied phase as the rewiring probability is varied. A simple mean field theory is shown to capture the behavior only qualitatively. An improved mean field theory carrying a longer spatial correlation gives better results. Motivated by numerical results in networks of different degrees and mean field results, we propose a scaling variable that combines the rewiring probability and mean degree in a special form. The scaling variable is shown to work well in analyzing data corresponding to different networks and different rewiring probabilities. An application is to predict the results for networks of different degrees based solely on results obtained from networks of one degree. Studying scaling behavior provides an alternative path for understanding co-evolving agent-based dynamical systems, especially in light of the trade-off between complexity of a theory and its accuracy. - Highlights: • Identified key features and phase transitions in coevolving inverse voter model. • Constructed a better theory incorporating longer spatial correlation. • Proposed scaling variable and illustrated possible scaling behavior. • Used scaling behavior to predict results of IVM in a different network.

Learning to Eat: Behavioral and Psychological Aspects.

Science.gov (United States)

Birch, Leann L

2016-01-01

Because infants are totally dependent upon parents (or other caregivers) for care and sustenance, parents' feeding practices are a key feature of the family environments in which infants and young children learn about food and eating. Feeding practices include not only what the child is fed, but also the how, when, why and how much of feeding. Extensive evidence indicates that parenting behavior influences a variety of child outcomes, including cognitive and socioemotional development, as well as the development of self-regulatory skills. The focus of this chapter is on what is known about how parenting, particularly feeding practices, influences the early development of several aspects of children's eating behavior, including the acquisition of food preferences, self-regulatory skills, children's reactivity to food cues, satiety responsiveness and 'picky eating'. It is argued that traditional feeding practices, which evolved to protect children from environmental threats and ensure adequate intake in the context of food scarcity, can be maladaptive in current environments. An evidence base is needed to inform public policy to reduce early obesity risk in current environments, where too much palatable food is a major threat to child health. Results of recent research provides evidence that promoting responsive feeding practices can alter the development of eating behavior, sleep patterns and early self-regulatory skills, as well as reduce early obesity risk. © 2016 Nestec Ltd., Vevey/S. Karger AG, Basel.

A fast learning method for large scale and multi-class samples of SVM

Science.gov (United States)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.

Social Interaction in Infants' Learning of Second-Language Phonetics: An Exploration of Brain-Behavior Relations.

Science.gov (United States)

Conboy, Barbara T; Brooks, Rechele; Meltzoff, Andrew N; Kuhl, Patricia K

2015-01-01

Infants learn phonetic information from a second language with live-person presentations, but not television or audio-only recordings. To understand the role of social interaction in learning a second language, we examined infants' joint attention with live, Spanish-speaking tutors and used a neural measure of phonetic learning. Infants' eye-gaze behaviors during Spanish sessions at 9.5-10.5 months of age predicted second-language phonetic learning, assessed by an event-related potential measure of Spanish phoneme discrimination at 11 months. These data suggest a powerful role for social interaction at the earliest stages of learning a new language.

Large-scale experiments on aerosol behavior in light water reactor containments

International Nuclear Information System (INIS)

Schock, W.; Bunz, H.; Adams, R.E.; Tobias, M.L.; Rahn, F.J.

1988-01-01

Recently, three large-scale experimental programs were carried out dealing with the behavior of aerosols during core-melt accidents in light water reactors (LWRs). In the Nuclear Safety Pilot Plant (NSPP) program, the principal behaviors of different insoluble aerosols and of mixed aerosols were measured in dry air atmospheres and in condensing steam-air atmospheres contained in a 38-m/sup 3/ steel vessel. The Demonstration of Nuclear Aerosol Behavior (DEMONA) program used a 640-m/sup 3/ concrete containment model to simulate typical accident sequence conditions, and measured the behavior of different insoluble aerosols and mixed aerosols in condensing and transient atmospheric conditions. Part of the LWR Aerosol Containment Experiments (LACE) program was also devoted to aerosol behavior in containment; and 852-m/sup 3/ steel vessel was used, and the aerosols were composed of mixtures of insoluble and soluble species. The results of these experiments provide a suitable data base for validation of aerosol behavior codes. Fundamental insight into details of aerosol behavior in condensing environments has been gained through the results of the NSPP tests. Code comparisons have been and are being performed in the DEMONA and LACE experiments

Chemically intuited, large-scale screening of MOFs by machine learning techniques

Science.gov (United States)

Borboudakis, Giorgos; Stergiannakos, Taxiarchis; Frysali, Maria; Klontzas, Emmanuel; Tsamardinos, Ioannis; Froudakis, George E.

2017-10-01

A novel computational methodology for large-scale screening of MOFs is applied to gas storage with the use of machine learning technologies. This approach is a promising trade-off between the accuracy of ab initio methods and the speed of classical approaches, strategically combined with chemical intuition. The results demonstrate that the chemical properties of MOFs are indeed predictable (stochastically, not deterministically) using machine learning methods and automated analysis protocols, with the accuracy of predictions increasing with sample size. Our initial results indicate that this methodology is promising to apply not only to gas storage in MOFs but in many other material science projects.

Copy of Using Emulation and Simulation to Understand the Large-Scale Behavior of the Internet.

Energy Technology Data Exchange (ETDEWEB)

Adalsteinsson, Helgi; Armstrong, Robert C.; Chiang, Ken; Gentile, Ann C.; Lloyd, Levi; Minnich, Ronald G.; Vanderveen, Keith; Van Randwyk, Jamie A; Rudish, Don W.

2008-10-01

We report on the work done in the late-start LDRDUsing Emulation and Simulation toUnderstand the Large-Scale Behavior of the Internet. We describe the creation of a researchplatform that emulates many thousands of machines to be used for the study of large-scale inter-net behavior. We describe a proof-of-concept simple attack we performed in this environment.We describe the successful capture of a Storm bot and, from the study of the bot and furtherliterature search, establish large-scale aspects we seek to understand via emulation of Storm onour research platform in possible follow-on work. Finally, we discuss possible future work.3

English Learning Achievement and EFL Learners' Cheating Attitudes and Cheating Behaviors

Science.gov (United States)

Rahim, Mehrak; Goli, Atefeh

2016-01-01

The aim of the current study was investigating the role of achievement in learning English as a foreign language in EFL learners' cheating attitudes and cheating behaviors. Eight hundred junior high-school students were selected based on random cluster sampling and participated in the study. Their attitudes towards academic dishonesty and their…

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality.

Science.gov (United States)

Li, Zhongyu; Butler, Erik; Li, Kang; Lu, Aidong; Ji, Shuiwang; Zhang, Shaoting

2018-02-12

Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i.e., stacked convolutional autoencoders (SCAEs). The deep features are subsequently fused with the hand-crafted features for more accurate representation. Considering the exhaustive search is usually very time-consuming in large-scale databases, we employ a novel binary coding method to compress feature vectors into short binary codes. Our framework is validated on a public data set including 58,000 neurons, showing promising retrieval precision and efficiency compared with state-of-the-art methods. In addition, we develop a novel neuron visualization program based on the techniques of augmented reality (AR), which can help users take a deep exploration of neuron morphologies in an interactive and immersive manner.

Behavioral evidence for differences in social and non-social category learning

Directory of Open Access Journals (Sweden)

Lucile eGamond

2012-08-01

Full Text Available When meeting someone for the very first time one spontaneously categorizes the seen person on the basis of his/her appearance. Categorization is based on the association between some physical features and category labels that can be social (character trait… or non-social (tall, thin. Surprisingly little is known about how such associations are formed, particularly in the social domain. Here, we aimed at testing whether social and non-social category learning may be dissociated. We presented subjects with a large number of faces that had to be rated according to social or non-social labels, and induced an association between a facial feature (inter-eye distance and the category labels using two different procedures. In a first experiment, we used a feedback procedure to reinforce the association; behavioral measures revealed an association between the physical feature manipulated and abstract non-social categories, while no evidence for an association with social labels could be found. In a second experiment, we used passive exposure to the association between physical features and labels; we obtained behavioral evidence for learning of both social and non-social categories. These results support the view of the specificity of social category learning; they suggest that social categories are best acquired through unsupervised procedures that can be considered as a simplified proxy for group transmission.

A Systematic Review and Psychometric Evaluation of Adaptive Behavior Scales and Recommendations for Practice

Science.gov (United States)

Floyd, Randy G.; Shands, Elizabeth I.; Alfonso, Vincent C.; Phillips, Jessica F.; Autry, Beth K.; Mosteller, Jessica A.; Skinner, Mary; Irby, Sarah

2015-01-01

Adaptive behavior scales are vital in assessing children and adolescents who experience a range of disabling conditions in school settings. This article presents the results of an evaluation of the design characteristics, norming, scale characteristics, reliability and validity evidence, and bias identification studies supporting 14…

The Costly Consequences of not Being Socially and Behaviorally Ready to Learn by Kindergarten in Baltimore City.

Science.gov (United States)

Bettencourt, Amie F; Gross, Deborah; Ho, Grace; Perrin, Nancy

2018-02-01

Social, emotional, and behavioral skills are foundational to learning and long-term success. However, poverty and exposure to adverse childhood experiences reduce the chances of children entering kindergarten socially-behaviorally ready to learn. This study examined the unique impact of 5-year-old children (N = 11,412) entering kindergarten not socially-behaviorally ready on three costly school outcomes by fourth grade in Baltimore City Public Schools: being retained in grade, receiving services and supports through an IEP or 504 plan, and being suspended/expelled. Controlling for all other types of school readiness, students not identified as socially-behaviorally ready for kindergarten were more likely to experience all three school outcomes. Findings underscore the importance of early prevention and intervention strategies targeting parents and social-behavioral readiness skills during the first 5 years of life.

Development and preliminary psychometric properties of the multidimensional neglectful behavior scale-child report.

Science.gov (United States)

Kantor, Glenda Kaufman; Holt, Melissa K; Mebert, Carolyn J; Straus, Murray A; Drach, Kerry M; Ricci, Lawrence R; MacAllum, Crystal A; Brown, Wendy

2004-11-01

This article describes the development and psychometric properties of the Multidimensional Neglectful Behavior Scale-Child Report (MNBS-CR). The measure is broadly conceptualized to tap child neglect across four core domains: cognitive, emotional, physical and supervisory neglect, and it assesses exposure to violence, alcohol-related neglect, abandonment, and children's appraisals of parenting. Features include pictorial items, audio computer-assisted testing, and programming by age and gender of the child and caregiver. A clinical sample of 144 children, age 6 to 15 years, and a comparison sample of 87 children were tested. Results showed that the MNBS-CR has high reliability, with higher reliability found for older children (alpha = .94) than for younger children (alpha = .66). Among older children, the MNBS-CR Supervisory scale was significantly associated with the Child Behavior Check List (CBCL), and total MNBS-CR scores were significantly associated with clinician reports of behavioral disorders. Younger and older neglected children scored significantly higher on the MNBS-CR than community children.

Astrocytic IL-6 mediates locomotor activity, exploration, anxiety, learning and social behavior.

Science.gov (United States)

Erta, Maria; Giralt, Mercedes; Esposito, Flavia Lorena; Fernandez-Gayol, Olaya; Hidalgo, Juan

2015-07-01

Interleukin-6 (IL-6) is a major cytokine in the central nervous system, secreted by different brain cells and with roles in a number of physiological functions. We herewith confirm and expand the importance of astrocytic production of and response to IL-6 by using transgenic mice deficient in astrocytic IL-6 (Ast-IL-6 KO) or in its receptor (Ast-IL-6R KO) in full C57Bl/6 genetic background. A major prosurvival effect of astrocytic IL-6 at early ages was clearly demonstrated. Robust effects were also evident in the control of activity and anxiety in the hole-board and elevated plus-maze, and in spatial learning in the Morris water-maze. The results also suggest an inhibitory role of IL-6 in the mechanism controlling the consolidation of hippocampus-dependent spatial learning. Less robust effects of astrocytic IL-6 system were also observed in despair behavior in the tail suspension test, and social behavior in the dominance and resident-intruder tests. The behavioral phenotype was highly dependent on age and/or sex in some cases. The phenotype of Ast-IL-6R KO mice mimicked only partially that of Ast-IL-6KO mice, which indicates both a role of astrocytes in behavior and the participation of other cells besides astrocytes. No evidences of altered function of the hypothalamic-pituitary-adrenal axis were observed. These results demonstrate that astrocytic IL-6 (acting at least partially in astrocytes) regulates normal behavior in mice. Copyright © 2015 Elsevier Inc. All rights reserved.

Grounding the meanings in sensorimotor behavior using reinforcement learning

Directory of Open Access Journals (Sweden)

Igor eFarkaš

2012-02-01

Full Text Available The recent outburst of interest in cognitive developmental robotics is fueled by the ambition to propose ecologically plausible mechanisms of how, among other things, a learning agent/robot could ground linguistic meanings in its sensorimotor behaviour. Along this stream, we propose a model that allows the simulated iCub robot to learn the meanings of actions (point, touch and push oriented towards objects in robot's peripersonal space. In our experiments, the iCub learns to execute motor actions and comment on them. Architecturally, the model is composed of three neural-network-based modules that are trained in different ways. The first module, a two-layer perceptron, is trained by back-propagation to attend to the target position in the visual scene, given the low-level visual information and the feature-based target information. The second module, having the form of an actor-critic architecture, is the most distinguishing part of our model, and is trained by a continuous version of reinforcement learning to execute actions as sequences, based on a linguistic command. The third module, an echo-state network, is trained to provide the linguistic description of the executed actions. The trained model generalises well in case of novel action-target combinations with randomised initial arm positions. It can also promptly adapt its behavior if the action/target suddenly changes during motor execution.

Test-retest reliability of the Clinical Learning Environment, Supervision and Nurse Teacher (CLES + T) scale.

Science.gov (United States)

Gustafsson, Margareta; Blomberg, Karin; Holmefur, Marie

2015-07-01

The Clinical Learning Environment, Supervision and Nurse Teacher (CLES + T) scale evaluates the student nurses' perception of the learning environment and supervision within the clinical placement. It has never been tested in a replication study. The aim of the present study was to evaluate the test-retest reliability of the CLES + T scale. The CLES + T scale was administered twice to a group of 42 student nurses, with a one-week interval. Test-retest reliability was determined by calculations of Intraclass Correlation Coefficients (ICCs) and weighted Kappa coefficients. Standard Error of Measurements (SEM) and Smallest Detectable Difference (SDD) determined the precision of individual scores. Bland-Altman plots were created for analyses of systematic differences between the test occasions. The results of the study showed that the stability over time was good to excellent (ICC 0.88-0.96) in the sub-dimensions "Supervisory relationship", "Pedagogical atmosphere on the ward" and "Role of the nurse teacher". Measurements of "Premises of nursing on the ward" and "Leadership style of the manager" had lower but still acceptable stability (ICC 0.70-0.75). No systematic differences occurred between the test occasions. This study supports the usefulness of the CLES + T scale as a reliable measure of the student nurses' perception of the learning environment within the clinical placement at a hospital. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Interview with Joe McMann: Lessons Learned from Fifty Years of Observing Hardware and Human Behavior