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Winchell, Adam; Mozer, Michael; Lan, Andrew; Grimaldi, Phillip; Pashler, Harold – International Educational Data Mining Society, 2018
When engaging with a textbook, students are inclined to highlight key content. Although students believe that highlighting and subsequent review of the highlights will further their educational goals, the psychological literature provides no evidence of benefits. Nonetheless, a student's choice of text for highlighting may serve as a window into…
Descriptors: Textbooks, Biology, Documentation, Science Instruction
DiCerbo, Kristen – Learning, Media and Technology, 2016
The volume of data that can be captured and stored from students' everyday interactions with digital environments allows for the creation of models of student knowledge, skills, and attributes unobtrusively. However, models and techniques for transforming these data into information that is useful for educators have not been established. This…
Descriptors: Bayesian Statistics, Educational Technology, Electronic Learning, Learning Processes
Skewes, Joshua C.; Gebauer, Line – Journal of Autism and Developmental Disorders, 2016
Convergent research suggests that people with ASD have difficulties localizing sounds in space. These difficulties have implications for communication, the development of social behavior, and quality of life. Recently, a theory has emerged which treats perceptual symptoms in ASD as the product of impairments in implicit Bayesian inference; as…
Descriptors: Autism, Pervasive Developmental Disorders, Auditory Perception, Bayesian Statistics
Longford, Nicholas Tibor – Journal of Educational and Behavioral Statistics, 2016
We address the problem of selecting the best of a set of units based on a criterion variable, when its value is recorded for every unit subject to estimation, measurement, or another source of error. The solution is constructed in a decision-theoretical framework, incorporating the consequences (ramifications) of the various kinds of error that…
Descriptors: Decision Making, Classification, Guidelines, Undergraduate Students
Liu, Haiyan; Zhang, Zhiyong; Grimm, Kevin J. – Grantee Submission, 2016
Growth curve modeling provides a general framework for analyzing longitudinal data from social, behavioral, and educational sciences. Bayesian methods have been used to estimate growth curve models, in which priors need to be specified for unknown parameters. For the covariance parameter matrix, the inverse Wishart prior is most commonly used due…
Descriptors: Bayesian Statistics, Computation, Statistical Analysis, Growth Models
Kim, Dan; Opfer, John E. – Developmental Psychology, 2017
Representations of numerical value have been assessed by using bounded (e.g., 0-1,000) and unbounded (e.g., 0-?) number-line tasks, with considerable debate regarding whether 1 or both tasks elicit unique cognitive strategies (e.g., addition or subtraction) and require unique cognitive models. To test this, we examined how well a mixed log-linear…
Descriptors: Computation, Numbers, Children, Cognitive Development
Moore, Paula Hearn; Griffin, Richard B. – Journal of Academic Administration in Higher Education, 2017
This paper describes and compares the profiles of the top accounting programs in the United States as identified by "U.S. News and World Report" in 2004 with the profiles of the top accounting programs in the United States as identified by the "Accounting Degree Review" in 2014. The "Accounting Degree Review"'s list…
Descriptors: Accounting, Course Evaluation, Undergraduate Study, Bayesian Statistics
Gagliardi, Annie; Feldman, Naomi H.; Lidz, Jeffrey – Cognitive Science, 2017
Children acquiring languages with noun classes (grammatical gender) have ample statistical information available that characterizes the distribution of nouns into these classes, but their use of this information to classify novel nouns differs from the predictions made by an optimal Bayesian classifier. We use rational analysis to investigate the…
Descriptors: Children, Statistics, Learning, Bayesian Statistics
Martin-Fernandez, Manuel; Revuelta, Javier – Psicologica: International Journal of Methodology and Experimental Psychology, 2017
This study compares the performance of two estimation algorithms of new usage, the Metropolis-Hastings Robins-Monro (MHRM) and the Hamiltonian MCMC (HMC), with two consolidated algorithms in the psychometric literature, the marginal likelihood via EM algorithm (MML-EM) and the Markov chain Monte Carlo (MCMC), in the estimation of multidimensional…
Descriptors: Bayesian Statistics, Item Response Theory, Models, Comparative Analysis
Braem, Senne; Liefooghe, Baptist; De Houwer, Jan; Brass, Marcel; Abrahamse, Elger L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
Unlike other animals, humans have the unique ability to share and use verbal instructions to prepare for upcoming tasks. Recent research showed that instructions are sufficient for the automatic, reflex-like activation of responses. However, systematic studies into the limits of these automatic effects of task instructions remain relatively…
Descriptors: Responses, Context Effect, Visual Stimuli, Performance
Polanin, Joshua R.; Hennessy, Emily A.; Tanner-Smith, Emily E. – Journal of Educational and Behavioral Statistics, 2017
Meta-analysis is a statistical technique that allows an analyst to synthesize effect sizes from multiple primary studies. To estimate meta-analysis models, the open-source statistical environment R is quickly becoming a popular choice. The meta-analytic community has contributed to this growth by developing numerous packages specific to…
Descriptors: Meta Analysis, Open Source Technology, Computer Software, Effect Size
Washburn, Jeanne – ProQuest LLC, 2017
In order to remain competitive, higher education institutions must be prepared to acculturate adjunct faculty to their mission and instructional philosophy (Bojarczyk, 2008). They must also develop programs that support and engage adjunct faculty (Blodgett, 2008; Landers, 2012). The purpose of this study was to analyze and describe differences…
Descriptors: Adjunct Faculty, Needs Assessment, Comparative Analysis, Acculturation
Choi, Kilchan; Kim, Jinok – Journal of Educational and Behavioral Statistics, 2019
This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of…
Descriptors: Regression (Statistics), Hierarchical Linear Modeling, Longitudinal Studies, Cohort Analysis
Lang, Charles – Journal of Learning Analytics, 2014
This article proposes a coherent framework for the use of Inverse Bayesian estimation to summarize and make predictions about student behaviour in adaptive educational settings. The Inverse Bayes Filter utilizes Bayes theorem to estimate the relative impact of contextual factors and internal student factors on student performance using time series…
Descriptors: Bayesian Statistics, Academic Achievement, Prediction, Student Behavior
López Puga, Jorge – Teaching Statistics: An International Journal for Teachers, 2014
The aprioristic (classical, naïve and symmetric) and frequentist interpretations of probability are commonly known. Bayesian or subjective interpretation of probability is receiving increasing attention. This paper describes an activity to help students differentiate between the three types of probability interpretations.
Descriptors: Probability, Bayesian Statistics, Data Interpretation, Instructional Materials

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