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Norouzian, Reza; de Miranda, Michael; Plonsky, Luke – Language Learning, 2018
Frequentist methods have long dominated data analysis in quantitative second language (L2) research. Recently, however, several empirical fields have begun to embrace alternatives known as Bayesian methods. Using an open-source approach, we provide an applied, nontechnical rationale for Bayesian methods in L2 research. First, we compare the…
Descriptors: Second Language Learning, Language Research, Bayesian Statistics, Comparative Analysis
Bárcena, M. J.; Garín, M. A.; Martín, A.; Tusell, F.; Unzueta, A. – Journal of Statistics Education, 2019
Teaching some concepts in statistics greatly benefits from individual practice with immediate feedback. In order to provide such practice to a large number of students we have written a simulator based on an historical event: the loss in May 22, 1968, and subsequent search for the nuclear submarine USS Scorpion. Students work on a simplified…
Descriptors: Computer Simulation, Computer Assisted Instruction, Teaching Methods, Bayesian Statistics
Eadie, Gwendolyn; Huppenkothen, Daniela; Springford, Aaron; McCormick, Tyler – Journal of Statistics Education, 2019
We present an active-learning strategy for undergraduates that applies Bayesian analysis to candy-covered chocolate m&m's®. The exercise is best suited for small class sizes and tutorial settings, after students have been introduced to the concepts of Bayesian statistics. The exercise takes advantage of the nonuniform distribution of…
Descriptors: Undergraduate Students, Bayesian Statistics, Active Learning, Learning Activities
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
Wu, Mike; Davis, Richard L.; Domingue, Benjamin W.; Piech, Chris; Goodman, Noah – International Educational Data Mining Society, 2020
Item Response Theory (IRT) is a ubiquitous model for understanding humans based on their responses to questions, used in fields as diverse as education, medicine and psychology. Large modern datasets offer opportunities to capture more nuances in human behavior, potentially improving test scoring and better informing public policy. Yet larger…
Descriptors: Item Response Theory, Accuracy, Data Analysis, Public Policy
Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers