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Husni Almoubayyed; Stephen E. Fancsali; Steve Ritter – International Educational Data Mining Society, 2023
Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…
Descriptors: Prediction, Models, Reading Ability, Computer Software
Michelle P. Banawan; Jinnie Shin; Tracy Arner; Renu Balyan; Walter L. Leite; Danielle S. McNamara – Grantee Submission, 2023
Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities in how they construe and communicate meaning. This study examines the extent to which discourse…
Descriptors: Algebra, Discourse Analysis, Semantics, Syntax
Zheng, Guoguo; Fancsali, Stephen E.; Ritter, Steven; Berman, Susan R. – Journal of Learning Analytics, 2019
If we wish to embed assessment for accountability within instruction, we need to better understand the relative contribution of different types of learner data to statistical models that predict scores and discrete achievement levels on assessments used for accountability purposes. The present work scales up and extends predictive models of math…
Descriptors: Formative Evaluation, Predictor Variables, Summative Evaluation, Scores
Sahba Akhavan Niaki – ProQuest LLC, 2018
The increasing amount of available subjective text data in internet such as product reviews, movie critiques and social media comments provides golden opportunities for information retrieval researchers to extract useful information out of such datasets. Topic modeling and sentiment analysis are two widely researched fields that separately try to…
Descriptors: Models, Classification, Content Analysis, Documentation
Baker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
Sampson, Demetrios G., Ed.; Spector, J. Michael, Ed.; Ifenthaler, Dirk, Ed.; Isaias, Pedro, Ed. – International Association for Development of the Information Society, 2013
These proceedings contain the papers of the IADIS International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2013), October 22-24, 2013, which has been organized by the International Association for Development of the Information Society (IADIS), co-organized by The University of North Texas (UNT), sponsored by the…
Descriptors: Conference Papers, Cognitive Processes, Learning Processes, Short Term Memory