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Geden, Michael; Emerson, Andrew; Carpenter, Dan; Rowe, Jonathan; Azevedo, Roger; Lester, James – International Journal of Artificial Intelligence in Education, 2021
Game-based learning environments are designed to provide effective and engaging learning experiences for students. Predictive student models use trace data extracted from students' in-game learning behaviors to unobtrusively generate early assessments of student knowledge and skills, equipping game-based learning environments with the capacity to…
Descriptors: Game Based Learning, Middle School Students, Microbiology, Secondary School Science
Dever, Daryn A.; Azevedo, Roger; Cloude, Elizabeth B.; Wiedbusch, Megan – International Journal of Artificial Intelligence in Education, 2020
Game-based learning environments (GBLEs) focus on enhancing learning by providing learners with various representations of information (e.g., text, diagrams, etc.) while allowing full autonomy, or control over their actions. Challenges arise as research shows that learners inaccurately use cognitive and metacognitive processes when given full…
Descriptors: Game Based Learning, Personal Autonomy, Undergraduate Students, Eye Movements
Taub, Michelle; Sawyer, Robert; Lester, James; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2020
The goal of this study was to examine college students' (n = 61) contextualized emotions during in-game actions while playing "Crystal Island," a game-based learning environment where students are tasked with solving the mystery of what illness impacted all island inhabitants. We examined emotions during in-game actions: during book…
Descriptors: Psychological Patterns, Independent Study, Logical Thinking, Game Based Learning
Taub, Michelle; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2019
The goal of this study was to use eye-tracking and log-file data to investigate the impact of prior knowledge on college students' (N = 194, with a subset of n = 30 for eye tracking and sequence mining analyses) fixations on (i.e., looking at) self-regulated learning-related areas of interest (i.e., specific locations on the interface) and on the…
Descriptors: Prior Learning, Eye Movements, Metacognition, Learning Processes
Lintean, Mihai; Rus, Vasile; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2012
This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…
Descriptors: Semantics, Intelligent Tutoring Systems, Prior Learning, Mathematics