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Halim Acosta; Seung Lee; Daeun Hong; Wookhee Min; Bradford Mott; Cindy Hmelo-Silver; James Lester – International Educational Data Mining Society, 2025
Understanding the relationship between student behaviors and learning outcomes is crucial for designing effective collaborative learning environments. However, collaborative learning analytics poses significant challenges, not only due to the complex interplay between collaborative problem-solving and collaborative dialogue but also due to the…
Descriptors: Learning Analytics, Cooperative Learning, Student Behavior, Prediction
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Halim Acosta; Seung Lee; Bradford Mott; Haesol Bae; Krista Glazewski; Cindy Hmelo-Silver; James Lester – International Educational Data Mining Society, 2024
Collaborative game-based learning offers opportunities for students to participate in small group learning experiences that foster knowledge sharing, problem solving, and engagement. Student satisfaction with their collaborative experiences plays a pivotal role in shaping positive learning outcomes and is a critical factor in group success during…
Descriptors: Cooperative Learning, Game Based Learning, Learning Analytics, Prediction
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Nguyen, Huy Anh; Hou, Xinying; Stamper, John; McLaren, Bruce M. – International Educational Data Mining Society, 2020
A challenge in digital learning games is assessing students' learning behaviors, which are often intertwined with game behaviors. How do we know whether students have learned enough or needed more practice at the end of their game play? To answer this question, we performed post hoc analyses on a prior study of the game "Decimal Point,"…
Descriptors: Computer Games, Educational Games, Game Based Learning, Instructional Effectiveness