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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
Halim Acosta; Seung Lee; Haesol Bae; Chen Feng; Jonathan Rowe; Krista Glazewski; Cindy Hmelo-Silver; Bradford Mott; James C. Lester – International Journal of Artificial Intelligence in Education, 2025
Understanding students' multi-party epistemic and topic based-dialogue contributions, or how students present knowledge in group-based chat interactions during collaborative game-based learning, offers valuable insights into group dynamics and learning processes. However, manually annotating these contributions is labor-intensive and challenging.…
Descriptors: Game Based Learning, Artificial Intelligence, Technology Uses in Education, Cooperative Learning
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
Minji Jeon; Kathleen Jantaraweragul; Anne Ottenbreit-Leftwich; Cindy Hmelo-Silver; Krista Glazewski; Bradford Mott; James Lester; Cathy Ringstaff – International Journal of Designs for Learning, 2024
The PrimaryAI project focuses on developing an upper elementary integrated curriculum that covers life science, artificial intelligence (AI), and computer science concepts. The PrimaryAI curriculum uses both problem-based learning (PBL) and game-based learning (GBL) to engage students and situates the curriculum in a real-world context. The…
Descriptors: Inquiry, Artificial Intelligence, Technology Uses in Education, Elementary School Students

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