Advancing peer learning with learning analytics and artificial intelligence

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Detalles Bibliográficos
Publicado en:	International Journal of Educational Technology in Higher Education vol. 22, no. 1 (Dec 2025), p. 62
Autor Principal:	Noroozi, Omid
Outros autores:	Schunn, Christian, Schneider, Bertrand, Banihashem, Seyyed Kazem
Publicado:	Springer Nature B.V.
Materias:	Students Technological change Literacy Feedback Teacher education Educational technology Learning activities Machine learning Virtual reality Education Teachers Effectiveness Learning analytics Collaborative learning Pedagogy Higher education Social network analysis Social networks Mathematics education Case studies Artificial intelligence Educational objectives Peers Mathematics teachers Gamification Learning processes Gestures Multimodality Learning Peer review Research design Peer assessment Cooperative learning Familiarity Uptake Ability Interdisciplinary aspects Social comparison Collaboration Innovations Discourse analysis Active Learning Grading Innovation Interpersonal Relationship Individual Differences Educational Assessment Educational Environment Educational Strategies Control Groups Influence of Technology Experimental Groups Class Size Instructional Materials Educational Change Correlation Feedback (Response) Accuracy Emotional Response
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Descripción
Resumo:	Peer learning is a promising instructional strategy, particularly in higher education, where increasing class sizes limits teachers’ abilities to effectively support students’ learning. However, its use in a traditional way is not always highly effective, due to, for example, students’ lack of familiarity with strategies such as peer feedback. Recent advancements in educational technologies, including learning analytics and artificial intelligence (AI), offer new pathways to support and enhance peer learning. This editorial introduces a special issue that examines how emerging educational technologies, specifically learning analytics, AI, and multimodal tools, can be thoughtfully integrated into peer learning to improve its effectiveness and outcomes. The six studies featured in this issue present key innovations, including the successful application of AI-supported peer assessment systems, multimodal learning analytics for analyzing collaborative gestures and discourse, gamified online platforms, social comparison feedback tools and dashboards, group awareness tools for collaborative learning, and behavioral indicators of peer feedback literacy. Collectively, these studies show how these technologies can scaffold peer learning processes, enrich the quality and uptake of peer feedback, foster engagement through gamification, promote reflective and collaborative learning, and address peer feedback literacy. However, the issue also identifies underexplored gaps, such as the short-term nature of many interventions, insufficient focus on the role of teachers, limited cultural and equity considerations, and a need for deeper theoretical integration. This editorial argues for a more pedagogically grounded, inclusive, and context-sensitive approach to technology-enhanced peer learning—one that foregrounds student agency, long-term impact, and interdisciplinary collaboration. The contributions of this special issue provide insights to guide future research, design, and practice in advancing peer learning through educational technologies.
ISSN:	2365-9440 1698-580X
DOI:	10.1186/s41239-025-00559-5
Fonte:	Political Science Database