Content area
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.
Details
Active Learning;
Grading;
Innovation;
Cooperative Learning;
Case Studies;
Interpersonal Relationship;
Educational Objectives;
Artificial Intelligence;
Individual Differences;
Educational Assessment;
Educational Environment;
Educational Strategies;
Control Groups;
Influence of Technology;
Experimental Groups;
Educational Technology;
Class Size;
Instructional Materials;
Educational Change;
Correlation;
Feedback (Response);
Accuracy;
Emotional Response;
Higher Education
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
1 Wageningen University and Research, Wageningen, The Netherlands (GRID:grid.4818.5) (ISNI:0000 0001 0791 5666)
2 University of Pittsburgh, Pittsburgh, USA (GRID:grid.21925.3d) (ISNI:0000 0004 1936 9000)
3 Harvard University, Massachusetts, USA (GRID:grid.38142.3c) (ISNI:0000 0004 1936 754X)
4 Open Universiteit, Heerlen, The Netherlands (GRID:grid.36120.36) (ISNI:0000 0004 0501 5439)