Content area

Abstract

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

1009240
Title
Advancing peer learning with learning analytics and artificial intelligence
Author
Noroozi, Omid 1 ; Schunn, Christian 2 ; Schneider, Bertrand 3 ; Banihashem, Seyyed Kazem 4 

 Wageningen University and Research, Wageningen, The Netherlands (GRID:grid.4818.5) (ISNI:0000 0001 0791 5666) 
 University of Pittsburgh, Pittsburgh, USA (GRID:grid.21925.3d) (ISNI:0000 0004 1936 9000) 
 Harvard University, Massachusetts, USA (GRID:grid.38142.3c) (ISNI:0000 0004 1936 754X) 
 Open Universiteit, Heerlen, The Netherlands (GRID:grid.36120.36) (ISNI:0000 0004 0501 5439) 
Volume
22
Issue
1
Pages
62
Publication year
2025
Publication date
Dec 2025
Publisher
Springer Nature B.V.
Place of publication
Heidelberg
Country of publication
Netherlands
e-ISSN
23659440
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-09-26
Milestone dates
2025-09-09 (Registration)
Publication history
 
 
   First posting date
26 Sep 2025
ProQuest document ID
3255891210
Document URL
https://www.proquest.com/scholarly-journals/advancing-peer-learning-with-analytics-artificial/docview/3255891210/se-2?accountid=208611
Copyright
© The Author(s) 2025. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-11-14
Database
2 databases
  • Education Research Index
  • ProQuest One Academic