Harnessing AI for peer-to-peer learning support: Insights from a bibliometric analysis

Abstract

This study investigates the current use of artificial intelligence (AI) for peer-to-peer support through a bibliometric analysis of 1113 records based on co-words. The research employs a four-phase exploratory design that involves co-word search, data charting, and result summation. It uses an inductive, relevant, and reflexive thematic approach (TA). The theoretical foundation is grounded in retention, attrition, and learning theories, including personal, social, emotional, constructive, and humanistic theories. The analysis aims to determine whether institutions leverage AI for peer-to-peer learning as part of peer support. The findings reveal a significant gap in direct research on AI's role in peer-to-peer support, underscoring the need for future studies on its impact on learning customisation, socio-emotional learning, and ethical issues in education.

Keywords

• Academic achievement
• Artificial Intelligence
• Student Retention
• Attrition
• Socio-emotional Learning
• Personalised Learning