A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade

This review examines the current state of integration and impact of AI-enhanced collaborative learning in the higher education sector. Given the rapid advances in technology, AI has enormous potential for application in educational settings, with benefits in terms of personalizing learning, better e...

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Main Author: Attila Kovari
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Social Sciences and Humanities Open
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590291125000622
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author Attila Kovari
author_facet Attila Kovari
author_sort Attila Kovari
collection DOAJ
description This review examines the current state of integration and impact of AI-enhanced collaborative learning in the higher education sector. Given the rapid advances in technology, AI has enormous potential for application in educational settings, with benefits in terms of personalizing learning, better engaging learners and improving learning outcomes. Artificial intelligence tools, in particular machine learning, natural language processing and recommender algorithms, facilitate collaborative learning by enabling personalized learning through feedback and group work. Furthermore, this review concludes that predictive analytics and multimodal approaches supported by artificial intelligence have been shown to enhance student engagement and motivation, while personalized learning systems and recommender algorithms ensure the effectiveness of collaborative learning environments. It also identifies two other critical issues: good task design and effective emotional engagement and social presence in AI-based environments. In addition, it highlights some of the problems and ethical considerations arising from the integration of AI like transparency, data protection, and a balance between full automation and human touch. This review aims to integrate the current state and future opportunities of AI-enhanced collaborative learning within a higher education context to inform educators, researchers, and policy makers in pursuit of improving teaching and learning practices.
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spelling doaj-art-0c19f9d4bf9e4bf3a932ff7f6b45dd0c2025-08-20T03:30:45ZengElsevierSocial Sciences and Humanities Open2590-29112025-01-011110133510.1016/j.ssaho.2025.101335A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decadeAttila Kovari0Institute of Digital Technology, Faculty of Computer Science, Eszterházy Károly Catholic University, Eger, Hungary; Institute of Computer Engineering, University of Dunaújváros, Dunaújváros, Hungary; Institute of Electronics and Communication Systems, Kandó Kálmán Faculty of Electrical Engineering, Óbuda University, Budapest, Hungary; GAMF Faculty of Engineering and Computer Science, John von Neumann University, Kecskemét, Hungary; Corresponding author. Institute of Digital Technology, Faculty of Computer Science, Eszterházy Károly Catholic University, Eger, Hungary.This review examines the current state of integration and impact of AI-enhanced collaborative learning in the higher education sector. Given the rapid advances in technology, AI has enormous potential for application in educational settings, with benefits in terms of personalizing learning, better engaging learners and improving learning outcomes. Artificial intelligence tools, in particular machine learning, natural language processing and recommender algorithms, facilitate collaborative learning by enabling personalized learning through feedback and group work. Furthermore, this review concludes that predictive analytics and multimodal approaches supported by artificial intelligence have been shown to enhance student engagement and motivation, while personalized learning systems and recommender algorithms ensure the effectiveness of collaborative learning environments. It also identifies two other critical issues: good task design and effective emotional engagement and social presence in AI-based environments. In addition, it highlights some of the problems and ethical considerations arising from the integration of AI like transparency, data protection, and a balance between full automation and human touch. This review aims to integrate the current state and future opportunities of AI-enhanced collaborative learning within a higher education context to inform educators, researchers, and policy makers in pursuit of improving teaching and learning practices.http://www.sciencedirect.com/science/article/pii/S2590291125000622AI-Powered collaborative learningHigher educationPersonalized learningStudent engagementSocial presenceEducational outcomes
spellingShingle Attila Kovari
A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade
Social Sciences and Humanities Open
AI-Powered collaborative learning
Higher education
Personalized learning
Student engagement
Social presence
Educational outcomes
title A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade
title_full A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade
title_fullStr A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade
title_full_unstemmed A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade
title_short A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade
title_sort systematic review of ai powered collaborative learning in higher education trends and outcomes from the last decade
topic AI-Powered collaborative learning
Higher education
Personalized learning
Student engagement
Social presence
Educational outcomes
url http://www.sciencedirect.com/science/article/pii/S2590291125000622
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