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The Impact of AI on the Personal and Collaborative Learning Environments in Higher Education.

  • Published In: European Journal of Education, 2025, v. 60, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Msambwa, Msafiri Mgambi; Wen, Zhang; Daniel, Kangwa 3 of 3

Abstract

Artificial intelligence (AI) has extensively developed, impacting different sectors of society, including higher education, and has attracted the attention of various educational stakeholders, leading to a growing number of research on its integration into education. Hence, this systematic literature review examines the impact of integrating AI tools in higher education on students' personal and collaborative learning environments. Analysis of 148 articles published between 2021 and 2024 indicates that AI Tools improve personalised learning and assessments, communication and engagement, and scaffolding performance and motivation. Additionally, they promote a collaborative learning environment by providing peer‐learning opportunities, enhanced learner‐content interaction and cooperative learning support. Indeed, strategies such as skills development, ethical use, academic integrity and instructional content design. Acknowledged limitations include ethical considerations, particularly privacy and bias, which require ongoing attention. Hence, it is recommended to create a good balance between AI‐mediated and human interaction in learning environments, a key area of future exploration. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:European Journal of Education. 2025/03, Vol. 60, Issue 1, p1
  • Document Type:Literature Review
  • Subject Area:Education
  • Publication Date:2025
  • ISSN:0141-8211
  • DOI:10.1111/ejed.12909
  • Accession Number:183654397
  • Copyright Statement:Copyright of European Journal of Education is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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