REVIEW article
Front. Educ.
Sec. Digital Learning Innovations
This article is part of the Research TopicArtificial Intelligence in Educational Technology: Innovations, Impacts, and Future DirectionsView all 8 articles
The Impact of Artificial Intelligence-based Learning Tools in Academic Innovation: A Review of Deep Seek, GPT, and Gemini (2020–2025)
Provisionally accepted
- 1Prince Sultan University, Riyadh, Saudi Arabia
- 2Soochow University, Suzhou, China
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Artificial Intelligence-based Learning Tools (AI-LTs) are rapidly reshaping higher education by advancing the learning, teaching, and administrative processes. This paper offers a systematic review of peer-reviewed research, published between 2020 and 2025, by examining the roles, advantages, and challenges of the AI-LTs like ChatGPT, Deep Seek, Gemini, and Meta AI. Using a qualitative method, relevant studies were sourced from databases such as Scopus and Web of Science, by using strict criteria for the selection and extraction of data. The review highlights that the AI-LTs can significantly improve the personalized learning experiences, boost the engagement of students, and streamline the administrative operations. However, they also introduce ethical challenges like algorithmic bias and risks to data privacy. The study underscores the importance of responsible adoption of AI, advocating for the development of faculty algorithmic transparency and the robust collaboration of human-AI. Future research should prioritize empirical investigations to further validate the influence of the AI-LTs across diverse academic environments.
Keywords: Artificial Intelligence-based Learning Tools, Academic innovation, personalized learning, algorithmic transparency, higher education
Received: 20 Aug 2025; Accepted: 05 Nov 2025.
Copyright: © 2025 Younas, El-Dakhs and Noor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Muhammad Younas, myounas@psu.edu.sa
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