Cited by 63Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in EducationArtificial Intelligence in Healthcare and Education

A Comprehensive Systematic Review of AI-Driven Approaches to Self-Directed Learning

Open access
Younas, Muhammad, Abdel Salam El-Dakhs, Dina, Jiang, Yicun·2025·IEEE Access

Abstract

Artificial intelligence (AI)-enhanced technologies are increasingly being researched and applied in learning and instruction. Previous studies have demonstrated the growing influence of AI tools in improving learning outcomes and transforming the educational landscape. However, limited research has explored learners’ engagement with AI resources to support self-directed learning, and no comprehensive review exists in this context. This study conducts a systematic review to examine the potential directions underlying the use of AI-enabled resources to assist learners in self-directed learning. The review targeted articles from high-profile databases such as Web of Science and ScienceDirect. A range of AI resources, including intelligent tutoring systems and conversational agents, were identified in the reviewed articles for their roles in providing personalized learning support, question-answering assistance, timely feedback, action recommendations, and interactive learning experiences that foster self-directed learning aspirations. The review also demonstrated that AI-supported self-directed learning can have a positive effect on the satisfaction of learners’ autonomy and competence needs. Besides that, prior knowledge of the learners acts as a facilitator for the continued use of AI resources, thereby positively affecting the outcomes of self-directed learning. Although AI in education is still a rare research field, future studies should focus, for example, on the use of concrete AI tools, such as intelligent tutoring systems or dialog systems supporting other forms of self-directed learning.

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Crossref · 10.1109/access.2025.3546319

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70 of 70 references verified0 citation errors · 0 not checkable

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  • Research by Younas et al. and Wang et al. found that intelligent tutoring systems and gamified AI applications promote student interest and self-directed learning.

    “These findings align with research by Younas et al. [59] and Wang et al. [37], which have also found that intelligent tutoring systems and gamified AI applications promote student interest and self-directed learning.”

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Authors
Younas, M., Abdel Salam El-Dakhs, D., & Jiang, Y.
Affiliations
  • Prince Sultan University (SA)
  • Language and Communication Research Laboratory, College of Humanities and Sciences, Prince Sultan University, Riyadh, Saudi Arabia
  • Shenzhen Technology University (CN)
Venue
IEEE Access
Published
2025
Volume
13
Pages
38387-38403
ISSN
2169-3536 (ISSN-L)
OpenAlex
W4408017171
Cited by
63
References
70
Citations by year
2026: 34 · 2025: 29
FWCI
6.14
Type
journal article
Language
en
Open access
Locations
  • IEEE Access (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Prince Sultan University under the Language and Communication Research Laboratory (RL-CH-2019/9/1)
  • Youth Fund Project for Humanities and Social Sciences Research, Ministry of Education, China (21YJC740022)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
self-directed learning, artificial intelligence in education, intelligent tutoring systems, chatbots, personalized learning support, learner autonomy, learner competence, prior knowledge, student satisfaction

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