Cognitive Mechanisms Underlying Learning Gains in Intelligent Tutoring Systems

A Systematic Literature Review

Authors

DOI:

https://doi.org/10.56741/IISTR.jetia.001801


Keywords:

Adaptive Learning, Artificial Intelligence, Cognitive Mechanisms, Intelligent Tutoring Systems, Knowledge Tracing

Abstract

Intelligent Tutoring Systems (ITS) have emerged as powerful AI-driven learning technologies capable of delivering personalized instruction at scale. This study provides a systematic review of literature published between 2020 and 2025 to examine the cognitive mechanisms through which ITS improve learning outcomes. A total of 20 empirical and high-impact studies were analyzed using predefined inclusion criteria focusing on adaptive feedback, knowledge tracing, scaffolding, metacognition, and motivational design. The findings reveal that ITS consistently produce small-to-moderate learning gains (d ≈ 0.30–0.70), with feedback and knowledge tracing identified as the most dominant and reliable mechanisms. Metacognitive supports demonstrate the strongest influence on deep learning and self-regulated learning, while scaffolding contributes to conceptual understanding and transfer. Motivation and engagement features, although less frequently studied, enhance persistence and learning intensity. The review also highlights emerging trends, including the integration of learning analytics, affective computing, and hybrid ITS architectures. However, challenges remain in model interpretability, standardization of outcomes, and alignment with pedagogical practices. This study contributes a synthesized framework linking cognitive mechanisms to learning effectiveness and provides directions for future research to develop more explainable, scalable, and pedagogically grounded ITS.

Author Biographies

Isaac John Ibanga, Modibbo Adama University

is an erudite scholar, researcher, and lecturer in the Sandwich Degree Programme of the Faculty of Education, Modibbo Adama University, Yola, Adamawa State, Nigeria. He specializes in electrical technology education, with academic interests spanning technical skills development, vocational education, and instructional innovation. Isaac is actively involved in teaching, research, and curriculum enhancement aimed at strengthening technology-based education. He has contributed to several academic publications and participates in initiatives promoting quality technical education in Nigeria. (email: isaacjohn@mau.edu.ng).

Aniekan Elijah Asukwo, Modibbo Adama University

is a lecturer in the Department of Electrical Technology Education at Modibbo Adama University of Technology (MAUTECH), Yola. He holds a Ph.D. in Electrical/Electronic Technology Education, with expertise in TVET, psychomotor skill assessment, digital teacher competencies, and university–industry collaboration. He has published extensively on practical skill evaluation in electronics work trade and serves on the editorial board of the VUNOKLANG Multidisciplinary Journal. Dr. Asukwo is dedicated to strengthening technical education and improving graduate employability. (email: aaelija@mau.edu.ng).

Bashir Mohammed, Modibbo Adama University

is an experienced lecturer in the Department of Electrical Technology Education at Modibbo Adama University, Yola, Adamawa State, Nigeria. He is an active member of several professional bodies and has held multiple academic and administrative positions. His scholarly work focuses on advancing teaching, learning, and curriculum development in electrical technology education. Dr. Bashir has authored numerous publications that contribute to strengthening technical education at both secondary and tertiary levels. (email: mohammedbashir2016@mautech.edu.ng).

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Published

2026-03-27

How to Cite

Ibanga, I. J., Asukwo, A. E., & Mohammed, B. (2026). Cognitive Mechanisms Underlying Learning Gains in Intelligent Tutoring Systems: A Systematic Literature Review. Journal of Educational Technology Innovation and Applications, 2(01), 32–43. https://doi.org/10.56741/IISTR.jetia.001801

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Vol. 2 No. 01 (2026): Journal of Educational Technology Innovation and Applications

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Copyright (c) 2026 Isaac John Ibanga, Aniekan Elijah Asukwo, Bashir Mohammed

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