Mobile-Based Intelligent Tutoring Systems: Enhancing Personalized Learning in Digital Education.
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| Title: | Mobile-Based Intelligent Tutoring Systems: Enhancing Personalized Learning in Digital Education. |
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| Authors: | Akhter, Shamim1 shamim.akhter@newinti.edu.my, Kumar, Tribhuwan2 t.kumar@psau.edu.sa, Shaheen, Musart3 shaheenmusarat332@gmail.com |
| Source: | International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 9, p4-16. 13p. |
| Subjects: | Intelligent tutoring systems, Individualized instruction, Data privacy, Technology Acceptance Model, Digital learning, Self-determination theory |
| Abstract: | The article focuses on mobile-based intelligent tutoring systems (M-ITS) and their role in enhancing personalized learning within digital education. It reviews theoretical foundations, including self-determination theory (SDT) and the technology acceptance model (TAM), and presents the Mobile Adaptive Personalized Tutoring (MAPT) framework, which integrates learner profiling, knowledge representation, pedagogical intelligence, mobile interfaces, and evaluation analytics. Empirical evidence indicates that M-ITS improve academic performance and learner engagement across diverse populations, including neurodivergent students and English as a Foreign Language (EFL) learners, with emerging generative AI (GenAI) components enabling dynamic, conversational tutoring. The article also discusses technical, pedagogical, and ethical challenges related to scalability, data privacy, and inclusivity, and suggests future research directions emphasizing longitudinal studies, cross-cultural validation, and human-AI collaboration in education. [Extracted from the article] |
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| Database: | Engineering Source |
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