International Journal of Innovative Computer Science and IT Research

E-ISSN: 3067-1108

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Volume 2 Issue 9
September 2026

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AI-Enabled Personalized Education: Adaptive Learning Systems, Learner Analytics and Human-Centred Pedagogy

Author(s) Sanna Järvelä
Country Finland
Abstract Artificial intelligence is expanding the capacity of educational systems to analyze learner activity, estimate knowledge states, recommend learning resources, adjust instructional difficulty, and provide timely feedback. These capabilities support personalized education, but they do not ensure pedagogical quality, learner agency, inclusion, or meaningful teacher participation. This paper develops a human-centred framework for AI-enabled personalized education by integrating adaptive learning systems, learner analytics, formative assessment, teacher judgment, and ethical data governance. A conceptual and simulation-based methodology evaluates twelve illustrative learning environments through two composite measures: learner-analytics integration and personalized-learning effectiveness.
The simulated analysis identifies a strong positive association between these measures, with a descriptive correlation of r=.989. This relationship is illustrative and does not establish causation or represent empirical educational outcomes. The findings indicate that data integration can strengthen personalization when analytics are aligned with curriculum, feedback, accessibility, and teacher-led intervention. However, systems that optimize only performance scores may narrow learning, misclassify students, intensify surveillance, reproduce historical inequalities, and weaken learner autonomy.
The paper proposes a layered implementation strategy combining learner modeling, adaptive sequencing, interpretable analytics, educator oversight, student participation, privacy protection, and continuous evaluation. It concludes that effective personalized education should use AI to extend the instructional capabilities of teachers and learners rather than automate pedagogy as a closed technical process.
Keywords artificial intelligence in education, personalized learning, adaptive learning, learner analytics, human-centred pedagogy, formative feedback, educational data ethics.
Field Engineering
Published In Volume 2, Issue 9, September 2026
Published On 2026-09-05
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E-ISSN: 3067-1108
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