Citation

Jaffri, Syed Uzair and Koo, Ah Choo and Hussain, Salman and Ting, Choo Yee (2026) AI-Based Online Education Systems Integrating Real-Time Affective Computing: A Design-Oriented Conceptual Framework. Social Sciences, 15 (7). p. 421. ISSN 2076-0760

Text AI-Based Online Education Systems Integrating Real-Time Affective Computing_ A Design-Oriented Conceptual Framework.pdf - Published Version Restricted to Repository staff only Download (524kB)

Abstract

The implementation of an artificial intelligence (AI)-based system for monitoring, forecasting, and learner performance support has been intensified by the rapid expansion of online education systems. Existing online educational platforms completely rely on learning analytics and machine learning to customize content delivery. On the other hand, these platforms fundamentally focus on behavioral and cognitive indicators, whereas the integration of affective computing into learning analytics and adaptive decision-making processes is lacking. During the learning process, emotions like engagement, boredom, and confusion play a vital role. Nonetheless, the integration of adaptive online learning systems is still fragmented and underdeveloped. The latest progress in affective computing and multimodal sensing technologies allow for the inference of the affective state of learners in real-time, which creates a range of potential opportunities to create emotionally sensitive learning spaces. Despite technological innovations, the existing studies do not have a conceptual framework that is unified, design-oriented, and clearly incorporates affective computing with AI-based learning analytics to inform real-time pedagogical adaptation. To address this gap, this study introduces a design-oriented conceptual framework for AI-based online education systems that incorporate real-time affective computing. This conceptual framework combines the theoretical foundation of learning analytics, affective computing, and adaptive learning systems. The suggested framework offers a clear and scalable basis of online learning environments that are affective-aware by offering a clear framework of development, assessment, and consequent empirical validation.

Item Type:	Article
Uncontrolled Keywords:	Affective computing, online learning
Subjects:	L Education > LB Theory and practice of education > LB1060 Learning Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI) Faculty of Creative Multimedia (FCM)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Sep 2026 08:30
Last Modified:	02 Sep 2026 08:30
URII:	http://shdl.mmu.edu.my/id/eprint/16548

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