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February 24, 2026AUIQ Humanities and Social Sciences0 citations

Behavioural–Personality Framework for Adaptive E-Learning

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HGHisham Al Ghunaimi

Key Points

  • The research aims to integrate behavioural theory, specifically MBTI, into e-learning system design to improve learner engagement and motivation.
  • Conducted a qualitative conceptual content analysis
  • Synthesized secondary evidence from peer-reviewed literature and institutional reports (2015–2024)
  • Identified theoretical categories related to behavioural reinforcement and personality differentiation
  • Behavioural reinforcement is frequently underused in e-learning systems
  • Personality differences impact motivation and persistence but are often overlooked
  • Aligning reinforcement with MBTI preferences can improve emotional stability and engagement

Abstract

Purpose: This study examines the limited integration of behavioural theory—specifically the Myers–Briggs Type Indicator (MBTI)—in the design of e-learning systems. MBTI is considered because personality variation influences learner motivation, engagement, and behavioural responses, yet most digital platforms rely on uniform instructional strategies. The study focuses on higher-education e-learning, where behavioural disengagement and psychological strain are increasingly reported. Design/methodology/approach: A qualitative conceptual content-analysis approach is used to synthesise secondary evidence from peer-reviewed literature, policy documents, and institutional reports (2015–2024). The analysis identifies three theoretical categories—behavioural reinforcement, personality-based differentiation, and adaptive learning interaction—which shape the proposed behavioural–personality framework. Findings: Three core patterns emerged: (1) behavioural reinforcement is inconsistently embedded within e-learning systems; (2) personality differences affect motivation, cognitive load, and persistence but remain insufficiently addressed; and (3) aligning reinforcement mechanisms with MBTI preferences can enhance self-regulation, emotional stability, and engagement. These insights support the need for a unified behavioural–personality model for digital pedagogy. Practical implications: The study offers actionable guidance for universities, instructional designers, e-learning developers, and higher-education policymakers seeking to personalise learning pathways and strengthen student–teacher interaction in virtual learning environments. Social implications: Embedding behavioural theory in e-learning promotes equity, digital inclusion, and psychological well-being by recognising diverse learner profiles. Limitations: As a conceptual synthesis, the study excludes primary data and non-English sources; empirical testing across institutional and cultural contexts is recommended. Originality/value: The paper proposes a unified behavioural–personality framework linking reinforcement theory with MBTI profiling to support adaptive, human-centred e-learning design.

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Hisham Al Ghunaimi (2026) studied this question.

synapsesocial.com/papers/699d3fb3de8e28729cf645a0https://doi.org/10.70176/3106-7557.1009
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