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.
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.
Keywords
Behavioural theory
E-learning
MBTI
Personality-Based learning
Student engagement