Enhancing Trust and Engagement Among Thai E-Learning Consumers Through AI Personalization, Chatbots, and E-Service Quality
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Abstract
Purpose: This study investigates the impact of artificial intelligence (AI) personalization, chatbots, and e-service quality on customer experience, flow state, and learning outcomes, as well as how these factors influence customer trust and engagement among Thai e-learning users. Methodology: Structural equation modeling (SEM) was employed to test the proposed conceptual framework based on data collected from 498 Thai e-learning platform users through a quantitative survey. Findings: AI personalization and chatbots significantly improved customer experience and learning outcomes. AI personalization also increased flow state, whereas the chatbot–flow path was not supported. E-service quality showed no unique effect once AI personalization and chatbots were modeled. Learning outcomes were the only significant proximal predictor of customer trust and customer engagement. Overall, personalization and chatbots primarily influenced trust and customer engagement indirectly by enhancing learning outcomes. Applications of this study: The findings provide actionable insights for regulators, platform operators, and educational institutions. Prioritizing adaptive AI personalization and responsive chatbot support can strategically improve learning outcomes to ultimately foster greater trust and sustained engagement in Thailand’s e-learning ecosystem.
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