Adopting AI-powered chatbots for academic performance: A qualitative model based on grounded theory approach

Abstract

Artificial intelligence (AI) integration into higher education is expanding. This study aims to conceptualise the higher vocational lecturers' adoption of AI-powered chatbots (AIPC) for academic performance. This research employs semi-structured interviews to collect data from 30 lecturers across 10 Chinese higher vocational higher education institutes. And then, using grounded theory to process the data. The findings reveal that AI-powered chatbot adoption is shaped by institutional support, pedagogical adaptability, and social influence. Institutional support, including leadership commitment, policy incentives, and structured training, plays a decisive role. Pedagogical adaptability varies across disciplines, with humanities and management lecturers more receptive than engineering and technical instructors, who highlight AI’s limitations in hands-on training. Social influence in higher vocational education is multi-tiered, shaped not only by peers and students but also by institutional leadership and industry collaborations. Finally, this research develops a qualitative model to encourage adopting AI-powered chatbots for academic performance.

Keywords: Artificial intelligence (AI), chatbots, higher vocational education, technology adoption, institutional support.

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