Adopting AI-Powered Chatbots for Academic Performance: A Qualitative Model Based on Grounded Theory Approach
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| Title: | Adopting AI-Powered Chatbots for Academic Performance: A Qualitative Model Based on Grounded Theory Approach |
|---|---|
| Language: | English |
| Authors: | Fan Wang, Songyu Jiang |
| Source: | African Educational Research Journal. 2025 13(1):52-64. |
| Availability: | Net Journals. 25 Akintola Road, Sapele, Delta State, 331107, Nigeria. e-mail: service@netjournals.org; Web site: https://www.netjournals.org/aer_index.html |
| Peer Reviewed: | Y |
| Page Count: | 13 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Computer Software, College Faculty, Career and Technical Education, Foreign Countries, Technology Uses in Education, Academic Achievement, Grounded Theory, Teaching Methods, Social Influences, Humanities, Management Development, Business Education, Engineering Education, Technology Education, School Business Relationship, Industry |
| Geographic Terms: | China |
| ISSN: | 2354-2160 |
| 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. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1468503 |
| Database: | ERIC |
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