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Published on: December 16, 2010
My digital mentor: a mixed-methods study of user-GAI interactions
Lei Xian1, Guangqiu Cao2, Na Zhang2
1School of Management, Xiamen University, Xiamen, China.
Generative Artificial Intelligence (GAI) in online learning requires a combination of factors for long-term use. Perceived value and satisfaction, influenced by intelligence, accuracy, and support, drive sustained engagement with GAI tools.
Area of Science:
- Educational Technology
- Artificial Intelligence in Education
- Human-Computer Interaction
Background:
- Generative Artificial Intelligence (GAI) offers dynamic content for online learning.
- Existing research focuses on short-term GAI adoption, neglecting long-term usage and psychological factors.
Purpose of the Study:
- Investigate long-term (infusion) use of GAI in online learning.
- Identify psychological mechanisms driving GAI infusion use.
- Develop a framework for effective user-GAI interaction.
Main Methods:
- Two-stage mixed-methods approach: semi-structured interviews (N=26) followed by survey validation (N=327).
- Identified key factors: intelligence, explainability, response time, integrability, accuracy, source credibility, personalization, and emotional support.
- Employed fsQCA to determine factor configurations for infusion use.
Main Results:
- Eight identified factors influence infusion use through perceived value and satisfaction.
- No single factor is sufficient; combinations of factors are crucial for sustained GAI use.
- User-GAI interaction is mediated by psychological factors like perceived value and satisfaction.
Conclusions:
- Findings expand technology adoption literature in online learning.
- Practical implications for designing effective user-GAI interactions.
- Highlights the importance of a holistic approach to GAI integration in education.
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