Understanding Chinese university students' continued learning intentions with DeepSeek: An Integrated TAM-SOR model
View abstract on PubMed
Summary
This summary is machine-generated.University students
Area Of Science
- Educational Technology
- Artificial Intelligence in Education
- Higher Education
Background
- Higher education in China is modernizing with AI tools like DeepSeek.
- University students are shifting towards intelligent learning methods.
- Existing AI research overlooks crucial emotional and motivational factors in student learning.
Purpose Of The Study
- To analyze emotional perceptions influencing DeepSeek adoption by university students.
- To investigate factors driving sustained use of generative AI in higher education.
- To identify barriers and facilitators for AI learning platform adoption.
Main Methods
- Combined Technology Acceptance Model (TAM) and Stimulus-Organism-Response (SOR) models.
- Collected 476 valid responses via an online questionnaire survey.
- Analyzed emotional perceptions and their impact on AI tool usage.
Main Results
- Perceived emotions and sustained motivation are key to adopting generative AI learning tools.
- Tool convenience enhances practicality, usability, and positive emotions.
- Learning habit-aligned designs increase control and pleasure, driving sustained use.
- High self-efficacy reduces usage barriers by fostering an emotional connection with AI functions.
Conclusions
- Emotional perceptions and sustained motivation are critical for university students' adoption of AI learning technologies.
- Convenience, usability, and habit-aligned design foster positive emotions and sustained use.
- Self-efficacy plays a vital role in overcoming adoption barriers for generative AI learning platforms.
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