Shao et al. (2026) — Under review.
Survey of 206 engineering students: AI chatbots provide greatest perceived benefit as relief from competence frustration, smaller benefits for autonomy, weakest for relatedness. Baseline motivational states matter more than demographics; inattention moderates how baseline competence and autonomy relate to perceived AI benefits. Offers design principles for engineering-specific AI learning tools.
Relevance to AI in Education: This paper contributes to the understanding of llm-assessment, personalized-learning, and student-experience. The findings have implications for adaptive-learning systems, formative-assessment design, and the broader edtech-platform landscape. Future work should explore how these results generalize across stem-education and higher-ed contexts.
This research connects to the growing body of work on ai-literacy and teacher-role, highlighting both the promise and limitations of AI tools in educational settings.
Related Pages
- higher-ed — related concept
- stem-education — related concept
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- student-experience — related concept
- scaffolding — related concept
- personalized-learning — related concept