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"Bespoke Bots": Diverse Instructor Needs for Customizing Generative AI Classroom Chatbots
arXiv – CS AI|Irene Hou (UC San Diego), Zeyu Xiong (ETH Zurich), Philip J. Guo (UC San Diego), April Yi Wang (ETH Zurich)||1 views
🤖AI Summary
Researchers analyzed how university STEM instructors customize AI chatbots for classroom use, identifying ten common categories of customization. The study found that instructors prioritize aligning chatbot behavior with course materials over persona customization, but needs vary significantly by course size and teaching style, suggesting modular AI chatbot designs would be most effective.
Key Takeaways
- →Instructors consistently prioritize customizing chatbot behavior to align with course materials and pedagogical strategies over persona/tone adjustments.
- →Customization needs vary significantly by course size, discipline, and teaching style, even across courses taught by the same instructor.
- →No single AI chatbot design can meet all educational contexts, highlighting the need for flexible solutions.
- →Ten common categories of chatbot customization were identified including persona, guardrails, and personalization.
- →Modular AI chatbot systems may provide the most promising approach for educational applications.
Read Original →via arXiv – CS AI
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