Date
Publisher
arXiv
AI chatbots have emerged as promising educational tools for personalized learning experiences, with advances in large language models (LLMs) enabling teachers to create and customize these chatbots for their specific classroom needs. However, there is a limited understanding of how teachers create pedagogical chatbots and integrate them into their lessons. Through semi-structured interviews with seven K-12 teachers, we examined their practices and challenges when designing, implementing, and deploying chatbots. Our findings revealed that teachers prioritize developing task-specific chatbots aligned with their lessons. Teachers engaged in various creation practices and had different challenges; novices struggled mainly with initial design and technical implementation, while experienced teachers faced challenges with technical aspects and analyzing conversational data. Based on these insights, we explore approaches to supporting teachers' chatbot creation process and opportunities for designing future chatbot creation systems. This work provides practical insights into deepening the understanding of teacher-driven AI chatbots and AI-augmented learning environments.
Study at a glance
- Question: How do K-12 teachers create educational chatbots, and what challenges do they face?
- Setting and data: Seven K-12 teachers.
- Method: Semi-structured interviews.
Why it matters
Advances in large language models enable teachers to customize AI chatbots for their specific classroom needs. However, there is limited understanding of how teachers create these pedagogical chatbots and integrate them into their lessons.
Key findings
- In interviews with seven K-12 teachers, educators prioritized creating task-specific chatbots that directly aligned with their classroom lessons.
- Novice teachers struggled mainly with initial chatbot design and technical implementation.
- Experienced teachers faced challenges with technical aspects and analyzing conversational data from chatbot interactions.
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