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Developing Effective Educational Chatbots with ChatGPT prompts: Insights from Preliminary Tests in a Case Study on Social Media Literacy (with appendix)

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arxiv 2306.10645 v2 pith:DP25Y4L7 submitted 2023-06-18 cs.HC cs.AIcs.CY

classification cs.HCcs.AIcs.CY
keywords educationalchatbotschatgptlearningabilitycapabilitiescasechatbot
verification ladder T0 review T1 audit T2 compute T3 formal
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Educational chatbots come with a promise of interactive and personalized learning experiences, yet their development has been limited by the restricted free interaction capabilities of available platforms and the difficulty of encoding knowledge in a suitable format. Recent advances in language learning models with zero-shot learning capabilities, such as ChatGPT, suggest a new possibility for developing educational chatbots using a prompt-based approach. We present a case study with a simple system that enables mixed-turn chatbot interactions and discuss the insights and preliminary guidelines obtained from initial tests. We examine ChatGPT's ability to pursue multiple interconnected learning objectives, adapt the educational activity to users' characteristics, such as culture, age, and level of education, and its ability to use diverse educational strategies and conversational styles. Although the results are encouraging, challenges are posed by the limited history maintained for the conversation and the highly structured form of responses by ChatGPT, as well as their variability, which can lead to an unexpected switch of the chatbot's role from a teacher to a therapist. We provide some initial guidelines to address these issues and to facilitate the development of effective educational chatbots.

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  1. ProfiLLM: An LLM-Based Framework for Implicit Profiling of Chatbot Users

    cs.AI 2025-06 conditional novelty 6.0 of 10

    ProfiLLM infers chatbot users' IT/cybersecurity proficiency from their prompts, achieving a rapid initial reduction in profiling error in synthetic and limited human evaluations.

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