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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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 15 of its 53 references that are in the map. First posted on arXiv 18 Jun 2023.
Builds on
15 of 53 references.
References · 15
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- 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
- 2023Automatic Prompt Optimization with "Gradient Descent" and Beam Searchcited by 628
- 2023Hyena Hierarchy: Towards Larger Convolutional Language Modelscited by 388
- 2021Do Prompt-Based Models Really Understand the Meaning of their Prompts?cited by 324
- 2023Large Language Models Fail on Trivial Alterations to Theory-of-Mind Taskscited by 288
- 2022Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionalscited by 191
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- 2022HyperPrompt: Prompt-based Task-Conditioning of Transformerscited by 67
- 2022Exploring the Universal Vulnerability of Prompt-based Learning Paradigmcited by 56
3 more
- 2023Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraintscited by 31
- 2021Challenging Social Media Threats using Collective Well-being Aware Recommendation Algorithms and an Educational Virtual Companioncited by 4
- 2023Conversation Style Transfer using Few-Shot Learningcited by 4
Built on by
Citing papers per year: 2023: 2; 2024: 1; 2025: 1; 2026: 2.
6 papers.
- 2023User Modeling in the Era of Large Language Models: Current Research and Future Directionscited by 18
- 2023Learning to Prompt in the Classroom to Understand AI Limits: A pilot studycited by 6
- 2025Understanding Learner-LLM Chatbot Interactions and the Impact of Prompting Guidelinescited by 6
- 2024Unimib Assistant: designing a student-friendly RAG-based chatbot for all their needscited by 4
- 2026"Bespoke Bots": Diverse Instructor Needs for Customizing Generative AI Classroom Chatbotscited by 2
- 2026The Hidden Cost of Contextual Sycophancy: an AI Literacy Intervention in Human-AI Collaborationcited by 1
- 2026The Hidden Cost of Contextual Sycophancy: an AI Literacy Intervention in Human-AI Collaboration18 May 2026
- 2026"Bespoke Bots": Diverse Instructor Needs for Customizing Generative AI Classroom Chatbots10 Feb 2026
- 2025Understanding Learner-LLM Chatbot Interactions and the Impact of Prompting Guidelines10 Apr 2025
- 2024Unimib Assistant: designing a student-friendly RAG-based chatbot for all their needs29 Nov 2024
- 2023User Modeling in the Era of Large Language Models: Current Research and Future Directions11 Dec 2023
- 2023Learning to Prompt in the Classroom to Understand AI Limits: A pilot study4 Jul 2023