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.

Koyuturk, C., Yavari, M., Theophilou, E., Bursic, S., Donabauer, G., Telari, A., et al. (2023). Developing Effective Educational Chatbots with ChatGPT prompts: Insights from Preliminary Tests in a Case Study on Social Media Literacy (with appendix). Intervento presentato a: 31st International Conference on Computers in Education (ICCE), Matsue.

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

Cansu Koyuturk
;
Mona Yavari
;
Sathya Bursic
;
Gregor Donabauer
;
Alessia Telari
;
Alessia Testa
;
Alessandro Gabbiadini
;
Dimitri Ognibene
2023

Abstract

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.
poster + paper
Computer Science - Human-Computer Interaction; Computer Science - Human-Computer Interaction; Computer Science - Artificial Intelligence; Computer Science - Computers and Society
English
31st International Conference on Computers in Education (ICCE)
2023
2023
http://arxiv.org/abs/2306.10645v2
none
Koyuturk, C., Yavari, M., Theophilou, E., Bursic, S., Donabauer, G., Telari, A., et al. (2023). Developing Effective Educational Chatbots with ChatGPT prompts: Insights from Preliminary Tests in a Case Study on Social Media Literacy (with appendix). Intervento presentato a: 31st International Conference on Computers in Education (ICCE), Matsue.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/467678
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