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Title: Simulating Students: An AI Chatbot for Teacher Training
Authors: Bhowmik, Saptarshi
Barrett, Alex
Ke, Fengfeng
Yuan, Xin
Southerland, Sherry
Dai, Chih-Pu
West, Luke
Dai, Zhaihuan
Keywords: Learning Sciences
Issue Date: 2022
Publisher: International Society of the Learning Sciences
Citation: Bhowmik, S., Barrett, A., Ke, F., Yuan, X., Southerland, S., Dai, C., West, L., & Dai, Z. (2022). Simulating students: An AI chatbot for teacher trAIning. In Chinn, C., Tan, E., Chan, C., & Kali, Y. (Eds.), Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022 (pp. 1972-1973). International Society of the Learning Sciences.
Abstract: This article describes the development of a chatbot designed to simulate students in a 3D virtual environment for the purpose of pre-service teacher training. Using a generative pretrained transformer-based deep neural network model, researchers created an artificially intelligent chatbot using language resource data from authentic classroom dialogues. Results indicate that the chatbot needs to be fine-tuned with additional programming. This program is intended to be used in future research on teacher-training in virtual simulations.
Description: Poster
Appears in Collections:ISLS Annual Meeting 2022

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