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User Adaptive Language Learning Chatbots With A Curriculum

Conference Paper/Proceedings
User Adaptive Language Learning Chatbots With A Curriculum
Publication Year:
2023
Publication Source:
Communications In Computer And Information Science
Volume:
1831 CCIS
Funding Type:
ECR:Core
Author(s):
Qian, Kun; Shea, Ryan; Li, Yu; Fryer, Luke Kutszik; Yu, Zhou
Supporting Project(s):

Along with the development of systems for natural language understanding and generation, dialog systems have been widely adopted for language learning and practicing. Many current educational dialog systems perform chitchat, where the generated content and vocabulary are not constrained. However, for learners in a school setting, practice through dialog is more effective if it aligns with students’ curriculum and focuses on textbook vocabulary. Therefore, we adapt lexically constrained decoding to a dialog system, which urges the dialog system to include curriculum-aligned words and phrases in its generated utterances. We adopt a generative dialog system, BlenderBot3, as our backbone model and evaluate our curriculum-based dialog system with middle school students learning English as their second language. The constrained words and phrases are derived from their textbooks, suggested by their English teachers. The evaluation result demonstrates that the dialog system with curriculum infusion improves students’ understanding of target words and increases their interest in practicing English. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.