LLM-Driven Learning Analytics Dashboard for Teachers in EFL Writing Education
Abstract
Introduces a learning analytics dashboard that helps EFL teachers monitor student ChatGPT interactions and align classroom strategies using LLM-driven insights.
Authors: Minsun Kim, SeonGyeom Kim, Suyoun Lee, Yoosang Yoon, Junho Myung, Haneul Yoo, Hyungseung Lim, Jieun Han, Yoonsu Kim, So-Yeon Ahn, Juho Kim, Alice Oh, Hwajung Hong, Tak Yeon Lee
Journal: EMNLP 2024 Workshop, CustomNLP4U
Abstract: This paper presents the development of a dashboard designed specifically for teachers in English as a Foreign Language (EFL) writing education. Leveraging LLMs, the dashboard facilitates the analysis of student interactions with an essay writing system, which integrates ChatGPT for real-time feedback. The dashboard aids teachers in monitoring student behavior, identifying noneducational interaction with ChatGPT, and aligning instructional strategies with learning objectives. By combining insights from NLP and Human-Computer Interaction (HCI), this study demonstrates how a human-centered approach can enhance the effectiveness of teacher dashboards, particularly in ChatGPT-integrated learning.
Link: Read the full paper
Keywords: Human-Computer interaction, Learning Analytics, Education, LLM, AI