An LLM-Powered Adaptive Practicing System

Md Rayhan Kabir, Fuhua Lin

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

The deployment of artificial intelligence in online education systems has become very popular in recent years. Recently published large language models tend to have a huge application potential for developing intelligent online education systems. In this paper, we propose a personalized online practicing system where we will use ChatGPT to generate questions and provide appropriate feedback for the student's responses to the questions. We designed a prompt generator and a text analyzer to send prompts and process the responses by ChatGPT. We also integrated an adaptive feedback mechanism to determine whether a student has mastered a topic or not. We developed a prototype of our proposed system. From initial experiments with a given topic, we found that ChatGPT could accurately and effectively generate questions and feedback to enable adaptive practice.

Original languageEnglish
Pages (from-to)43-52
Number of pages10
JournalCEUR Workshop Proceedings
Volume3487
Publication statusPublished - 2023
Event1st Annual Workshop on Empowering Education with LLMs - the Next-Gen Interface and Content Generation, AIEDLLM 2023 - Tokyo, Japan
Duration: 7 Jul. 2023 → …

Keywords

  • AI in education
  • Adaptive Practicing
  • ChatGPT
  • Large Language model

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