ChatPRCS: A Personalized Support System for English Reading Comprehension based on ChatGPT

TL;DR

ChatPRCS leverages ChatGPT to create a personalized reading comprehension support system that predicts learner ability, generates suitable questions, and evaluates responses, thereby improving individualized English reading instruction.

Contribution

This paper introduces a novel system combining ability prediction, question generation, and automated evaluation using ChatGPT, tailored to individual learners' needs based on the Zone of Proximal Development.

Findings

High-quality questions aligned with expert standards

Effective ability prediction from historical data

Improved personalized reading comprehension support

Abstract

As a common approach to learning English, reading comprehension primarily entails reading articles and answering related questions. However, the complexity of designing effective exercises results in students encountering standardized questions, making it challenging to align with individualized learners' reading comprehension ability. By leveraging the advanced capabilities offered by large language models, exemplified by ChatGPT, this paper presents a novel personalized support system for reading comprehension, referred to as ChatPRCS, based on the Zone of Proximal Development theory. ChatPRCS employs methods including reading comprehension proficiency prediction, question generation, and automatic evaluation, among others, to enhance reading comprehension instruction. First, we develop a new algorithm that can predict learners' reading comprehension abilities using their historical data as the foundation for generating questions at an appropriate level of difficulty. Second, a series of new ChatGPT prompt patterns is proposed to address two key aspects of reading comprehension objectives: question generation, and automated evaluation. These patterns further improve the quality of generated questions. Finally, by integrating personalized ability and reading comprehension prompt patterns, ChatPRCS is systematically validated through experiments. Empirical results demonstrate that it provides learners with high-quality reading comprehension questions that are broadly aligned with expert-crafted questions at a statistical level.