ChatPRCS：基于ChatGPT的个性化英语阅读理解支持系统
ChatPRCS: A Personalized Support System for English Reading Comprehension based on ChatGPT
AI总结：
本文提出基于ChatGPT和最近发展区理论的个性化阅读理解支持系统ChatPRCS，通过能力预测、提示模式和自动评估生成与专家水平一致的高质量问题。
摘要：
作为学习英语的一种常见方式，阅读理解主要涉及阅读文章并回答相关问题。然而，设计有效练习的复杂性导致学生遇到标准化问题，使其难以与个体学习者的阅读理解能力相匹配。通过利用以ChatGPT为代表的大型语言模型所提供的先进能力，本文基于最近发展区理论，提出了一种新颖的个性化阅读理解支持系统，称为ChatPRCS。ChatPRCS采用阅读理解能力预测、问题生成和自动评估等方法来增强阅读理解教学。首先，我们开发了一种新算法，能够利用学习者的历史数据预测其阅读理解能力，作为生成适当难度问题的基础。其次，提出了一系列新的ChatGPT提示模式，以解决阅读理解目标的两个关键方面：问题生成和自动评估。这些模式进一步提高了生成问题的质量。最后，通过整合个性化能力和阅读理解提示模式，ChatPRCS通过实验得到系统验证。实证结果表明，该系统为学习者提供了高质量的阅读理解问题，在统计层面上与专家精心设计的问题广泛一致。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
