Abstract:
Reading comprehension is a widely adopted method for learning English, involving reading articles and answering related questions. However, the reading comprehension trai...Show MoreMetadata
Abstract:
Reading comprehension is a widely adopted method for learning English, involving reading articles and answering related questions. However, the reading comprehension training typically focuses on the skill level required for a standardized learning stage, without considering the impact of individual differences in linguistic competence. This article presents a personalized support system for reading comprehension, named chat generative pretrained transformer (ChatGPT)-based personalized reading comprehension support (ChatPRCS), based on the zone of proximal development (ZPD) theory. It leverages the advanced capabilities of large language models, exemplified by ChatGPT. ChatPRCS employs methods, including skill prediction, question generation and automatic evaluation, to enhance reading comprehension instruction. First, a ZPD-based algorithm is developed to predict students' reading comprehension skills. This algorithm analyzes historical data to generate questions with appropriate difficulty. Second, a series of 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 skill prediction and reading comprehension prompt patterns, ChatPRCS is validated through a series of 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. Furthermore, this study investigates the effect of the system on learning achievement, learning motivation, and cognitive load, providing further evidence of its effectiveness in instructing English reading comprehension.
Published in: IEEE Transactions on Learning Technologies ( Volume: 17)
Funding Agency:
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- IEEE Keywords
- Index Terms
- Reading Comprehension ,
- Personal Support ,
- English Reading Comprehension ,
- Cognitive Load ,
- Skill Level ,
- English Learners ,
- Learning Motivation ,
- Zone Of Proximal Development ,
- Automatic Evaluation ,
- Reading Comprehension Skills ,
- Prediction Model ,
- Experimental Group ,
- Use Of Systems ,
- Student Learning ,
- Individual Learning ,
- Learning Skills ,
- Area Under Curve ,
- Operation Period ,
- Reading Skills ,
- Student Motivation ,
- Question Difficulty ,
- Current Skills ,
- Question Generation ,
- Skills Of Students ,
- Mental Load ,
- Questionable Quality ,
- Problem-based Learning ,
- English Skills ,
- Reading Performance ,
- Current Reading
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Reading Comprehension ,
- Personal Support ,
- English Reading Comprehension ,
- Cognitive Load ,
- Skill Level ,
- English Learners ,
- Learning Motivation ,
- Zone Of Proximal Development ,
- Automatic Evaluation ,
- Reading Comprehension Skills ,
- Prediction Model ,
- Experimental Group ,
- Use Of Systems ,
- Student Learning ,
- Individual Learning ,
- Learning Skills ,
- Area Under Curve ,
- Operation Period ,
- Reading Skills ,
- Student Motivation ,
- Question Difficulty ,
- Current Skills ,
- Question Generation ,
- Skills Of Students ,
- Mental Load ,
- Questionable Quality ,
- Problem-based Learning ,
- English Skills ,
- Reading Performance ,
- Current Reading
- Author Keywords