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<p>This study explores the integration of artificial intelligence (AI) technology into the Modeled Sustained Silent Reading (MSSR) programme, a reading initiative widely adopted in Taiwan that aims to foster students’ reading interest and establish sustained reading habits. Despite its popularity, MSSR faces challenges, such as Limited Perspective Reading (LPR), Unplanned Reading (UPR), and a Lack of Individualised Interactions (LII), which hinder the programme’s effectiveness. To address these issues, we developed an AI-powered reading assistant designed to support teachers by managing students’ reading lists and facilitating meaningful teacher-student book discussions. Utilizing advanced technologies such as Whisper speech-to-text and ChatGPT-4, the AI system transcribes book-chat dialogues in real-time and generates analytical meta-reviews to provide teachers with insights into students’ reading behaviors. A one-year pilot study involving five teachers and 75 students (grades 2–6) revealed that the AI reading assistant effectively aligned teacher recommendations with student preferences, boosting borrowing. AI-supported book chats fostered richer student expression across ages. AI eased book chat management, enabling tailored guidance and student independence. AI streamlined lesson prep and reporting, enhancing teacher evaluations. It improved parent-teacher communication and progress monitoring. Teachers found AI a supportive tool enhancing efficiency while maintaining human connection. AI holds significant potential to enrich learning and optimize teaching practices.</p>

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AI-Supported Reading Mentorship

  • 期刊论文

  • 发表日期：

    2025年7月17日

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  • Chang-Yen Liao

摘要

This study explores the integration of artificial intelligence (AI) technology into the Modeled Sustained Silent Reading (MSSR) programme, a reading initiative widely adopted in Taiwan that aims to foster students’ reading interest and establish sustained reading habits. Despite its popularity, MSSR faces challenges, such as Limited Perspective Reading (LPR), Unplanned Reading (UPR), and a Lack of Individualised Interactions (LII), which hinder the programme’s effectiveness. To address these issues, we developed an AI-powered reading assistant designed to support teachers by managing students’ reading lists and facilitating meaningful teacher-student book discussions. Utilizing advanced technologies such as Whisper speech-to-text and ChatGPT-4, the AI system transcribes book-chat dialogues in real-time and generates analytical meta-reviews to provide teachers with insights into students’ reading behaviors. A one-year pilot study involving five teachers and 75 students (grades 2–6) revealed that the AI reading assistant effectively aligned teacher recommendations with student preferences, boosting borrowing. AI-supported book chats fostered richer student expression across ages. AI eased book chat management, enabling tailored guidance and student independence. AI streamlined lesson prep and reporting, enhancing teacher evaluations. It improved parent-teacher communication and progress monitoring. Teachers found AI a supportive tool enhancing efficiency while maintaining human connection. AI holds significant potential to enrich learning and optimize teaching practices.