Revolutionizing Flipped Learning with ChatGPT: A Strategic Framework for Enhanced Educational Engagement
翻转学习
计算机科学
知识管理
数学教育
心理学
作者
Thomas Newham,Peter Williams,Alastair Town
标识
DOI:10.4995/head24.2024.17240
摘要
This paper proposes a novel framework for integrating ChatGPT in flipped learning environments, enhancing both asynchronous and synchronous content delivery. It explores leveraging Large Language Models (LLMs) like ChatGPT to personalize and streamline educational content, utilizing Bloom's Taxonomy and Constructive Alignment for pedagogical design. The paper emphasizes the transformation of the educator's role and the creation of custom assessments using AI. It also outlines practical applications, including case studies, to demonstrate the improved learning outcomes and engagement through ChatGPT's integration. The proposal envisions an optimized educational landscape, rich in quality, diversity, and efficiency.