计算机科学
生成语法
文件夹
跟踪(教育)
平面图(考古学)
数学教育
人工智能
多媒体
教育学
心理学
考古
金融经济学
经济
历史
作者
Siu Cheung Kong,John Chi‐Kin Lee,Olson Tsang
标识
DOI:10.58459/rptel.2024.19030
摘要
The emergence and popularity of generative artificial intelligence (AI) tools, particularly text-based ones known as large language models, pose both opportunities and challenges to education. The ability of these tools to generate human-like texts based on minimal instructions causes concerns among educators about students’ use of these tools for academic writing, which may constitute a breach of academic integrity. We propose a pedagogical design that models on self-regulated learning and the authoring cycle and develops students’ critical thinking and self-regulation when composing academic writing using text-based generative AI tools. It contains six iterative and interactive phases. Students first plan the content and structure of the writing, then generate prompts for text-based generative AI tools. Next, students preview and verify the tools’ output, followed by the fourth phase of producing the writing using the corrected output. Fifthly, peer review by fellow students may be required to polish and proofread the writing. Lastly, through portfolio-tracking, students reflect on the writing process, and formulate strategies for future usage of text-based generative AI tools for writing. This pedagogical design helps students and teachers embrace text-based generative AI while addressing the perils these tools present, and guides the development of education interventions and instruments.
科研通智能强力驱动
Strongly Powered by AbleSci AI