批判性思维
协作学习
心理学
判断
过程(计算)
数学教育
焦点小组
教育技术
知识管理
心理干预
生成模型
计算机科学
教育学
计算机支持的协作学习
教师教育
元认知
计算机辅助通信
在线讨论
任务(项目管理)
教学设计
生成语法
合作写作
合作学习
学习分析
教学方法
有意义的学习
认知
审议
概念图
思维过程
任务分析
作者
Auli Lehtinen,Faisal Rehman Channa,Piia Näykki,Emilia Ahlström,Mikko Hiljanen
摘要
ABSTRACT Background Generative artificial intelligence (GenAI) tools, such as ChatGPT, present both opportunities and concerns in education. They can support collaborative knowledge construction by providing systematic problem‐solving support. However, a strong focus on critical thinking and validity judgement is needed. GenAI's role in collaborative learning remains underexplored, especially in fostering critical thinking. Objectives This study examines GenAI's role in a collaborative task where 75 pre‐service teachers co‐create lesson plans on sustainable development. Methods Process mining is used to identify sequential patterns that indicate critical thinking. These patterns draw on video analysis and on categorising collaborative groups into high and low performers based on lesson‐plan quality. We analyse different prompt types (conceptual, pedagogical, and refining prompts). We also analyse activities, such as writing, editing, searching for other online sources, and copy‐pasting information. The sequential interplay of these activities reveals important aspects of critical engagement with GenAI. Results and Conclusions The results showed that participants frequently engaged in an iterative process of prompt refinement, indicating reflective use of AI. They also integrated conceptual and pedagogical aspects in their prompting. High‐performing groups demonstrated deeper engagement in activities such as iterative writing and corroborating GenAI content with other online resources. In contrast, low‐performing groups showed repetitive prompting and reliance on AI‐generated content. The results illustrate GenAI's role in collaborative and reflective learning and call for targeted interventions to support critical thinking. Educational interventions should focus, for example, on prompt refinement, guided reflection, and verification of GenAI information against other sources. Theoretically and methodologically, our analyses provide a foundation for further research.
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