The effects of critical thinking intervention on reliance behaviors, problem-solving quality, and creativity during human-Generative AI collaborative learning

IF 10.5 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Computers & Education Pub Date : 2026-07-01 Epub Date: 2026-01-18 DOI:10.1016/j.compedu.2026.105576
Chenyu Hou , Gaoxia Zhu , Yanzhi Liu , Vidya Sudarshan , Josephine Leng Leng Chong , Fannie Yifan Zhang , Michael Yong Heng Tan , Yew Soon Ong
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引用次数: 0

Abstract

As Generative AI becomes increasingly used in various educational contexts, understanding how students engage with these tools during collaborative problem-solving is critical. While prior research suggests that critical thinking is essential in human-AI problem-solving, few studies have examined how instructional interventions, targeting critical thinking, might shape their reliance behaviors and collaborative outcomes. This study investigates the effects of a critical thinking intervention embedded in a problem-based learning (PBL) environment where students are engaged with Generative AI. The intervention combined strategies that foster critical thinking, including authentic instruction, structured dialogue, and AI-supported peer mentoring, aiming to promote students' thoughtful engagement and improve problem-solving performance. Participants (N = 226) were assigned to experimental (with critical thinking interventions) or comparison (without critical thinking interventions) conditions. We used pre- and post-surveys to measure participants' trust, critical thinking, and AI reliance behaviors, and group reports and chat histories to assess their problem-solving quality and creativity. Results revealed that the intervention did not produce significant improvement in self-reported critical thinking, possibly due to the short intervention duration. However, the intervention led to a marginal reduction in students' thoughtless use of Generative AI and significantly reduced the direct adoption of AI-generated content. Notably, students in the intervention condition produced more creative solutions, demonstrating higher levels of originality and idea density in their group reports. These findings suggest that how students use Generative AI is critical, especially when it is almost impossible to control whether they use it or not. The study highlights the importance of designing interventions that cultivate students’ critical thinking to support creative human-AI problem-solving.
人类生成人工智能协作学习中批判性思维干预对依赖行为、问题解决质量和创造力的影响
随着生成式人工智能越来越多地应用于各种教育环境,了解学生在协作解决问题过程中如何使用这些工具至关重要。虽然之前的研究表明,批判性思维在人类-人工智能问题解决中至关重要,但很少有研究调查针对批判性思维的教学干预如何影响他们的依赖行为和合作结果。本研究探讨了在学生参与生成式人工智能的基于问题的学习(PBL)环境中嵌入批判性思维干预的效果。干预措施结合了培养批判性思维的策略,包括真实的教学、结构化的对话和人工智能支持的同伴指导,旨在促进学生的深思熟虑参与,提高解决问题的能力。参与者(N = 226)被分配到实验(有批判性思维干预)或比较(没有批判性思维干预)条件。我们使用前后调查来衡量参与者的信任、批判性思维和人工智能依赖行为,并使用小组报告和聊天记录来评估他们解决问题的质量和创造力。结果显示,干预并没有显著改善自我报告的批判性思维,可能是由于干预时间短。然而,干预导致学生对生成式人工智能的轻率使用略有减少,并显著减少了对人工智能生成内容的直接采用。值得注意的是,在干预条件下的学生提出了更多创造性的解决方案,在他们的小组报告中表现出更高的原创性和想法密度。这些发现表明,学生如何使用生成式人工智能是至关重要的,尤其是在几乎不可能控制他们是否使用它的情况下。该研究强调了设计干预措施的重要性,这些干预措施可以培养学生的批判性思维,以支持创造性的人类-人工智能问题解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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