超越效率:关于生成式人工智能对认知、元认知和学习中的认知代理的影响的实证见解

IF 8.1 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Lixiang Yan, Viktoria Pammer-Schindler, Caitlin Mills, Andy Nguyen, Dragan Gašević
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引用次数: 0

摘要

生成式人工智能(GenAI)有望重塑教育,然而,除了提高效率和可扩展性之外,其对学习者的更深层次认知、认知、社会情感和伦理影响方面的关键问题仍然存在。这个特别的部分收集了来自不同教育环境的新兴经验证据,以研究与先进的GenAI系统(从智能导师和会话代理到人工智能生成的反馈提供者)的互动如何塑造学习者的认知参与、认知代理、元认知调节和与技术的情感关系。虽然研究揭示了个性化指导、协作探究和增强自我反思方面的积极影响的证据,但研究结果也强调了认知警惕性降低、肤浅学习和对人工智能对话者的情感依赖等风险。这些见解主张对教育进行重新构想,积极试验新的人工智能技术,同时不断收集和批判性地评估证据——将教育设想为不仅是完全由人类或人工智能主导的活动,而且是一种真正的协作努力,在有意义和有道德基础的伙伴关系中平衡人类智能和人工智能能力。展望未来,在这篇社论中,我们提出了一个跨学科的研究路线图,敦促更深入地研究与持续接触人工智能相关的认知和神经后果,同时开发全面的框架来培养人工智能素养和评估判断。它还鼓励对日益模糊的人类与人工智能界限的长期伦理影响进行严格评估。最终,在人工智能背景下推进教育需要积极主动地应对这些新出现的复杂性,这样教师和学习者不仅可以在人工智能的未来中生存,还可以创造性地、批判性地和道德地共同合作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Beyond efficiency: Empirical insights on generative AI's impact on cognition, metacognition and epistemic agency in learning

Beyond efficiency: Empirical insights on generative AI's impact on cognition, metacognition and epistemic agency in learning

Beyond efficiency: Empirical insights on generative AI's impact on cognition, metacognition and epistemic agency in learning

Beyond efficiency: Empirical insights on generative AI's impact on cognition, metacognition and epistemic agency in learning

Generative AI (GenAI) promises to reshape education, yet, beyond gains in efficiency and scalability, crucial questions remain regarding its deeper cognitive, epistemic, socio-emotional and ethical implications for learners. This special section collects emerging empirical evidence from diverse educational settings to examine how interactions with advanced GenAI systems—ranging from intelligent tutors and conversational agents to AI-generated feedback providers—shape learners' cognitive engagement, epistemic agency, metacognitive regulation and emotional relationships with technology. While studies reveal evidence of positive effects in personalised guidance, collaborative inquiry and enhanced self-reflection, findings also highlight risks such as diminished epistemic vigilance, superficial learning and emotional dependence on AI interlocutors. These insights advocate for an educational re-imagining that actively experiments with novel AI technologies while continuously gathering and critically evaluating evidence—envisioning education not merely as a spectrum ranging from fully human- or AI-led activities but also as genuinely collaborative endeavours that balance human intelligence and AI capabilities in meaningful and ethically grounded partnerships. Looking ahead, in this editorial, we propose an interdisciplinary research roadmap that urges deeper examination of the cognitive and neural consequences associated with sustained AI exposure, together with the development of comprehensive frameworks to cultivate AI literacy and evaluative judgement. It also encourages rigorous assessment of the long-term ethical implications of increasingly blurred human-AI boundaries. Ultimately, advancing education in GenAI-infused contexts requires proactive engagement with these emerging complexities, so that teachers and learners not only survive in an AI-infused future but also creatively, critically and ethically co-author it.

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来源期刊
British Journal of Educational Technology
British Journal of Educational Technology EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
15.60
自引率
4.50%
发文量
111
期刊介绍: BJET is a primary source for academics and professionals in the fields of digital educational and training technology throughout the world. The Journal is published by Wiley on behalf of The British Educational Research Association (BERA). It publishes theoretical perspectives, methodological developments and high quality empirical research that demonstrate whether and how applications of instructional/educational technology systems, networks, tools and resources lead to improvements in formal and non-formal education at all levels, from early years through to higher, technical and vocational education, professional development and corporate training.
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