Wu Dang, Zhang Jianyang
School of Special Education, Handan University, Handan, China.
Faculty of Arts, University of Auckland, Auckland, New Zealand.
PLoS One. 2025 May 9;20(5):e0323349. doi: 10.1371/journal.pone.0323349. eCollection 2025.
As generative artificial intelligence (AI) rapidly transforms educational landscapes, understanding its impact on students' core competencies has become increasingly critical for educators and policymakers. Despite growing integration of AI technologies in classrooms, there remains a significant knowledge gap regarding how these tools influence the development of essential 21st-century skills in secondary education contexts. This study addresses this gap by investigating the relationships between generative AI applications and two critical student outcomes: innovation capability and digital literacy. Through structural equation modeling analysis of data collected from 500 students across grades 7-12, the research reveals three key findings: Firstly, generative AI applications demonstrate a substantial positive effect on students' innovation capability (β = 0.862, p < .001), enhancing critical thinking, creative problem-solving, and adaptive learning processes. Secondly, AI integration significantly improves digital literacy (β = 0.835, p < .001) by facilitating sophisticated information processing and active technological engagement. Thirdly, a strong bidirectional relationship exists between innovation capability and digital literacy (β = 0.791, p < .001), suggesting these competencies mutually reinforce each other in AI-enhanced learning environments. The model demonstrates robust explanatory power with excellent fit indices. By integrating the Technology Acceptance Model with Diffusion of Innovations theory, this study advances theoretical understanding of AI's educational impact while providing practical guidelines for educators. The findings underscore the importance of strategic AI integration in educational curricula and suggest specific pathways for developing critical student competencies in the digital age.
随着生成式人工智能（AI）迅速改变教育格局，对于教育工作者和政策制定者而言，了解其对学生核心能力的影响变得愈发关键。尽管人工智能技术在课堂中的应用日益广泛，但在这些工具如何影响中等教育背景下21世纪关键技能的发展方面，仍存在重大知识空白。本研究通过调查生成式人工智能应用与两个关键学生成果之间的关系来填补这一空白：创新能力和数字素养。通过对从7至12年级的500名学生收集的数据进行结构方程模型分析，研究得出三个关键发现：首先，生成式人工智能应用对学生的创新能力具有显著的积极影响（β = 0.862，p <.001），增强了批判性思维、创造性解决问题和适应性学习过程。其次，人工智能的融入通过促进复杂的信息处理和积极的技术参与，显著提高了数字素养（β = 0.835，p <.001）。第三，创新能力和数字素养之间存在强烈的双向关系（β = 0.791，p <.001），表明这些能力在人工智能增强的学习环境中相互促进。该模型具有强大的解释力，拟合指数良好。通过将技术接受模型与创新扩散理论相结合，本研究推进了对人工智能教育影响的理论理解，同时为教育工作者提供了实用指南。研究结果强调了在教育课程中战略性地融入人工智能的重要性，并为数字时代培养学生关键能力提出了具体途径。
