| 616 | 0 | 176 |
| 下载次数 | 被引频次 | 阅读次数 |
随着生成式人工智能(GenAI)在高校的迅速普及,大学生对其的接受态度、使用行为及能力发展预期成为亟需系统检验的重要议题。基于约翰·比格斯(John B. Biggs)的3P学习过程模型,本文构建“态度—行为—能力”分析框架,利用全国20所高校共计12,678名大学生的问卷数据,系统分析大学生对GenAI的使用特征及群体差异。研究发现,大学生整体呈现出“积极态度—策略使用—有限能力预期”的特征:在态度上,学生普遍支持GenAI的应用,同时对数据安全和隐私风险保持审慎;在行为上,态度越积极的学生越倾向于更频繁地使用GenAI,且使用主要集中于语言支持与写作辅助等任务;在能力发展方面, GenAI使用与学生的高阶思维能力提升预期呈显著正相关,但学生对其促进批判性思维和创新能力的作用仍相对谨慎。群体差异分析表明,双一流高校学生在态度、使用行为和能力发展预期上均表现得更为积极;在学科方面,人文与农医学科学生相对消极。基于上述发现,本文从高校课程建设、 AI素养培养与数字鸿沟治理等方面提出政策建议,以促进GenAI在高等教育中的科学应用与学生能力的可持续发展。
Abstract：With the rapid diffusion of generative artificial intelligence(GenAI) in higher education, college students' acceptance, usage behaviors, and expectations regarding capability development have become essential issues that warrant systematic investigation. Drawing on John B. Biggs' s 3P learning process model, this study develops an “ Attitude—Behavior—Ability” analytical framework and utilizes survey data from 12,678 undergraduates across 20 universities in China to examine students' Gen AI usage patterns and group differences. The results reveal a general pattern of “Positive Attitudes—Strategic Use—Limited Ability Expectations.” Regarding attitudes, most students support the use of GenAI while remaining cautious about data security and privacy risks. In terms of usage behaviors, students with more positive attitudes tend to use GenAI more frequently, primarily for language support and writing-related tasks. As for ability development, GenAI use is significantly and positively associated with students' expectations for improved higher-order thinking skills; however, students remain cautious about GenAI's role in enhancing critical thinking and creativity. Heterogeneity analyses further show that students from Double First-Class universities exhibit more positive attitudes, higher usage frequency, and stronger expectations for ability development compared to those from non-Double First-Class institutions; meanwhile, students in humanities and agriculture/medicine disciplines tend to be less positive. Based on these findings, the study proposes policy recommendations concerning curriculum design, AI literacy development, and digital divide mitigation to support the responsible and sustainable integration of GenAI in higher education.
[1]王佑镁,王旦等.“阿拉丁神灯”还是“潘多拉魔盒”:ChatGPT教育应用的潜能与风险[J].现代远程教育研究,2023,35(2):48-56.
[2]欧阳嘉煜,缪静敏等.国外一流大学应对生成式人工智能挑战的策略分析——基于对31所国外一流大学的线上调研[J].高等教育研究,2023,44(10):99-109.
[3]鲁长风,田友谊.生成式人工智能嵌入拔尖创新人才培养的潜在风险与突破——基于一项混合研究设计[J].中国电化教育,2025,(3):78-85.
[4]冯永刚,吕鑫源.生成式人工智能嵌入教育的伦理检视[J].中国电化教育,2025,(11):18-25.
[5]Albayati H.Investigating undergraduate students’perceptions and awareness of using Chat GPT as a regular assistance tool:A user acceptance perspective study[J].Computers and Education:Artificial Intelligence,2024,6:100203.
[6]楚金金.大学生对生成式人工智能辅助学术英语写作态度研究[J].中国电化教育,2025,(8):123-130.
[7][26][28] Nguyen A,Hong Y,et al.Human-AI collaboration patterns in AIassisted academic writing[J].Studies in Higher Education,2024,49(5):847-864.
[8][27] Playfoot D,Quigley M,et al.Hey Chat GPT,give me a title for a paper about degree apathy and student use of AI for assignment writing[J].The Internet and Higher Education,2024,62:100950.
[9][10] Biggs J.From Theory to Practice:A Cognitive Systems Approach[J].Higher Education Research&Development,1993,12(1):73-85.
[11][15] Ganotice F A, Chan L K. How can students succeed in computersupported interprofessional team-based learning?Understanding the underlying psychological pathways using Biggs’ 3P model[J]. Computers in Human Behavior,2019,91:211-219.
[12][13][18] Chan C K Y,Hu W.Students’voices on generative AI:perceptions,benefits,and challenges in higher education[J].International Journal of Educational Technology in Higher Education,2023,20(1):43.
[14][16] Li L Y,Tsai C C.Students’patterns of accessing time in a text structure learning system:relationship to individual characteristics and learning performance[J].Educational Technology Research and Development,2020,68(5):2569-2594.
[17]Farhi F,Jeljeli R,et al.Analyzing the students’ views,concerns,and perceived ethics about chat GPT usage[J].Computers and Education:Artificial Intelligence,2023,5:100180.
[19]Davis F.Technology acceptance model:TAM[D].Ann Arbor:University of Michigan,1987.
[20]Tiwari C K,Bhat Mohd A,et al.What drives students toward Chat GPT? An investigation of the factors influencing adoption and usage of Chat GPT[J].Interactive Technology and Smart Education,2023,21(3):333-355.
[21]Al Awadhi S,Morris A.The Use of the UTAUT Model in the Adoption of EGovernment Services in Kuwait[A].Proceedings of the 41st Annual Hawaii International Conference on System Sciences[C].Waikoloa,HI:IEEE Computer Society,2008.
[22]Venkatesh V,Thong J Y L,et al.Consumer Acceptance and Use of Information Technology:Extending the Unified Theory of Acceptance and Use of Technology[J].MIS Quarterly,2012,36(1):157-178.
[23]Budhathoki T,Zirar A,et al.ChatGPT adoption and anxiety:a cross-country analysis utilising the unified theory of acceptance and use of technology(UTAUT)[J].Studies in Higher Education,2024,49(5):831-846.
[24]Abdaljaleel M,Barakat M,et al.A multinational study on the factors influencing university students’ attitudes and usage of Chat GPT[J].Scientific Reports,2024,14(1):1983.
[25]Ojubanire O A. Olaleye S A. et al. Awareness, perception, and adoption of Chat GPT in African HEIs:A multi-dimensional analysis[J].The Internet and Higher Education,2025,65:100999.
[29]von Garrel J,Mayer J.Artificial Intelligence in studies—use of Chat GPT and AI-based tools among students in Germany[J].Humanities and Social Sciences Communications,2023,10:799.
[30][31]李艳,许洁等.大学生生成式人工智能应用现状与思考——基于浙江大学的调查[J].开放教育研究,2024,30(1):89-98.
[32][36] Di W, Danxia X, et al.The effects of learner factors on higher-order thinking in the smart classroom environment[J].Journal of Computers in Education,2019,6(4):483-498.
[33][37][38] Lu K,Yang H H,et al.Examining the key influencing factors on college students ’ higher-order thinking skills in the smart classroom environment[J].International Journal of Educational Technology in Higher Education,2021,18(1):1.
[34]Anderson L W,Krathwohl D R.A Taxonomy for Learning,Teaching,and Assessing:A Revision of Bloom’s Taxonomy of Educational Objectives[M].New York:Longman,2001.
[35]Albadarin Y,Saqr M,et al.A systematic literature review of empirical research on Chat GPT in education[J].Discover Education,2024,3(1):60.
[39]李曼丽,乔伟峰等.大语言模型工具能促进高校学生的高阶思维能力发展吗?——基于12所双一流大学学生问卷调查的实证分析[J].现代教育技术,2025,35(1):34-43.
[40]Michel-Villarreal R,Vilalta-Perdomo E,et al.Challenges and Opportunities of Generative AI for Higher Education as Explained by Chat GPT[J].Education Sciences,2023,13(9):856.
[41]马银琦,黄恒等.“技术赋能”还是“工具依赖”:生成式人工智能对研究生科研创新力的影响研究[J].电化教育研究,2024(12):58-66.
[42]周江林.“双一流”高校数字化转型的价值、偏差与路向[J].研究生教育研究,2024,(3):27-33.
(1)本文所采用的分析方法侧重于关联检验,旨在揭示变量之间的逻辑关系和相互关联,而非进行因果推断。
基本信息:
中图分类号:G434;G645.5
引用信息:
[1]周雪涵,马莉萍,郑翔睿.“态度—行为—能力”框架下的大学生生成式人工智能使用研究:特征、差异与关联分析[J].中国电化教育,2026,No.472(05):57-66.
基金信息:
国家自然科学基金面上项目“生成式人工智能使用模式及其对大学生发展的影响：追踪调查与实验干预”(项目编号：72574011)部分研究成果
2026-05-10
2026-05-10