Generative AI-Empowered Evaluation Systems for Security Education in Vocational Colleges: A Comprehensive Review

Jian Chen; XiangShun Yin; JunLian Tang

doi:10.47297/taposatWSP2633-456917.20260705

PDF
导出
分享
收藏
专辑

Generative AI-Empowered Evaluation Systems for Security Education in Vocational Colleges: A Comprehensive Review

7卷第5期

浏览量: 0 Downloads: 0

Generative AI-Empowered Evaluation Systems for Security Education in Vocational Colleges: A Comprehensive Review
Generative AI-Empowered Evaluation Systems for Security Education in Vocational Colleges: A Comprehensive Review
Chongqing Security Vocational College, Chongqing, 401451, China
2026年7卷第5期页码：85-88
网络首发：2026-07-15，

纸质出版：2026-05-30
DOI：10.47297/taposatWSP2633-456917.20260705
Accepted：

Scan QR Code

Jian Chen, XiangShun Yin & JunLian Tang. (2026). Generative AI-Empowered Evaluation Systems for Security Education in Vocational Colleges: A Comprehensive Review. 科技理论与实践（英文版）, 7(5), 85-88.

Chen Jian,Yin XiangShun,Tang JunLian.Generative AI-Empowered Evaluation Systems for Security Education in Vocational Colleges: A Comprehensive Review[J].Theory and Practice of Science and Technology,2026,07(05):85-88.
Jian Chen, XiangShun Yin & JunLian Tang. (2026). Generative AI-Empowered Evaluation Systems for Security Education in Vocational Colleges: A Comprehensive Review. 科技理论与实践（英文版）, 7(5), 85-88. DOI： 10.47297/taposatWSP2633-456917.20260705.

Chen Jian,Yin XiangShun,Tang JunLian.Generative AI-Empowered Evaluation Systems for Security Education in Vocational Colleges: A Comprehensive Review[J].Theory and Practice of Science and Technology,2026,07(05):85-88. DOI： 10.47297/taposatWSP2633-456917.20260705.

摘要

Abstract

The rapid advancement of generative artificial intelligence (AI) has created unprecedented opportunities for transforming educational evaluation across disciplines. This review examines the convergence of generative AI capabilities

self-efficacy theory

and the distinctive requirements of security education in vocational colleges to propose a four-dimensional evaluation framework — Scenario Simulation

Adaptive Feedback

Competency Profiling

and Reflective Assessment. We systematically analyze the existing literature on generative AI applications in educational assessment

the theoretical foundations of self-efficacy and constructivist learning

and the persistent challenges confronting security education. Our analysis identifies critical barriers to implementation

including algorithmic bias

data privacy concerns

and the risk of technological dependency. The findings indicate that generative AI can fundamentally transform security education evaluation from passive

paper-based testing toward active

scenario-based

and individualized assessment paradigms while simultaneously enhancing student self-efficacy through carefully designed feedback mechanisms.

关键词

Keywords

references

Batista, J., Mesquita, A., & Carnaz, G. (2024). Generative AI and higher education: Trends, challenges, and future directions. Information, 15(11), 676.

Hwang, G.J., & Chen, N.S. (2023). Exploring the potential of generative AI in education. Educational Technology & Society, 26(2), 14-25.

Hwang, G.J., & Chen, N.S. (2024). Generative AI in education: Promises, perils, and pathways. Educational Technology & Society, 27(1), 1-15.

Su, Y., & Yang, W. (2023). Generative AI in education: A comprehensive review. Smart Learning Environments, 10(1), 45.

Alnajim, A.M., Habib, S., Islam, M., et al. (2023). Exploring cybersecurity education and training techniques: A comprehensive survey. Symmetry, 15(12), 2175.

Conklin, W.A. (2023). Cybersecurity education in universities: Current state and future needs. IEEE Access, 12, 48305-48317.

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215.

Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman.

Usher, E.L., & Pajares, F. (2008). Sources of self-efficacy in school: A critical review and synthesis. Review of Educational Research, 78(4), 751-796.

Schunk, D.H., & DiBenedetto, M.K. (2021). Self-efficacy theory in education. Emerald Publishing.

Honicke, T., & Broadbent, J. (2016). The influence of academic self-efficacy on academic performance: A meta-analysis. Educational Research Review, 17, 63-84.

Alnajim, A.M., & Alrawashdeh, H.S. (2024). Leveraging generative AI for cybersecurity education: Opportunities and challenges. IEEE Access, 13, 117473-117490.

Topping, K.J. (2009). Peer assessment: Learning from exemplars. Assessment & Evaluation in Higher Education, 35(5), 539-554.

Liu, Y., Bian, X., Wang, F., & Zhou, X. (2025). Educators' reflections on AI-automated feedback in higher education. Frontiers in Education, 10, 1704820.

Wang, Y.Y., & Chuang, Y.W. (2024). Artificial intelligence self-efficacy: Scale development and validation. Education and Information Technologies, 29, 4785-4808.

Zhang, L., & Xu, H. (2025). The paradox of self-efficacy and technological dependence in AI-assisted learning. Computers in Human Behavior Reports, 16, 100640.

Pellegrino, J.W. (2020). The assessment landscape: A changing ecosystem. Educational Measurement: Issues and Practice, 39(4), 1-12.

Vygotsky, L.S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

Jonassen, D.H. (1991). Objectivism versus constructivism: Do we need a new philosophical paradigm? Educational Technology Research and Development, 39(3), 5-14.

Gulikers, J.T.M., Bastiaens, T.J., & Kirschner, P.A. (2004). A five-dimensional framework for authentic assessment. Educational Technology Research and Development, 52(3), 67-86.

Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press.

Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.

Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.

Achiam, J., et al. (2023). GPT-4 technical report. arXiv preprint arXiv: 2303.08774 .

Zhao, J., Chapman, E., & Ghassemi Pour Sabet, P. (2024). Generative AI and educational assessments: A systematic review. Education Research & Perspectives, 51, 124-155.

Mhlanga, D. (2024). Open AI in education, the responsible and ethical use of ChatGPT towards lifelong learning. Education, Excellence and Equity, 1(1), 51-62.

Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-resolution image synthesis with latent diffusion models. CVPR, 10684-10695.

Betker, J., Goh, G., Im, V., et al. (2023). Improving image generation with better captions. arXiv preprint arXiv: 2303.08774 .

Xia, X., Ruan, C., & Shi, T. (2024). Generative AI for real-time cloud security monitoring and threat intelligence. IEEE Cloud Computing, 12(2), 45-58.

Dhungana, P., & Sharma, R. (2024). Virtual reality for safety-relevant training: A systematic review. Virtual Reality, 28, 23.

文章被引用时，请邮件提醒。

Submit

Research on Generative Artificial Intelligence-Driven Innovation and Aesthetic Expansion in Film and Television Art Design

Research Progress on a Generative AI-Powered Clinical Reasoning Training Model for Rehabilitation Assessment

Research on New Applications of Generative AI in the Supply Chain Field

Application of AI Technology in Film and Television Audio Production

Optimization of Coil Layout and Power Scheduling for Dynamic Wireless Charging Lanes on Highways

Related Author

Yaru Du School of Design and Art, Beijing Technology and Business University

Yonghua Jiang School of Design and Art, Beijing Technology and Business University

Xiuhui Cao Geely University of China

Zhuyao Tang School of Logistics Engineering, Shanghai Maritime University

Lingzi Li Communication University of China, Nanjing, Radio and Television College

Qingzhong Feng Communication University of China, Nanjing, Radio and Television College

Related Institution

School of Design and Art, Beijing Technology and Business University

Geely University of China

School of Logistics Engineering, Shanghai Maritime University

Communication University of China, Nanjing, Radio and Television College

⁰