ARTICLE

Volume 2,Issue 1

All Issues
Submit to EDS
Cite this article
0
Views
20 January 2026

Algorithmic Trust Bias Among College Students in the Age of Artificial Intelligence: A Study on Cognitive Generation Mechanisms and Value-Oriented Issues

Xiaohua Qiu1 ,  Weiwei Wang*
Show Less
1 Central University of Finance and Economics, Beijing 100081, China
EDS 2026 , 2(1), 32–37; https://doi.org/10.61369/EDS.202601006
© 2026 by the Author. Licensee Art and Technology, USA. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC BY-NC 4.0) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Download PDF
Cite
XML
HTML
Abstract

Against the backdrop of artificial intelligence’s deep integration into higher education, the stable feedback and efficient output of generative AI have led college students to develop algorithmic trust bias. This is manifested in overreliance on algorithmic outputs, diminished multi-source verification practices, and passive absorption of values. The underlying causes are associated with AI’s technical advantages, reduced learning workload, and weakened critical judgment capabilities. Universities need to construct a governance system centered on multi-source input, conceptual reinforcement, critical thinking training, and value orientation. By regulating the use of AI and reconstructing cognitive chains, institutions can help students maintain cognitive subjectivity and mitigate structural risks in talent cultivation.

Keywords
Generative intelligence
Algorithmic trust bias
Value judgment
Higher education
Cognitive structure
Funding
2024 Beijing Research Project on the Integration of Ideological and Political Education in Primary, Secondary and Tertiary Schools, “Research on the Integrated Teaching of Ideological and Political Courses in Primary, Secondary and Tertiary Schools from the Perspective of the ‘Three Adaptations’ Concept” (Project No.: XXSZ2024YB04); Theoretical Research Project on Party Building and Ideological and Political Work of Central University of Finance and Economics in 2025–2026, “Research on the Characteristics of College Students’ Network Social Circle Stratification and Discourse Guidance Strategies of Mainstream Ideology” (Project No.: DJD25005); the CUFE Postgraduate students support program for the integration of research and teaching, “Research on the Opportunities, Challenges and Paths of AI-Empowered Mainstream Ideological Construction” (Project No.: 2025216)
References

[1] Zheng XD, Hu KY, Yang JM, et al., 2025, Where Exactly Are Education and Learning Heading in the Age of Artificial Intelligence—An Examination Based on the Embodied Cognition Perspective. Modern Distance Education Research, 37(6): 11–23.

[2] Li Y, Dai Y, 2026, Artificial Intelligence as a Method: Systematic Generation and Governance Reconstruction of the Integration of Educational Technology Talents. Journal of Higher Education Evaluation, 42(1): 102–112 + 185–186.

[3] Shang ZC, Yan YH, 2023, The Educational Application of ChatGPT and Its Transformations and Ethical Challenges. Journal of Northeast Normal University (Philosophy and Social Sciences Edition), (5): 44–54.

[4] Liang JB, Xie Y, Tang ZH, 2025, Mechanism, Challenges and Countermeasures of Generative Artificial Intelligence Empowering the Digital Transformation of Education. Modern Education Management, (11): 15–23.

[5] Yang DZ, He JJ, 2025, Philosophical Reflection on the Reform of School Science Education from the Perspective of Artificial Intelligence. Journal of Dialectics of Nature, (11): 100–107.

[6] Ou JJ, 2025, Toward a “Harmonious Engineering”: Philosophical Evolution and Path Transformation of Engineering Education in the Age of Artificial Intelligence. Chongqing Higher Education Research, 14(1): 33–42.

[7] Wei R, Duan SJ, 2025, The Form and Guidance Direction of AI Empowering the Dissemination of Ideological and Political Education Discourse in Colleges and Universities. Educational Research, (10): 124–134.

[8] Anonymous, 2025, Artificial Intelligence Driving Educational Reform: Application Fields, Practical Challenges and Future Prospects. Journal of the Chinese Society of Education, (S1): 4–6.

[9] Wang YM, Wang XY, Liu CC, 2024, Research on the Ethical Risk Management Framework for the Application of Generative Artificial Intelligence in Education. E-education Research, (10): 28–34.

[10] Tong H, Yang YJ, 2024, Potential and Risk Research of Generative Artificial Intelligence in Educational Applications Based on the “Moralization of Technology” Theory. E-education Research, (7): 12–18.

[11] Chai N, Cao BQ, 2025, From Value Alignment to Value Symbiosis: Ethical Risks and Governance of School Education in the Intelligent Era. Modern Distance Education Research, 37(6): 104–111.

[12] Wang JH, 2025, Reconsidering the Relationship Between Education and Technology. Open Education Research, (5): 4–10.

[13] Liang Y, Zhang W, 2025, The Theoretical Framework, Practical Paradoxes and Path Optimization of DeepSeek Empowering Ideological and Political Education in Vocational Colleges. Inner Mongolia Social Sciences, (6): 181–189.

[14] Xuan RT, 2025, Research on the Application, Potential Risks and Countermeasures of AI Agents in Vocational Education. China Computer & Communication, (22): 205–211.

[15] Su JJ, Ye HS, 2025, From Embodied Intelligence to Educational Innovation: Multi-Disciplinary Construction of Cognitive Growth Paths. Open Education Research, (5): 79–88.

Share
Back to top
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here
Accept