The Trust Crisis of News Among Students: Theoretical Construction and Scale Validation based on the Extended TAM Model-A Research on Media Trust Among College Students

DOI: https://doi.org/10.62517/jnme.202610208

Author(s)

Weichang Li

Affiliation(s)

Hainan Tropical Ocean University, Sanya, Hainan, China

Abstract

As generative artificial intelligence (Generative AI, GAI) technology is deeply embedded in the news production chain, AI news has become an important channel for contemporary college students to obtain information. However, the potential authenticity crisis behind it is quietly eroding the young generation's information trust system. This paper focuses on the core issue of "the trust crisis of AI news among students". Based on Davis' classic Technology Acceptance Model (TAM), integrating the information credibility theory and the perceived risk theory, a five-dimensional Extended TAM for AI News (ETAN) model suitable for the context of AI news is constructed, and a high-reliability and high-validity measurement scale containing 18 items is developed. Through a questionnaire survey of undergraduates and postgraduates in multiple universities across the country and the analysis of the Structural Equation Model (SEM), the study finds that the student group shows a significant psychological paradox of "high convenience-low credibility" towards AI news. That is, the scores of perceived usefulness (PU) and perceived ease of use (PEOU) are generally higher than 5.5 (on a 7-point scale), while the average score of content accuracy (CA) is lower than 4.0, and the perceived risk (PR) exceeds 5.0. Further mechanism analysis shows that perceived risk plays a key mediating role in the process of AI news acceptance. It indirectly inhibits the behavioral intention (BI) by weakening the evaluation of content accuracy. This study not only fills the theoretical gap in the existing literature on the trust mechanism of AI news among students, but also provides empirical support and governance path suggestions for media institutions, education departments, and platform regulators. In the future, a hybrid communication model of "AI + manual review" should be promoted, media literacy education should be strengthened, and responsible AI communication ethics norms should be established.

Keywords

AI News; College Student Group; Trust Crises; Financial Trust Crisis; The Technology Acceptance Model (TAM); Perceived Risk; Content Accuracy; Media Literacy; Scale Development

References

[1] Davis F D. Perceived usefulness, perceived ease of use, and user acceptance of information technology [J]. MIS Quarterly, 1989, 13 (3): 319–340. [2] Venkatesh V, Davis F D. A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies [J]. Management Science, 2000, 46 (2): 186–204. [3] Metzger M J. Making sense of credibility on the web: Models for evaluating online information and recommendations for future research [J]. Journal of the American Society for Information Science and Technology, 2007, 58 (13): 2078–2091. [4] Zhang Chi. A Study on College Students' Willingness to Use Generative AI Tools-Based on the Technology Acceptance Model [J]. Science & Technology Communication, 2023 (23): 131-135. [5] Fu Jiarui. A Research Report on the Cognition and Application of Generative AI Technology among Domestic MTI Students [D]. Guangdong University of Foreign Studies, 2024. [6] Zhao Jiachen. The Influence of New AI-Designed Products on Consumers' Willingness to Give Word-of-Mouth [D]. Chongqing Jiaotong University, 2024. [7] An Hui. A Study on the Influencing Factors of the Willingness of the Elderly to Use AI [J]. Modern Marketing, 2024 (6): 36-38. [8] Wang Jiayu. A Study on the Influencing Factors of the Acceptance Willingness of Art Audiences towards AI-Generated Paintings [D]. University of Science and Technology of China, 2023. [9] RIEH S Y. Judgment of information quality and cognitive authority in the web [J]. Journal of the American Society for Information Science and Technology, 2002, 53 (2): 145–161. [10] Sunstein C R. Republic.com 2.0[M]. Princeton University Press, 2017. [11] Featherman M S, Pavlou P A. Predicting e-services adoption: A perceived risk facets perspective [J]. International Journal of Human-Computer Studies, 2003, 5 (94): 451–474. [12] Guo Jianglan. Criticism and Transcendence of the Regulation of High-Risk AI [J]. Journal of Beijing University of Technology (Social Sciences Edition), 2025 (4): 144-156. [13] Yang Hongmei, Wu Honghong, Dai Shuang. Research on the New Paradigm of Cybersecurity Empowered by AI [J]. Telecommunications World, 2024 (13): 30-32.