Testing an Entrepreneurial Structural Model Regarding Artificial Intelligence and Individual Innovation Capability Among Technical and Engineering Students at the University of Tehran

Document Type : Research Paper

Authors

1 Associate Professor, Department of Energy, Materials and Energy Research Center, karaj, Iran.

2 Associate Professor, Department of Educational Sciences, Payame Noor University, Tehran, Iran

3 Associate Professor, Department of Educational Sciences, Payame Noor University

4 PhD student, Department of Educational Sciences, Payame Noor University, Tehran, Iran

Abstract

This study aimed to test a structural model explaining the relationships among artificial intelligence literacy, perceived third-generation university support, AI-based entrepreneurial learning, entrepreneurial alertness, and individual innovation capability among engineering students at the University of Tehran. The study was applied in purpose, quantitative in approach, and descriptive-correlational in design. The statistical population consisted of engineering students at the University of Tehran, from whom 384 students were selected using Cochran’s formula and a multistage stratified cluster sampling method. Data were collected through questionnaires measuring the study constructs. The preliminary psychometric properties of the instruments were examined using exploratory factor analysis, confirmatory factor analysis, and Cronbach’s alpha. Data were analyzed through structural equation modeling. The proposed structural model demonstrated acceptable fit according to the reported goodness-of-fit indices. Artificial intelligence literacy and perceived third-generation university support had positive structural relationships with AI-based entrepreneurial learning. In addition, AI-based entrepreneurial learning was positively related to individual innovation capability both directly and indirectly through entrepreneurial alertness. The bootstrap results supported the mediating roles of AI-based entrepreneurial learning and entrepreneurial alertness in the model. Within the limits of a cross-sectional self-report design, engineering students’ innovation capability is associated with the interplay of AI literacy, perceived institutional support, entrepreneurial learning, and opportunity recognition. Universities seeking to strengthen students’ innovation capability should design problem-oriented entrepreneurial learning experiences that promote critical, ethical, and purposeful use of artificial intelligence tools.

References

منابع
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Innovation Economic Ecosystem Studies
Volume 6, Issue 2
June 2026
Pages 51-84

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