Artificial Intelligence in Entrepreneurship Education: An Empirical Investigation of Student Self- Efficacy, Learning Outcomes, and Equity Concerns

Abstract

Ese Sophia Mughele and Cyprian Akhere Okoduwa

This empirical study investigates the impact of Artificial Intelligence (AI) integration on entrepreneurial self-efficacy, learning outcomes, and equity in higher education. Despite growing AI adoption in entrepreneurship pedagogy, concerns persist regarding differential outcomes across student ability levels, ethical implications, and inadequate pedagogical frameworks. Through a quantitative survey design employing validated Likert-scale instruments, this study examines three hypotheses: (H1) AI integration positively influences entrepreneurial self-efficacy; (H2) AI-enhanced pedagogy differentially impacts students based on prior academic performance; and (H3) perceived ethical concerns moderate the relationship between AI use and learning outcomes. Data collected from 384 entrepreneurship students across three universities were analyzed using structural equation modeling and hierarchical regression analysis. Results confirm significant positive effects on self-efficacy (β = 0.58, p < .001) but reveal troubling disparities, with high-performing students demonstrating 20% improvement while lower-performing students experienced 10% decline. Ethical concerns significantly moderated AI effectiveness (β = -0.34, p < .01). Findings underscore the "capability paradox" threatening educational equity and necessitate evidence-based pedagogical frameworks, verification protocols, and ethical governance mechanisms to ensure AI serves as cognitive amplifier rather than inequality amplifier.

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