Abuja – Artificial Intelligence (AI) tools are helping transform entrepreneurship education in Nigerian universities by improving student engagement, creativity, and project performance. Although AI adoption remains at a moderate level, a recent study found that integrating AI into experiential and project-based learning already delivers measurable educational benefits. The research also highlights that successful AI implementation depends heavily on lecturer readiness and strong institutional support. These findings were published in 2026 by Seyi, Bako, Silas, Dashe, and Dauda from Federal University Wukari in the East Asian Journal of Multidisciplinary Research (EAJMR).
Artificial Intelligence has become one of the fastest-growing technologies in higher education, offering new ways to personalize learning, encourage creativity, and strengthen students' practical skills. In entrepreneurship education, AI-powered applications such as intelligent tutoring systems, adaptive learning platforms, and learning analytics provide students with real-time feedback while supporting independent learning and innovation. However, universities in Nigeria continue to face significant challenges in adopting these technologies due to limited digital infrastructure, insufficient institutional readiness, and the need for greater lecturer competence in AI-supported teaching.
The researchers employed a cross-sectional mixed-method design involving 401 students, 70 lecturers, and 9 university administrators from selected Nigerian universities. Participants were chosen using stratified random sampling to ensure balanced representation. Quantitative data were collected through validated online questionnaires, while qualitative information was obtained from structured interviews focusing on experiences and challenges related to AI implementation. The data were analyzed using descriptive statistics, simple linear regression, multiple regression, ANOVA, and t-tests to evaluate the relationship between AI adoption and learning outcomes.
The findings reveal that AI adoption among students remains at a moderate level. Students reported an average AI usage score of 2.91, while their readiness to use AI in learning averaged 2.77. Lecturer encouragement for AI adoption also reached a moderate level with a mean score of 2.51, whereas institutional promotion of AI tools was relatively low at 2.44. These results indicate that AI has begun to influence teaching and learning processes but has not yet become fully embedded within university systems.
From the lecturers' perspective, AI integration into classroom instruction also remains limited. The average score for AI implementation in teaching practice was 2.23, while lecturers' comfort with AI-supported project-based learning reached 2.25. Despite these relatively modest adoption levels, lecturers acknowledged that AI positively influences student engagement and academic performance, with average perception scores of 2.40 and 2.53, respectively. These findings suggest that the educational benefits of AI are already evident even though implementation is still developing.
Statistical analysis demonstrated a significant positive relationship between AI adoption and student learning outcomes. The regression model produced a correlation coefficient of R = 0.48 with R² = 0.23, indicating that AI adoption explains approximately 23 percent of the variation in student engagement, creativity, and project performance. The model was statistically significant with F = 19.88 and p < .001, while regression coefficients confirmed that increased AI usage directly contributes to stronger learning outcomes and better entrepreneurial project performance.
The study also found that successful AI integration depends not only on students but also on lecturers and institutional commitment. Multiple regression analysis showed that lecturer readiness and institutional support together explain 27 percent of the variation in AI implementation across universities. Lecturer readiness demonstrated a significant positive effect with β = 0.41, while institutional support also significantly predicted AI integration with β = 0.32. These findings emphasize that investments in digital infrastructure, staff development, and institutional policies are essential for expanding AI adoption in higher education.
According to Seyi and colleagues from Federal University Wukari, Artificial Intelligence should be viewed as more than a technological tool. When effectively integrated into experiential and project-based learning, AI has the potential to transform entrepreneurship education by creating more interactive, adaptive, and student-centered learning experiences. However, achieving sustainable implementation requires long-term institutional commitment, including improved technological infrastructure, continuous lecturer training, and policies that encourage educational innovation.
The research provides important insights for universities, educators, and policymakers seeking to modernize entrepreneurship education. Rather than introducing AI on an occasional or experimental basis, higher education institutions are encouraged to develop comprehensive implementation strategies supported by investments in digital learning systems, AI literacy programs, and organizational readiness. Such coordinated efforts can help universities prepare graduates with stronger creativity, innovation, and entrepreneurial competencies needed to succeed in an increasingly digital economy.
Authors
Research Source
Article Title: Artificial Intelligence Tools in Experiential and Project-Based Learning in Entrepreneurship Courses in Nigerian Universities
Journal: East Asian Journal of Multidisciplinary Research (EAJMR)
Publication Year: 2026
DOI: https://doi.org/10.55927/eajmr.v5i7.234
Journal Link: https://journaleajmr.my.id/index.php/eajmr
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