Abstract:
The field of entrepreneurship education (EE) is intricate and necessitates a thorough evaluation incorporating a broad spectrum of research. This study addresses this gap by utilizing big data analytics and machine learning techniques to analyze existing EE research. By dissecting the most prominent publications, journals, and authors in the EE domain, this study presents an up-to-date overview of the current state of research. The investigation focuses on seven key themes in EE research, namely gender and pedagogy, innovation and technology transfer, entrepreneurial intention, entrepreneurial mindset, entrepreneurial learning, entrepreneurial ecosystem and self-efficacy, and the theory of planned behavior. Through a systematic analysis, this paper provides valuable insights and recommendations for future research in EE. These recommendations include investigating the impact of Entrepreneurship Education on students, exploring the role of entrepreneurial intentions in start-up success, assessing the influence of Entrepreneurship Education on entrepreneurial intentions and capabilities, formulating strategies for effective Entrepreneurship Education and entrepreneurial intentions, and examining the factors that influence entrepreneurial intentions in university students. By addressing these research areas, this study aims to propel the field of EE forward and contribute to a more comprehensive understanding of entrepreneurship education.
