This study classifies the entrepreneurial profiles of students enrolled in the Business Development course at the National Agrarian University La Molina (UNALM), analyzing the variables of gender, age, and field of study. A non-experimental quantitative methodology was employed, using a survey validated by the Wadhwani Foundation, followed by a cluster analysis with the K-Means algorithm. The results identified two clusters of students with entrepreneurial tendencies and revealed a significant relationship between gender, age, and field of study with entrepreneurial profiles. Findings indicate that each student exhibits at least one type of entrepreneurial style, with certain profiles being more prevalent depending on gender and field of study. This study provides valuable insights for designing educational programs that foster entrepreneurship among diverse student groups.

This study classifies the entrepreneurial profiles of students enrolled in the Business Development course at the National Agrarian University La Molina (UNALM), analyzing the variables of gender, age, and field of study. A non-experimental quantitative methodology was employed, using a survey validated by the Wadhwani Foundation, followed by a cluster analysis with the K-Means algorithm. The results identified two clusters of students with entrepreneurial tendencies and revealed a significant relationship between gender, age, and field of study with entrepreneurial profiles. Findings indicate that each student exhibits at least one type of entrepreneurial style, with certain profiles being more prevalent depending on gender and field of study. This study provides valuable insights for designing educational programs that foster entrepreneurship among diverse student groups.

This study classifies the entrepreneurial profiles of students enrolled in the Business Development course at the National Agrarian University La Molina (UNALM), analyzing the variables of gender, age, and field of study. A non-experimental quantitative methodology was employed, using a survey validated by the Wadhwani Foundation, followed by a cluster analysis with the K-Means algorithm. The results identified two clusters of students with entrepreneurial tendencies and revealed a significant relationship between gender, age, and field of study with entrepreneurial profiles. Findings indicate that each student exhibits at least one type of entrepreneurial style, with certain profiles being more prevalent depending on gender and field of study. This study provides valuable insights for designing educational programs that foster entrepreneurship among diverse student groups.

This study aims to conduct a bibliometric analysis to investigate the current state of artificial intelligence (AI) adoption and utilization in higher education. A quantitative methodology was employed, analyzing 1476 scientific articles from renowned databases such as Scopus and Web of Science. Data was processed using the digital tools R and VOSviewer. The findings reveal an exponential growth in publications, with a growing focus on personalized learning, automated assessment, and the use of tools like ChatGPT. Significant international collaborations were identified; however, ethical challenges and the need for appropriate policies to ensure equitable and effective AI implementation in education were also highlighted. This study provides a global overview of research trends in AI in higher education, examining its applications, opportunities, and challenges for the teaching-learning ...