Adaptive Personalized Learning Systems: Enhancing Innovation and Entrepreneurship in Software Engineering Education

Abstract

Innovation and entrepreneurship are critical skills for university students in today’s fast-paced global economy. However, traditional educational models frequently fail to accommodate the diverse learning needs and aspirations of students, particularly in innovation-related fields such as programming, web design, and databases. This study presents a personalized learning system designed to enhance student engagement and foster entrepreneurial skills. The system utilizes academic performance data to generate tailored course recommendations, categorizing students by proficiency and aligning learning paths with their educational history, competencies, and career aspirations. The system was tested with 200 students from the Software Engineering Department at Al-Zaytoonah University of Jordan, using academic records, system interaction logs, and student surveys to collect data. The methods used for data analysis include both quantitative and qualitative approaches. Pre-and post-test performance scores were analyzed using statistical tests, such as t-tests, and descriptive statistics. Survey responses were analyzed using qualitative coding techniques. Results showed a 35% increase in student engagement and a 20% increase in academic performance. Further, 78% of students indicated increased readiness to work on innovative projects. This study makes a significant contribution to the literature on personalized learning and supports students' preparation for careers in rapidly evolving, innovation-driven industries.