Reimagining STEM learning : a comparative analysis of traditional and service learning approaches for social entrepreneurship

Abstract

This study examines a practical Teaching and Learning cycle tailored to integrate cutting-edge technologies (artificial intelligence (AI), machine learning,(ML) game development) and social entrepreneurship within a 'STEM with meaning' approach. This cycle, grounded in service learning and the 5E constructivist teaching model, aims to transcend the traditional lecture-based approach by fostering a comprehensive understanding of technology's societal impacts. Through a comparative analysis involving experimental and comparison groups, we evaluate the cycle's effectiveness in enhancing students' problem-solving skills, empathy, knowledge application, and sense of social responsibility-essential qualities for successful social entrepreneurs. This paper contributes to the burgeoning field of entrepreneurship education by demonstrating the value of a pedagogical approach that combines AI, machine learning, and game development with a strong emphasis on social entrepreneurship. Our results advocate a shift towards educational models that prepare students with technical skills and the awareness and capabilities needed to address complex social issues. Through this research, we highlight the critical role of innovative teaching methods in cultivating the next generation of socially responsible entrepreneurs, thereby enriching both the educational landscape and society at large.