Torn between realism and guidance in entrepreneurship education

Abstract

Although experiential entrepreneurship education requires balancing realism and instructional guidance, it remains unclear how these elements should be designed and how concrete design decisions shape individual learning processes. This dissertation examines the design and effects of metaverse-enhanced realism and AI-supported guidance in business simulation games. Drawing on five studies combining Action Design Research, value-added research, and complexity-informed analytics, the findings show that enhanced realism and adaptive guidance do not automatically improve learning processes. Rather, their effects depend on learner characteristics, contextual conditions, and temporal dynamics. Synthesizing these insights, the dissertation develops a Synergetic Model of Experiential Learning Dynamics in Entrepreneurship Education, conceptualizing entrepreneurial learning as a complex, non-linear process emerging from interactions between instructional design, individual learner charactierstics, and context over time.