Designing the Future of Entrepreneurship Education: Exploring an AI-Empowered Scaffold System for Business Plan Development

2025-05-29

AI Summary

Traditional entrepreneurship education lacks personalized guidance and practical scaffolding, hindering students’ ability to transform creative ideas into viable business plans. To address this, this study designs and implements an AI-augmented scaffolding system supporting the end-to-end development of business plans, enabling personalized learning pathways and dynamically adaptive feedback. Grounded in educational theory and explainable AI (XAI) principles, the system introduces a novel three-dimensional design framework—comprising mastery modeling, goal alignment, and adaptive scaffolding—validated through qualitative interviews, participatory needs modeling, and iterative prototyping. The research identifies three transferable system design dimensions, offering empirically grounded, actionable guidelines for AI-integrated entrepreneurship education. Findings advance the pedagogical shift from didactic instruction toward intelligent, human-AI collaborative learning environments.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Multiagent Systems: Agent/AI Theories and Architectures
• Intelligent Robots: Embodied AI

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

Entrepreneurship education equips students to transform innovative ideas into actionable entrepreneurship plans, yet traditional approaches often struggle to provide the personalized guidance and practical alignment needed for success. Focusing on the business plan as a key learning tool and evaluation method, this study investigates the design needs for an AI-empowered scaffold system to address these challenges. Based on qualitative insights from educators and students, the findings highlight three critical dimensions for system design: mastery of business plan development, alignment with entrepreneurial learning goals, and integration of adaptive system features. These findings underscore the transformative potential of AI in bridging gaps in entrepreneurship education while emphasizing the enduring value of human mentorship and experiential learning.

Problem

• AI system for personalized business plan guidance
• Bridging gaps in entrepreneurship education
• Integrating adaptive features with human mentorship

Innovation

• AI-empowered scaffold system design
• Personalized business plan guidance
• Adaptive entrepreneurial learning integration