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Mi, Y., Xu, Z., & Luo, J. (2018). Exploration of Whole-Process Multi-Dimensional Collaborative Practical Education for Innovation and Entrepreneurship among College Students. Research and Exploration in Laboratory, 37, 237.

has been cited by the following article:

• TITLE: The Advantages and Constraints of LLM-Augmented Knowledge Graphs in University Innovation and Entrepreneurship Education

  AUTHORS: Bingqi Liu, Zhi Weng, Ayinhu

  KEYWORDS: Large-Scale Models, Knowledge Graph, Innovation and Entrepreneurship Education, Constraints

  JOURNAL NAME: Advances in Applied Sociology, Vol.16 No.1, January 13, 2026

  ABSTRACT: This paper investigates the integration of Large Language Models with Knowledge Graphs (LLM-KGs) into the pedagogical framework of higher education, specifically within innovation and entrepreneurship programs. It argues that this synergy can catalyze a shift toward more intelligent and data-informed educational practices. However, the implementation is scrutinized through a critical lens, revealing significant constraints in data governance, a growing digital divide among faculty, and systemic institutional inertia. In response, the study proposes a set of strategic interventions designed to provide both a conceptual foundation and actionable guidance for the effective adoption of LLM-KG systems in university settings.