Scholarlink

This research explores the application of Institutional Research (IR) in higher education institutions and how systematic data collection and analysis can enhance operational efficiency and decision-making quality. The focus is on analyzing course content to better allocate educational resources and improve teaching quality. By combining the framework of Multiple Intelligences (MI) theory with the natural language processing capabilities of large language models, we offer a new perspective for course analysis. To determine the optimal number of clusters, we first use the elbow method and then apply the K-means algorithm to understand the characteristics of courses within each cluster. This approach provides important references for educational institutions to improve teaching quality and meet student needs.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Construction of Course Intelligence Feature Matrix Based on Multiple Intelligences and LLM and Its Application in Cluster Analysis

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Tzu-Chuen Lu,
  • Yu-Che Chien

摘要

This research explores the application of Institutional Research (IR) in higher education institutions and how systematic data collection and analysis can enhance operational efficiency and decision-making quality. The focus is on analyzing course content to better allocate educational resources and improve teaching quality. By combining the framework of Multiple Intelligences (MI) theory with the natural language processing capabilities of large language models, we offer a new perspective for course analysis. To determine the optimal number of clusters, we first use the elbow method and then apply the K-means algorithm to understand the characteristics of courses within each cluster. This approach provides important references for educational institutions to improve teaching quality and meet student needs.