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This study utilizes the K-Means clustering algorithm to analyze the vision and mission statements (VMS) of 117 Philippine state universities and colleges (SUCs). The most frequently occurring keywords were identified as “development” and “research.” Through expert validation, three distinct clusters emerged for the vision statements: “Globally Competitive and Nationally Responsive Workforce for Sustainable Development,” “Universities of Premier Recognition,” and “Regional Leadership in Science and Technology.” The mission statements were similarly categorized into three clusters: “Mandated Functions of the SUCs,” “Global Innovation Toward Sustainable Development,” and “Advancement in the Sciences.” SUCs across Luzon, Visayas, and Mindanao share a common vision of becoming global leaders in technology while adhering to their core mandates. This study demonstrates the potential of web scraping and K-Means clustering in VMS analysis and highlights the opportunity for future research to include private higher education institutions and expand geographically.

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Analysis of the Vision-Mission Statements of State Universities and Colleges in the Philippines Using K-Means Clustering

  • 会议论文

  • 发表日期：

    2025年

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  • Julius Ceazar G. Tolentino,
  • John Paul P. Miranda

摘要

This study utilizes the K-Means clustering algorithm to analyze the vision and mission statements (VMS) of 117 Philippine state universities and colleges (SUCs). The most frequently occurring keywords were identified as “development” and “research.” Through expert validation, three distinct clusters emerged for the vision statements: “Globally Competitive and Nationally Responsive Workforce for Sustainable Development,” “Universities of Premier Recognition,” and “Regional Leadership in Science and Technology.” The mission statements were similarly categorized into three clusters: “Mandated Functions of the SUCs,” “Global Innovation Toward Sustainable Development,” and “Advancement in the Sciences.” SUCs across Luzon, Visayas, and Mindanao share a common vision of becoming global leaders in technology while adhering to their core mandates. This study demonstrates the potential of web scraping and K-Means clustering in VMS analysis and highlights the opportunity for future research to include private higher education institutions and expand geographically.