Ilocos Sur Polytechnic State College

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Abstract

Educational institutions are progressively integrating technological tools and platforms to improve the process of faculty performance evaluation. Using a comprehensive, evidenced-based system to document, analyze, and enhance teaching effectiveness is essential to ensuring excellence in teaching and learning. This study aimed to integrate the innovative approach of data analytics into an online faculty evaluation system for Ilocos Sur Polytechnic State College-Main. Descriptive and developmental methods were used as the study involved survey and software development. The researchers employed the Agile framework methods during the development of the system. A total of 218 participants was selected through sampling techniques.  The participants’ responses from the unstructured interview were the bases of the upgrade, uncovering the current status of the existing faculty performance evaluation system. A comparative analysis was conducted to assess the usability of the current Faculty Performance Evaluation System (FPES) and the upgraded FPES. The results revealed a significant improvement in the overall usability rating of the upgraded FPES, achieving a "very high" level, as compared to the "moderate" rating of the existing FPES. The result implies that the enhanced EFPES manifested a positive impact in the College’s performance evaluation process, thus it is a favorable alternative to the existing system. Nonetheless, carrying out the recommendations, particularly enhancing the system’s functionalities on the integration of higher form of data analytics will provide a more inclusive and insightful analysis of faculty performance.

Full Article

DOI: https://doi.org/10.56901/KXPW6512

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Big Data Analytics for Network Anomaly Detection

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