Researcher Evaluation, Assessment, and Database System (READS): An AI-based Performance Analysis
Authors: Aileen U. Balbido, Adrianne N. De Guzman, Darien Chelsey P. Galura, Alfonso Miguel A. Alfonso, Jason Paul L. Villanueva, Timothy M. Amado, Glenn C. Virrey, Cherry G. Pascion, John Peter Ramos, Ira C. Valenzuela
Abstract
Research is a central function of a university and each faculty has rewarded a chance to undertake it in their preferred field. However, researchers are merely assessed objectively instead of assessing analytically in a way that scores are provided and calculated systematically. Many researches have been conducted to produce for the performance of a researcher. Yet, smarter algorithms are being sought. This study aims to develop an intelligent monitoring framework as a web application for assessing and observing faculty researchers in R&D of various colleges of the Technological University of the Philippines- Manila. Based on the literature review on faculty research performance, specific factors were used as the basis for evaluation. These factors were based on the criteria for the best researcher in the university namely: number of completed projects, research dissemination, patent or copyright certification, utilization of research, research-related awards, educational attainment, and Google Scholar metrics. These factors are given weight to be computed as T-index – the faculty researcher performance indicator. Research priorities or categories are also put into consideration. Subsequently, it was merged into the software system developed. This study became effective in the University deployment and put into good use in University Researcher and Development Services (URDS) Office. The developed web platform helped in recognizing distinguished researchers, level-up their research performance, and unleashed the researcher’s potential. Furthermore, the website helped the researcher to monitor their research activity and research field in which they succeeded.