Analysis of Faculty Evaluation by the Students using K-Means and Term Frequency-Inverse Document Frequency with Bag of Words Model

Alexandra Marie  M. Balane,; Jellimilcha  R. Dumalaon,; Ryan Christian  A. Imperial,

Analysis of Faculty Evaluation by the Students using K-Means and Term Frequency-Inverse Document Frequency with Bag of Words Model

Alexandra Marie M. Balane | Jellimilcha R. Dumalaon | Ryan Christian A. Imperial

Abstract:

The Faculty Performance Evaluation (FPE) of Letran Calamba is a monitoring system intended to recognize and reinforce the accomplishments of faculty members as they contribute to the realization of the mission of the Colegio. A tool named NETFES (Network Faculty Evaluation System) is used by the students to appraise their professors’ performance every term, but the system lacks an in-depth analysis of the evaluation results. The quantitative results are simply averaged and presented in a table. There is also a gap in interpreting the open remarks of faculty members; the evaluators need to go through each comment and there is no technique to single out the significant remarks left by the students. An application of data mining to determine underlying patterns in these results would be beneficial not only to the faculty and department heads, but also to the Human Resources and Academics divisions for the further improvement of overall faculty performance. This study developed a system that analyzed the data taken from the faculty evaluation by the students. It determined which areas of the evaluation the faculty are excellent at and which areas they could improve on through cluster analysis. Visualizations of the data were also generated, and these helped simplify the process of understanding tabular data. Additionally, trends in the data were shown, and open remarks left by the students were evaluated to determine which comments were significant. These allowed the evaluator to tag them as positive or negative.