Descriptive Feedback on Interns’ Performance using a text mining approach

Descriptive feedback is a powerful tool to identify the strength and the areas that need improvement of a certain program. Text analysis using the text mining approach is the most common application in the text processing field. This study aimed to determine the potentials and the imperfections of the IT interns while taking the internship program using a Naive Bayes text classification. Text dataset from the internship program of the IT curriculum under the College of Computer Studies and Information Technology (CCSIT) of Southern Leyte State University (SLSU) was the input of the study. This study applied the text mining application using the Naïve Bayes text classification to evaluate the performance of the IT interns. Results show that the IT interns of the program were proficient and technically competent but had a problem with their communication skills. The model has obtained an acceptable accuracy rating of 87.55% in predicting the performance of the students. Based on the results, the IT interns were efficient in the IT-related task. However, there is a need to improve interns’ communication skills. The management should think about a possible bridging program that will help the student to develop their communication skills.

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