Volume 2 - Issue 2, March - April 2026

The aim of this research is to propose an AI-Driven Feedback Generation System where the sentiment analysis outputs perplexity range from textual-based feedback responses STU/PART involved in any educational or education-based event which is related to IT. We developed the system to accelerate feedback collection and interpretation by applying natural language processing (NLP) and ML algorithms which automatically classify the notions, generate smart reports for teachers and event organizers. The work is carried out by means of a developmental study that combines AI models such as Naïve Bayes and transformer sentiment classifiers from fine-tuned contextual data collection. Based on system efficiency, accuracy and user satisfaction system test with IT students and staff were conducted. Results indicate that automatically analyzed sentiment-based feedback facilitates the evaluation process being less costly and more informative in terms of participant experiences. The usability (SUS) score of the system was 81.2, interpreted as excellent meaning that it could be used in educational and institutional contexts.

Reginald S. Prudente, Angeline C. Mangalay, Ralph Kevin J. Padios, Doffer John Temperatura,"AI-Driven Automated Feedback Generation System Using Sentiment Analysis in IT Education and Events" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(1635-1653) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.