Training and Seminar Recommender System Using Rule-Based Algorithm (77606)
Session Chair: Peter Leong
Sunday, 18 February 2024 09:55
Session: Session 1
Room: Kirimas
Presentation Type: Oral Presentation
Training and seminars play a crucial role in enhancing professional development, especially in academe. Faculty members should attend relevant training and seminars to help them stay up-to-date with the latest trends and technologies in their field. This study focused on the design and development of a Training and Seminar Recommender System Using a Rule-Based Algorithm for the College of Information and Communications Technology (CICT). This is to ensure the faculty members receive targeted suggestions that align with their specific needs and provide the best training and seminars that can improve faculty educational competence. The system aims to utilize the rule-based algorithm in providing a decision support mechanism for the administrators in recommending suited training and seminars based on faculty qualification. It's crucial to balance and send faculty to training that matches their needs to ensure good results. The constraints used were specialization, schedule, location, and budget. The descriptive research was used in the study through a survey questionnaire. This involved 77 college faculty members. The researcher used Rapid Application Development (RAD) to simulate software development, creating multiple prototypes until all functional requirements were met. To assess the level of acceptability, the Technology Acceptance Model (TAM) based on a descriptive Likert model scoring was used. The system got a 4.52 mean average score based on the respondent’s evaluation with a verbal interpretation of the “Very Acceptable” rating.
Authors:
Lilibeth Antonio, Bulacan State University, Philippines
About the Presenter(s)
Dr LILIBETH ANTONIO is a School Administrator at Bulacan State University in Philippines
See this presentation on the full schedule – Sunday Schedule
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