Charting Paths: A Graduate Tracer Study on the Employability of Engineering Graduates of the Polytechnic Institute of Tabaco
DOI:
https://doi.org/10.5281/zenodo.20140514Keywords:
graduate tracer study, employability, engineering graduates, curriculum relevance, job placement, higher educationAbstract
This study examined the employability of engineering graduates from the Polytechnic Institute of Tabaco (PITA) covering graduates from 2005 to 2022 across three programs: Bachelor of Science in Electrical Engineering (BSEE), Bachelor of Science in Computer Engineering (BSCoE), and Bachelor of Science in Electronics Engineering (BSECE). Using a quantitative descriptive survey design, data were gathered from 137 out of 163 graduates (84.04% response rate) through an online questionnaire adopted from the Commission on Higher Education (CHED) Graduate Tracer Study instrument. The study established the demographic profiles of the respondents, determined their job placement profiles, and assessed the relevance of the curriculum and useful skills acquired during college. Results revealed that the majority of graduates were male (77%), single (71%), and aged 24–37 years. The BS in Electrical Engineering had the highest number of graduates and the highest employment rate (86.05%). A significant 83.94% of the graduates were currently employed, with 62.04% finding their first job related to engineering. Nearly half (48.91%) secured employment in less than a month. The majority of graduates (70.80%) found their college curriculum relevant to their first job. Communication and problem-solving skills were identified as the most useful competencies in both their first and current jobs. However, no graduates from BSECE passed the licensure examination, and 44% of BSEE graduates did not pass. The findings underscore the need for curriculum enhancement, strengthened board examination preparation, and continuous alignment of engineering programs with industry demands. This study serves as a baseline for future tracer studies and provides data-driven recommendations for institutional improvement.
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