Development of a Graduate Employability Dashboard for Community Colleges

Abstract

Sistem Kajian Pengesanan Graduan (SKPG), also known as the Graduate Tracer Study, is a structured survey implemented by Malaysia’s Ministry of Higher Education (MOHE) to monitor the employment outcomes of graduates from higher education institutions. Graduate Tracer Studies (GTS) serve as an important mechanism for examining the relationship between higher education and labour market needs. These studies provide insights into graduates’ employment status, job relevance, career progression, and level of satisfaction with the programmes and institutions they attended. The implementation of GTS involves several key stages, including study design, identification of data sources, selection of the target population, determination of the appropriate survey period, and the development of comprehensive questionnaires. Data are collected by engaging graduates directly, and the findings are subsequently analysed and presented to support institutional planning, curriculum improvement, policy development, and graduate employability initiatives. This project is designed to share relevant international expertise and best practices in Graduate Tracer Studies with Jabatan Pendidikan Politeknik dan Kolej Komuniti (JPPKK), Malaysia. In addition, the integration of Machine Learning (ML) into graduate tracer study analysis can enhance the prediction of graduate employability rates. By using ML techniques, educational institutions can gain deeper insights into the effectiveness of their programmes and make more informed decisions to align academic offerings with students’ needs and labour market demands.