Systematic Review of Qualitative and Quantitative Studies on Perceived Employability of Graduates

The assessment of future students' employability by the Institute of Higher Learning in collaboration with career centres is one of the most crucial steps in the educational industry for establishing an active and ascendable plan. Predictive analysis for this project is done using machine learning. This study investigates the Employability Signals of Undergraduates in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria. The findings demonstrate that higher education was where the most accurate predictor of undergraduate students' employability was initially examined. The study's conclusions can be used to develop a roadmap that will make it simpler to use predictive analytics. The findings of this study may also facilitate the creation and application of predictive analytics, one of the possible approaches for analysing the education data gathered during the pre-covid period for this study. Systematic literature reviews should be trustworthy, repeatable, and valid when used in scientific investigations. As a result, the inquiry will reach a conclusion based on the evaluations found on pertinent and customized dates.