Student learning progress as predictor for graduate employability performance

• Main Authors: Wan Nor Afiqah, Wan Othman, Aziman, Abdullah
• Format: Conference or Workshop Item
• Language: English
• Published: IOP Publishing 2020
• Subjects: LB2300 Higher Education; LB2361 Curriculum; QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/29835/1/Student%20Learning%20Progress%20as%20Predictor%20for%20Graduate.pdf; http://umpir.ump.edu.my/id/eprint/29835/; https://doi.org/10.1088/1757-899X/769/1/012019; https://doi.org/10.1088/1757-899X/769/1/012019

Graduate employability is a major concern for higher education industry. There is a lack of research on the use of program learning outcomes (PLO) data to predict graduate employability performance especially on the duration they get employed. Therefore, our motivation in this study is to investigate how PLO data can be used to predict graduate employability performance. This study adopted quantitative analysis as a research method by using Simple Linear Regression to measure the highest correlation and significance values between learning progress and duration graduate to get employed. The PLO data from all semesters were segmented into four-time segments: 1st SEM, MID SEM, Pre-LI and LI. The slope value of linear model from time series analysis of four-time segments is used as a value to determine the performance of student learning progress. 47 responses (22% response rate) from 216 graduates who completed their study from Faculty of Computing, Universiti Malaysia Pahang in 2018 has been received as a case study. We found that learning progress from PLO 3 and PLO 6 which are 'Social Skills and Responsibilities' and 'Problem Solving and Scientific Skills' respectively, show significant values on the duration to get employed. This study highlights student learning progress is potential to be used as a predictor for graduate employability performance.