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This article discusses new methods for the analyses of program outcome measurements of an engineering undergraduate program, enabling a robust effort to continually improve the quality of the program. The analyses were conducted on an undergraduate engineering program at University Malaysia Sarawak (UNIMAS), based on program outcomeachievements of 80 students undertaking selected courses from 2015–2019. Three techniques were utilized: i.e., graphical visualization of data using boxplots, association analysis using Spearman’s rank correlation coefficient, and consistency analysis using Cronbach’s alpha. Using these techniques, the authors identified trendsamong the courses measuring the same program outcome. Boxplots are very effective in gaining an overview of the achievements of courses measuring the same program outcome, and in highlighting outliers and anomaliesin the data. It was also found that the Cronbach’s alpha result is coherent with that of the rank correlation coefficient. The techniques reported in this study can be applied to enhance data analysis for quality improvement of any academic program focusing on outcome-based education. Therefore, the study presented in this paper is both relevant and valuable to engineering programs working towards obtaining international accreditation. |
