A Six-Cycle Evaluation of Programme Quality Indicators in Outcome-Based Education
Authors
Faculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia (Malaysia)
Faculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia (Malaysia)
Faculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia (Malaysia)
Nurzulaifa Shaheera Erne Mohd Yasim
Faculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia (Malaysia)
Faculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia (Malaysia)
Faculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.100700678
Subject Category: Criminology
Volume/Issue: 10/7 | Page No: 10052-10057
Publication Timeline
Submitted: 2026-07-28
Accepted: 2026-08-01
Published: 2026-08-10
Abstract
Institutional quality assurance systems generate substantial programme-level data, yet these data are often used primarily for periodic reporting rather than longitudinal programme evaluation. This study examined three routinely collected programme quality indicators across six consecutive academic cycles in an Outcome-Based Education programme at a Malaysian public university. A retrospective descriptive longitudinal case-study design was used. Course-level records were extracted from Closing the Loop Continuous Quality Improvement reports covering March 2022 to October 2024. The indicators were Course Grade Rating, Entrance-Exit Survey, and Student Feedback Online. Courses were grouped by Part, defined as the semester of study within the programme. Means were calculated across valid course ratings within each Part, while cycle-level means and population standard deviations were calculated across the available Part means. All three indicators were reported on a five-point institutional performance scale. Course Grade Rating declined from 2.71 in March 2022 to 2.41 in March 2023 and ended at 2.64 in October 2024. Entrance-Exit Survey means were 3.36 in the first three cycles, peaked at 3.55 in October 2023, and ended at 3.30. Student Feedback Online increased from 3.23 to 3.61, with its highest mean of 3.91 recorded in March 2024. The non-parallel trajectories show why programme quality should not be reduced to a single indicator. Routine quality assurance records can support longitudinal programme monitoring, although variation in Part composition and the use of aggregated ratings limit causal interpretation.
Keywords
Outcome-Based Education; programme evaluation; course grade rating; quality assurance; continuous quality improvement
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References
1. Armatas, C., Kwong, T., Chun, C., Spratt, C., Chan, D., & Kwan, J. (2022). Learning analytics for programme review: Evidence, analysis, and action to improve student learning outcomes. Technology, Knowledge and Learning, 27(2), 461-478. https://doi.org/10.1007/s10758-021-09559-6 [Google Scholar] [Crossref]
2. Beerkens, M. (2018). Evidence-based policy and higher education quality assurance: Progress, pitfalls and promise. European Journal of Higher Education, 8(3), 272-287. https://doi.org/10.1080/21568235.2018.1475248 [Google Scholar] [Crossref]
3. Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education, 32(3), 347-364. https://doi.org/10.1007/BF00138871 [Google Scholar] [Crossref]
4. Boswell, M., Marshall, S., & Thornton, K. (2024). Quality assurance dysfunctions. Quality in Higher Education, 30(3), 486-507. https://doi.org/10.1080/13538322.2024.2339996 [Google Scholar] [Crossref]
5. Ibrahim, A., Mohamad Nor, M. R., Ahmad, H., & Mohamed Latiff, M. F. P. (2025). Reliability of program outcome attainment evaluation based on cumulative model and culminating model analysis. Jurnal Kejuruteraan, 37(1), 527-540. https://doi.org/10.17576/jkukm-2025-37(1)-39 [Google Scholar] [Crossref]
6. Liew, C. P., Lim, L. L., Chor, W. T., Yu, L. J., & Tan, J. (2022). Evaluation practices of learning outcomes that promote culture of continual quality improvement. AIP Conference Proceedings, 2433, 020022. https://doi.org/10.1063/5.0095086 [Google Scholar] [Crossref]
7. Liew, C. P., Puteh, M., Lim, L. L., Yu, L. J., Tan, J., Chor, W. T., & Tan, K. G. (2021). Evaluation of engineering students' learning outcomes: Creating a culture of continuous quality improvement. International Journal of Emerging Technologies in Learning, 16(15), 62-77. https://doi.org/10.3991/ijet.v16i15.23763 [Google Scholar] [Crossref]
8. Naveed Bin Rais, R., Rashid, M., Zakria, M., Hussain, S., Qadir, J., & Imran, M. A. (2021). Employing industrial quality management systems for quality assurance in outcome-based engineering education: A review. Education Sciences, 11(2), Article 45. https://doi.org/10.3390/educsci11020045 [Google Scholar] [Crossref]
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