A Performance Indicator Model for the Assessment of Program Outcomes

Öz

Outcome-Based Education (OBE) evaluates learning success by measuring the knowledge, skills, and competencies students are expected to achieve upon graduation. However, common program outcome (PO) assessment methods rely on course-level weighted averages, which limit detailed analysis and obscure the contribution of individual assessment components. To address this limitation, this study proposes a Performance Indicator Model (PIM) that measures program outcome attainment using question-level assessment data. The model incorporates curriculum-based weighting factors—such as course ECTS credits, assessment contribution ratios, and learning outcome–program outcome (LO–PO) relationships—within a hierarchical mathematical framework. This approach enables normalized aggregation of question-level performance at the program outcome level and produces scale-independent, PO-specific indicators. The effectiveness of the proposed model is demonstrated through an application scenario based on an undergraduate software engineering program. The results highlight substantial differences between PO-based indicators and traditional weighted averages, confirming the model’s potential to support accreditation-aligned, data-driven quality assurance and continuous improvement processes in diverse OBE contexts.

Anahtar Kelimeler

• Evaluation methodologies
• Program outcomes
• Performance indicator
• Micro-level assessment
• Outcome-based education

Program Çıktılarının Değerlendirilmesi İçin Bir Performans Göstergesi Modeli

Öz

Çıktı Temelli Eğitim (Outcome-Based Education – OBE), öğrenme başarısını öğrencilerin mezuniyet sırasında sahip olmaları beklenen bilgi, beceri ve yetkinlikleri ölçerek değerlendirir. Ancak yaygın program çıktısı (Program Outcome – PO) değerlendirme yöntemleri, ders düzeyindeki ağırlıklı ortalamalara dayanmaktadır. Bu durum ayrıntılı analiz yapılmasını sınırlandırmakta ve bireysel değerlendirme bileşenlerinin katkısını görünmez hale getirmektedir. Bu sınırlamayı gidermek amacıyla, bu çalışma program çıktısı kazanımını soru düzeyindeki değerlendirme verilerini kullanarak ölçen bir Performans Göstergesi Modeli (Performance Indicator Model – PIM) önermektedir. Model; derslerin AKTS kredileri, değerlendirme katkı oranları ve öğrenme çıktısı–program çıktısı (LO–PO) ilişkileri gibi müfredat temelli ağırlıklandırma faktörlerini hiyerarşik bir matematiksel yapı içinde bütünleştirir. Bu yaklaşım, soru düzeyindeki performans verilerinin program çıktısı düzeyinde normalize edilerek birleştirilmesini mümkün kılmakta ve ölçekten bağımsız, program çıktısına özgü göstergeler üretmektedir. Önerilen modelin etkinliği, lisans düzeyinde bir yazılım mühendisliği programına dayalı uygulama senaryosu üzerinden gösterilmiştir. Elde edilen sonuçlar, PO tabanlı göstergeler ile geleneksel ağırlıklı ortalamalar arasında önemli farklılıklar olduğunu ortaya koyarak modelin akreditasyon odaklı, veri temelli kalite güvencesi ve sürekli iyileştirme süreçlerini destekleme potansiyelini doğrulamaktadır.

Anahtar Kelimeler

• Değerlendirme yöntemleri
• Program çıktıları
• Performans göstergesi
• Mikro düzey değerlendirme
• Çıktı Temelli Eğitim

Kaynakça

1. [1]. N. S. Bohra, A. Johri, and M. Wasiq, “Systematic approach of measuring program outcomes of management postgraduate program,” Frontiers in Education 9 (2024), https://doi.org/10.3389/feduc.2024.1404946.
2. [2]. M. F. Caro, E. P. Flórez, and I. C. Muñoz, “A formal model for assessing the learning outcomes of academic programs,” Evaluation and Program Planning 114 (2026), 102644, https://doi.org/10.1016/j.evalprogplan.2025.102644.
3. [3]. M. K. Chan, C. C. Wang, and A. A. B. Arbai, “Development of dynamic OBE model to quantify student performance,” Computer Applications in Engineering Education 30 (5) (2022), 1293–1306, https://doi.org/10.1002/cae.22520.
4. [4]. D. Datta, “A rubric-based mathematical model for evaluation of direct PO attainment through CO attainment and CO–PO articulation matrix for OBE system,” Research Square (2022), https://doi.org/10.21203/rs.3.rs-2124169/v1.
5. [5]. M. Derouich, “Ensuring outcome-based curriculum coherence through systematic CLO–PLO alignment and feedback loops,” Discover Education 4 (2025), Article 486, https://doi.org/10.1007/s44217-025-00915-7.
6. [6]. R. Divekar, K. Chopra, P. Dange, and S. Mehendale, Securing the Future through Sustainability, Health, Education, and Technology, Routledge, 2024, https://doi.org/10.1201/9781003587200.
7. [7]. L. Gungat, H. Asrah, N. Bolong, and J. Makinda, “Comparison study on the assessment approach of course outcomes,” in Proceedings of the 3rd International Congress on Engineering Education (ICEED 2011), IEEE, 2011, pp. 80–84, https://doi.org/10.1109/iceed.2011.6235365.
8. [8]. H. M. Harmanani, “An outcome-based assessment process for accrediting computing programmes,” European Journal of Engineering Education 42 (6) (2016), 844–859, https://doi.org/10.1080/03043797.2016.1226781.

9. [9]. W. Hussain and W. Spady, “Specific, generic performance indicators and their rubrics for the comprehensive measurement of ABET student outcomes,” in Proceedings of the 2017 ASEE Annual Conference & Exposition, ASEE Conferences, 2017, https://doi.org/10.18260/1-2--28837.
10. [10]. W. Hussain, W. G. Spady, S. Z. Khan, B. A. Khawaja, T. Naqash, and L. Conner, “Impact evaluations of engineering programs using ABET student outcomes,” IEEE Access 9 (2021), 46166–46190, https://doi.org/10.1109/ACCESS.2021.3066921.
11. [11]. W. Hussain, F. Mak, and M. Addas, “Engineering program evaluations based on automated measurement of performance indicators data classified into cognitive, affective, and psychomotor learning domains of the revised Bloom’s taxonomy,” in Proceedings of the 2016 ASEE Annual Conference & Exposition, ASEE Conferences, 2016, https://doi.org/10.18260/p.27299.
12. [12]. A. Ibrahim, M. R. Mohamad Nor, H. Ahmad, and M. F. P. Mohamed Latiff, “Reliability of program outcome attainment evaluation based on cumulative model and culminating model analysis,” Jurnal Kejuruteraan 37 (1) (2025), 527–540, https://doi.org/10.17576/jkukm-2025-37(1)-39.
13. [13]. M. Keshavarz, “Measuring course learning outcomes,” Journal of Learning Design 4 (4) (2011), https://doi.org/10.5204/jld.v4i4.84.
14. [14]. Y. K. Lee, A. A. A. Rahim, N. M. Thamrin, A. J. Nor’aini, N. Mohd Asrol Alias, and N. Omar, “An outcome based approach to delivery and assessment of a course in control system design,” in Proceedings of the 2009 International Conference on Engineering Education (ICEED), IEEE, 2009, pp. 167–172, https://doi.org/10.1109/ICEED.2009.5490592.
15. [15]. R. Mahajan and D. Bansal, “Designing performance metrics and rubrics to assess student outcome attainment in engineering project design course,” Journal of Education 203 (2) (2021), 459–467, https://doi.org/10.1177/00220574211032587.
16. [16]. Q. A. Memon and A. Harb, “Developing electrical engineering education program assessment process at UAE University,” Australasian Journal of Engineering Education 15 (3) (2009), 155–164, https://doi.org/10.1080/22054952.2009.11464033.
17. [17]. K. Mohiuddin, Q. N. Naveed, O. A. Nasr, and N. Tairan, “Captivating strategies and cultivating quality standards for obtaining successful ABET accreditation and academic excellence: analyzing the contributing factors by implementing fuzzy AHP,” SAGE Open 15 (4) (2025), https://doi.org/10.1177/21582440251368954.
18. [18]. A. A. Mulla, H. S. Jadhav, and A. P. Shah, “A case study on course outcome and program outcome mapping levels based on competency and performance indicators,” Journal of Engineering Education Transformations 36 (S2) (2023), 326–331, https://doi.org/10.16920/jeet/2023/v36is2/23048.
19. [19]. D. Pradhan, “Effectiveness of outcome based education (OBE) toward empowering the students performance in an engineering course,” Journal of Advances in Education and Philosophy 5 (2) (2021), 58–65, https://doi.org/10.36348/jaep.2021.v05i02.003.
20. [20]. K. Premalatha, “Course and program outcomes assessment methods in outcome-based education: a review,” Journal of Education 199 (3) (2019), 111–127, https://doi.org/10.1177/0022057419854351.
21. [21]. H. M. Shaikh and A. Kumar, “Implementing an application for attainment calculation of program outcomes and course outcomes for courses of university-affiliated engineering programs,” International Journal of Engineering and Advanced Technology 11 (4) (2022), https://doi.org/10.35940/ijeat.D3409.0411422.
22. [22]. S. K. Sharma, S. V. Tirumalai, and A. A. Alhamdan, “Mathematical models for evaluating programs and course learning outcomes in higher education,” International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies 10 (3) (2019), 283–297, https://doi.org/10.14456/ITJEMAST.2019.28.
23. [23]. H. Zainol Abidin, N. Omar, H. Hashim, M. F. Abdul Latip, M. Murtadha Othman, S. Mohamed, N. Fazlina Naim, and Z. Mat Yasin, “Outcome based education performance evaluation on electrical engineering laboratory module,” in Proceedings of the 2009 International Conference on Engineering Education (ICEED), IEEE, 2009, pp. 153–158, https://doi.org/10.1109/ICEED.2009.5490593.
24. [24]. E. Avuçlu, S. Özdemir, “An Interactive and Advanced Online Exam Platform For Both Teachers and Students,” International Scientific and Vocational Studies Journal, 9 (1) (2024), 33-41, https://doi.org/10.47897/bilmes.1613874.