Thematic Analysis of the Pathologies of the Online Evaluation System for the Academic Progress of High School Students from Experts’ Perspectives
Keywords:
educational assessment, artificial intelligence, digital pedagogy , thematic analysis, high school education, academic progress , Online evaluationAbstract
This study aimed to identify and thematically analyze the pathologies of the online evaluation system for the academic progress of high school students from the perspectives of educational experts. This qualitative research employed a phenomenological approach. The study population included secondary school teachers and educational specialists in Kurdistan Province during the 2022–2023 academic year. Using purposive theoretical sampling, 15 experts experienced in online assessment practices were selected. Data were collected through semi-structured interviews and analyzed via open, axial, and selective coding using NVivo software. Credibility was enhanced through participant validation, analytical triangulation, and peer debriefing to ensure interpretive reliability. Thematic analysis revealed three overarching categories of online evaluation pathologies: instructional and infrastructural dysfunctions, human and managerial challenges, and ethical and psychological complications. Eight subthemes were identified, including lack of formative feedback, infrastructural deficiencies, limited digital competence among teachers, academic dishonesty among students, parental interference, psychological stress, decreased human interaction, and lack of digital culture. The findings indicate that inadequate feedback, weak digital literacy, and unstable technological infrastructure are the primary factors undermining the effectiveness and fairness of online evaluation systems in secondary education. The study concludes that despite the technological potential of online assessment, it remains constrained by structural, pedagogical, and ethical deficiencies. Enhancing teachers’ digital competence, improving infrastructure, and establishing clear ethical frameworks are essential steps toward strengthening the validity, reliability, and equity of online evaluation practices.
Downloads
References
Ahmad, N., Noorani, Z., & Sewani, R. (2025). Exploring Feedback and Assessment Practices: Perspectives From Prospective Teachers. CRSSS, 3(1), 953-966. https://doi.org/10.59075/c39z2h90
Anwar, R. N. (2024). Pendampingan Pembuatan Asesmen Sumatif Sebagai Laporan Hasil Belajar Peserta Didik Pada Komunitas Belajar Guru PAUD. Profetik J. Pengabdi. Masy., 2(2), 95-104. https://doi.org/10.62490/profetik.v2i02.670
Bakar, S. A. (2025). The Impact of Online Submission Systems on Teaching Practice in Digital Education Environments: A Case Study of Open University Malaysia. Muallim Journal of Social Science and Humanities, 231-239. https://doi.org/10.33306/mjssh/345
Beerepoot, M. T. P. (2023). Formative and Summative Automated Assessment With Multiple-Choice Question Banks. Journal of Chemical Education, 100(8), 2947-2955. https://doi.org/10.1021/acs.jchemed.3c00120
Begimbetova, G. A., Kassymova, G. K., & Abduldayev, Y. (2023). Criteria-Based Assessment Model in the Education System of Kazakhstan. Iasaýı Ýnıversıtetіnіń Habarshysy, 127(1), 276-287. https://doi.org/10.47526/2023-1/2664-0686.23
Brian, R., Murillo, A., Gomes, C., & Alseidi, A. (2024). Artificial Intelligence and Robotic Surgical Education. Global Surgical Education - Journal of the Association for Surgical Education, 3(1). https://doi.org/10.1007/s44186-024-00262-5
Dockens, A. L., & Shelton, K. (2025). AI for Formative and Summative Assessment. 353-386. https://doi.org/10.4018/979-8-3373-5102-5.ch013
Dubey, P., Crevar, A. R., & Rischard, M. K. (2025). Relevance of Artificial Intelligence in Assessment. 477-500. https://doi.org/10.4018/979-8-3373-2397-8.ch016
Gupta, S., & Srivastava, T. (2024). Assessment in Undergraduate Competency-Based Medical Education: A Systematic Review. Cureus. https://doi.org/10.7759/cureus.58073
Hurskaya, V., Mykhaylenko, S., Kartashova, Z., Kushevska, N., & Zaverukha, Y. (2024). Assessment and Evaluation Methods for 21st Century Education: Measuring What Matters. Futurity Education, 4(4), 4-17. https://doi.org/10.57125/fed.2024.12.25.01
Kumar, R., Balla, R., Chahal, D., Yadav, R., Manzer, S. M., Kadaiyan, R., & Singh, G. (2025). Creating Digital Environment Using Data Analytics and AI for Evaluation: A Conceptual Study. Int. J. Environ. Sci., 3435-3444. https://doi.org/10.64252/9dfkj869
Mahmudah, S., & Anggunsari, P. (2023). Oral Corrective Feedback as a Formative Assessment in Teaching Speaking Skill. Journal of Research on English and Language Learning (J-Reall), 4(1), 18-25. https://doi.org/10.33474/j-reall.v4i1.19432
Marzuki, A. G. (2023). Principles, Functions, Types, and Implementation of Assessments in Schools. https://doi.org/10.31219/osf.io/ejrk2
Muhanguzi, J., Tukur, M., Aja, L., Umar, S., Nakafu, G., Mugerwa, S., Sewalu, M. B. D., & Shafiu, A. (2025). Qualitative Study on Formative and Summative Assessment Strategies for Effective Learning Outcome Among Pharmacy Students: A Systematic Review. Foefujs, 5(2), 24-28. https://doi.org/10.64348/zije.20255
Nurhasan, U., Rahmanto, A. N., Mubarok, F. U., & Sabita, A. R. (2024). The Implementation of Automated Assessment Platform in Asynchronous Learning for Independent Learning of Game Programming User Interface for Students at Telkom Malang Vocational High School. Abdi Dosen Jurnal Pengabdian Pada Masyarakat, 8(1), 167-177. https://doi.org/10.32832/abdidos.v8i1.2165
Paiva, J. C., Figueira, Á., & Leal, J. P. (2023). Bibliometric Analysis of Automated Assessment in Programming Education: A Deeper Insight Into Feedback. Electronics, 12(10), 2254. https://doi.org/10.3390/electronics12102254
Paiva, J. C., Leal, J. P., & Figueira, Á. (2025). Incremental Repair Feedback on Automated Assessment of Programming Assignments. Electronics, 14(4), 819. https://doi.org/10.3390/electronics14040819
Peña, H.-K. D., & Galigao, R. (2025). Assessment for Learning: Balancing Traditional and Innovative Evaluation Approaches in Education. Pijhss. https://doi.org/10.69651/pijhss0402165
Riese, E., & Bälter, O. (2022). A Qualitative Study of Experienced Course Coordinators’ Perspectives on Assessment in Introductory Programming Courses for Non-Cs Majors. Acm Transactions on Computing Education, 22(4), 1-29. https://doi.org/10.1145/3517134
Tariq, M. U. (2025). AI-Powered Assessment Platforms. 117-146. https://doi.org/10.4018/979-8-3373-2130-1.ch004
Thakre, N. K., Ramesh, P., Thakur, M., & Sumitra, S. (2024). Using Innovative Technologies as E-Assessment Tool in Higher Educational Institutions. Nanotechnology Perceptions, 1262-1269. https://doi.org/10.62441/nano-ntp.vi.1757
Tonbuloğlu, B. (2024). Online Assessment in K12 Computer Science Education. 223-262. https://doi.org/10.4018/979-8-3693-4542-9.ch009
Tu, B., Nguyễn, M. T., & Nam, L. H. (2025). Development of Automatic Assessment System Based on Machine Learning for Student Learning Evaluation. Al-Hijr Journal of Adulearn World, 3(4), 483-493. https://doi.org/10.55849/alhijr.v3i4.856
Wijk, E. V. v., Blankenstein, F. M. v., Donkers, J., Janse, R. J., Bustraan, J., Adelmeijer, L. G. M., Dubois, E. A., Dekker, F. W., & Langers, A. M. J. (2024). Does ‘Summative’ Count? The Influence of the Awarding of Study Credits on Feedback Use and Test-Taking Motivation in Medical Progress Testing. Advances in Health Sciences Education, 29(5), 1665-1688. https://doi.org/10.1007/s10459-024-10324-4
Yang, Y. (2024). Formative Assessment: A Significant Facilitator of Student Learning. Science Insights Education Frontiers, 20(2), 3219-3221. https://doi.org/10.15354/sief.24.co267
Downloads
Published
Submitted
Revised
Accepted
Issue
Section
License
Copyright (c) 2025 غلامعلی عباسی (نویسنده); مجید محمدی (نویسنده مسئول); رفیق حسنی (نویسنده)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.