Faculty Perceptions of their Assessment Practices in the Age of AI
A Qualitative Case Study
DOI:
https://doi.org/10.5281/zenodo.18248185Abstract
Abstract Views: 312
Assessment practices are evolving from traditional methods to more personalized approaches due to the widespread growth of Artificial Intelligence (AI) tools. This change encourages educators to redesign assessments that emphasize real-world applications over memorization. The current qualitative case study explored faculty awareness of new assessment practices in the age of AI at one university in the northern region of Pakistan. Semi-structured interviews were used for data collection from faculty members, purposively selected from four faculties (Arts & Humanities, Biological & Health Sciences, Law & Social Sciences, and Natural and Computational Sciences) of the university. From thematic analysis of the data, two main themes emerged, i.e. evaluating students’ learning beyond AI and innovative assessment practices to assess authentic learning. The main findings depicted that teachers used project-based activities, classroom-based tasks, and assessed students through standard criteria. Moreover, the findings focused on assessment tasks exploring critical thinking, problem-solving, and creativity, rather than mere learning and rote memorization. The study suggests that universities may promote authentic assessments by determining criteria and ensuring the ethical use of AI.
Keywords:
Age of AI, Assessment practices, Faculty perceptions, Qualitative case studyReferences
AlAfnan, M. A. (2024). Taxonomy of educational objectives: Teaching, learning, and assessing in the information and artificial intelligence era. Journal of Curriculum and Teaching, 13(4), 173-191. https://doi.org/10.5430/jct.v13n4p173
Ali, M. Y., Bin Naeem, S., Bhatti, R., & Richardson, J. (2025). Factors affecting intention of academic librarians in Pakistan universities to use AI tools: an extension of the UTAUT model. Global Knowledge, Memory and Communication. https://doi.org/10.1108/GKMC-08-2024-0560
Almas, R., Fazal, S., & Nazir, F. (2024). Teachers’ perceptions about authentic assessment in higher education: A university case study. CARC Research in Social Sciences, 3(2), 241–249. https://doi.org/10.58329/criss.v3i2.136
Almatrafi, O., & Johri, A. (2025). Leveraging generative AI for course learning outcome categorization using Bloom's taxonomy. Computers and Education: Artificial Intelligence, 8, 100404. https://doi.org/10.1016/j.caeai.2025.100404
Baranovskaya, T., & Shaforostova, V. (2017). Assessment and Evaluation Techniques. Journal of Language and Education, 3(2), 30-38. https://doi.org/10.17323/2411-7390-2017-3-2-30-38
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Cai, L., Msafiri, M. M., & Kangwa, D. (2025). Exploring the impact of integrating AI tools in higher education using the Zone of Proximal Development. Education and Information Technologies, 30(6), 7191-7264. https://doi.org/10.1007/s10639-024-13112-0
Coombe, C., Vafadar, H., & Mohebbi, H. (2020). Language assessment literacy: What do we need to learn, unlearn, and relearn? Language Testing in Asia, 10(3). https://doi.org/10.1186/s40468-020-00101-6
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications.
DeJonckheere, M., & Vaughn, L. M. (2019). Semi-structured interviewing in primary care research: A balance of relationship and rigour. Family Medicine and Community Health, 7(2), e000057. https://doi.org/10.1136/fmch-2018-000057
DeLuca, C., Holden, M., & Rickey, N. (2025). From challenge to innovation: A grassroots study of teachers’ classroom assessment innovations. British Educational Research Journal, 51(1), 93-114. https://doi.org/10.1002/berj.4065
Fischer, I., Mirbahai, L., Beer, L., Buxton, D., Grierson, S., Griffin, L., & Gupta, N. (2023). Transforming higher education how we can harness AI in teaching and assessments and uphold academic rigour and integrity. University of Warwick: Coventry, UK.
Fitria, T. N. (2021). Artificial intelligence (AI) in education: Using AI tools for teaching and learning process. Prosiding Seminar Nasional & Call for Paper STIE AAS, 4(1), 134–147.
Frieary, A. (2025). The integration of Artificial Intelligence into curriculum design in Higher Education (Doctoral dissertation).
Hao, J., von Davier, A. A., Yaneva, V., Lottridge, S., von Davier, M., & Harris, D. J. (2024). Transforming assessment: The impacts and implications of large language models and generative AI. Educational Measurement: Issues and Practice, 43(2), 16-29. https://doi.org/10.1111/emip.12602
Hassan, T. (2025, November 25). The future of universities: Reinventing higher education by 2035. The Friday Times. https://www.thefridaytimes.com/25-Nov-2025/future-universities-reinventing-higher-education-2035
Khan, Z., Jan, R., Hussain, M., Shahab, M., & Ullah, N. (2025). Integration of artificial intelligence tools in academic libraries of Khyber Pakhtunkhwa: Current trends and future prospects. The Critical Review of Social Sciences Studies, 3(3), 907-922. https://doi.org/10.59075/6rf4rb49
Kurniawan, D., Masitoh, S., Bachri, B. S., Kamila, V. Z., Subastian, E., & Wahyuningsih, T. (2025). Integrating AI in digital project-based blended learning to enhance critical thinking and problem-solving skills. Multidisciplinary Science Journal, 7(12), 2025552. https://doi.org/10.31893/multiscience.2025552
Matheis, P., & John, J. J. (2024). Reframing assessments: Designing authentic assessments in the age of generative AI. In Academic Integrity in the Age of Artificial Intelligence (pp. 139-161). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-0240-8.ch008
Md Din, A. G. B., Bin Zabidin, M. A. R., Moawad Ali Tahawi, A. R., Md Din, O. B., & Aawi, F. (2023). Educational assessment: Its types and outcomes: A bibliometric analytical study. International Journal of Academic Research in Business and Social Sciences, 13(11), 1599–1618. https://doi.org/10.6007/IJARBSS/v13-i11/19516
Miles, M. B. (1994). Qualitative data analysis: An expanded sourcebook. Thousand Oaks.
Mislevy, R. J., Behrens, J. T., Dicerbo, K. E., & Levy, R. (2012). Design and discovery in educational assessment: Evidence-centered design, psychometrics, and educational data mining. Journal of Educational Data Mining, 4(1), 11-48. https://doi.org/10.5281/zenodo.3554641
Naqvi, A. (2020). Artificial intelligence for audit, forensic accounting, and valuation: A strategic perspective. Wiley. https://doi.org/10.1002/9781119601906
Naseer, M. A., Saeed, S., Afzal, A., Ali, S., & Malik, M. G. R. (2025). Navigating the integration of artificial intelligence in the medical education curriculum: a mixed-methods study exploring the perspectives of medical students and faculty in Pakistan. BMC Medical Education, 25(1), 273. https://doi.org/10.1186/s12909-024-06552-2
Norova, M. B., & Haydarali, A. (2021, March). Advantages and disadvantages of traditional and alternative ways of assessment. In Topical Issues of Teaching Foreign Languages: Republican Scientific-Practical Online Conference (pp. 195–200).
Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. Eurasia Journal of Mathematics, Science and Technology Education, 19(8), em2307. https://doi.org/10.29333/ejmste/13428
Paie, D. H. (2025). Assessing the use of artificial intelligence in the classroom: Teachers perspective. Journal of Education and Academic Settings, 2(1), 1–18. https://doi.org/10.62596/c3b8zj70
Patton, M. Q. (1990). Qualitative evaluation and research methods. Sage Publications.
Rubab, I., & Imran, A. (2023). A comparative analysis of traditional and online assessments: Perceptions and performance of undergraduate students. Pakistan Journal of Humanities and Social Sciences, 11(2), 1352–1358. https://doi.org/10.52131/pjhss.2023.1102.0439
Saxena, P., Saxena, V., Pandey, A., Flato, U., & Shukla, K. (2023). Multiple aspects of artificial intelligence. Book Saga Publications.
Shepard, L. A., Penuel, W. R., & Pellegrino, J. W. (2018). Using learning and motivation theories to coherently link formative assessment, grading practices, and large‐scale assessment. Educational Measurement: Issues and Practice, 37(1), 21-34. https://doi.org/10.1111/emip.12189
Simelane-Mnisi, S. (2025). Generative AI use in assessments in higher education. In EDULEARN25 proceedings (pp. 9755-9765). IATED. https://doi.org/10.21125/edulearn.2025.2534
Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., Lodge, J. M., Milligan, S., ... & Gašević, D. (2022). Assessment in the age of artificial intelligence. Computers and Education: Artificial Intelligence, 3, 100075. https://doi.org/10.1016/j.caeai.2022.100075
Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., Lodge, J. M., Milligan, S., Selwyn, N., & Gašević, D. (2022). Assessment in the age of artificial intelligence. Computers and Education Artificial Intelligence, 3, 100075. https://doi.org/10.1016/j.caeai.2022.100075
Vinothkumar, J., & Karunamurthy, A. (2023). Recent advancements in artificial intelligence technology: trends and implications. Quing: International Journal of Multidisciplinary Scientific Research and Development, 2(1), 1-11. https://doi.org/10.54368/qijmsrd.2.1.0003
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Zhao, J., Chapman, E., & Sabet, P. G. (2024). Generative AI and educational assessments: A systematic review. Education Research and Perspectives, 51, 124-155.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Bulletin of Multidisciplinary Studies
This work is licensed under a Creative Commons Attribution 4.0 International License.
