Unveiling the Dual Nature of AI in Grading: A Systematic Review of Benefits and Mitigation Strategies for Algorithmic Bias
DOI:
https://doi.org/10.58524/oler.v5i1.695Keywords:
AI in Education, Artificial Intelligence, Automated Assessment, Bibliometric, Systematic Literature ReviewAbstract
The use of Artificial Intelligence (AI) in educational evaluation optimizes learning outcomes. This research seeks to address the advantages and difficulties of implementing AI within academic evaluation frameworks with particular emphasis on the algorithmic bias problem and its implications for fairness in education. The absence of a thorough grasp of algorithmic bias, particularly how it can be utilized as a weapon against equitable education, reveals an important gap. We conduct a Systematic Literature Review (SLR) and bibliometric analysis on 121 articles sourced from Scopus published between 2021 to 2025 to trace the trends and examine the impacts and biases of AI on grading systems. The data demonstrates a significant increase in publications beginning 2018, concentrating on topics such as educational applications of AI, automated grading systems, and machine learning. The findings further indicate that though AI improves efficiency and consistency of the evaluations, it heightens the chances of biased outcomes because of non-diverse training data, prejudiced developers, and socio-cultural frameworks that could worsen the situation for already marginalized learners. In summary, this study highlights the critical gaps in bias mitigation strategies arising from the lack of ethical design frameworks, antecedent-free algorithms, and educator prep courses aimed at combating bias. These outcomes serve as benchmarks for the creation of more reliable and comprehensive AI systems for assessments and shift subsequent investigations to focus validation on different cultures and the incorporation of just AI design paradigmsReferences
Aghaziarati, A., Nejatifar, S., & Abedi, A. (2023). Artificial intelligence in education: Investigating teacher attitudes. AI and Tech in Behavioral and Social Sciences, 1(1), 35–42. https://doi.org/10.61838/kman.aitech.1.1.6
Anuyahong, B., Rattanapong, C., & Patcha, I. (2023). Analyzing the impact of artificial intelligence in personalized learning and adaptive assessment in higher education. International Journal of Research and Scientific Innovation, 10(4), 88–93. https://doi.org/10.51244/IJRSI.2023.10412
Armoogum, S., & Zakaria, M. Z. (2024). Deep Learning innovations in fingerprint recognition : A comparative study of model efficiencies. International Journal of Advances in Artificial Intelligence and Machine Learning Vol, 1(1), 28–35. https://doi.org/10.58723/ijaaiml.v1i1.294
Baker, C., & Fairclough, S. H. (2021). Adaptive virtual reality. Current Research in Neuroadaptive Technology, 1(1),159–176. https://doi.org/10.1016/B978-0-12-821413-8.00014-2
Branch, R. M. (2009). Instructional design-the ADDIE approach. Springer. https://doi.org/10.1007/978-0-387-09506-6
Cavique, L. (2024). Implications of causality in artificial intelligence. Frontiers in Artificial Intelligence, 7(August), 1–5. https://doi.org/10.3389/frai.2024.1439702
Coghlan, S., Miller, T., & Paterson, J. (2021). Good proctor or “big brother”? Ethics of online exam supervision technologies. Philosophy and Technology, 34(4), 1581–1606. https://doi.org/10.1007/s13347-021-00476-1
Cohen, A. K., & Snyder, R. E. (2024). Community-based participatory research for epidemiology, health equity, and community goals: Insights from Brazil, France, and USA. Community Health Equity Research and Policy. 45(4):385-393. https://doi.org/10.1177/2752535X241262857
Crompton, H., & Burke, D. (2022). Artificial intelligence in K-12 education. SN Social Sciences, 2(7), 2(3), 431-440. https://doi.org/10.1007/s43545-022-00425-5
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education : The state of the field. International Journal of Educational Technology in Higher Education, 20(22), 1–22. https://doi.org/10.1186/s41239-023-00392-8
Damaševičius, R. (2024). Commentary: ChatGPT-supported student assessment – can we rely on it? Journal of Research in Innovative Teaching and Learning, 17(2), 414–416. https://doi.org/10.1108/JRIT-09-2024-195
Emilio, F. (2024). FAIRNESS and bias in artificial intelligence : A brief survey of sources , impacts , and mitigation strategies. Sci, 6(1), 1–18. https://doi.org/10.3390/sci6010003
Gándara, D., Anahideh, H., Ison, M. P., & Picchiarini, L. (2024). Inside the black box: Detecting and mitigating algorithmic bias across racialized groups in college student-success prediction. AERA Open, 10(1). https://doi.org/10.1177/23328584241258741
Herawati, A. A., Yusuf, S., Ilfiandra, I., Taufik, A., & Ya Habibi, A. S. (2024). Exploring the role of artificial intelligence in education, students preferences and perceptions. Al-Ishlah: Jurnal Pendidikan, 16(2), 1029–1040. https://doi.org/10.35445/alishlah.v16i2.4784
Hosford, K., Aqil, N., Windle, J., Gundur, R. V., & Allum, F. (2022). Who researches organised crime? A review of organised crime authorship trends (2004–2019). Trends in Organized Crime, 25(3), 249–271. https://doi.org/10.1007/s12117-021-09437-8
Ifenthaler, D., Majumdar, R., Gorissen, P., Judge, M., Mishra, S., Raffaghelli, J., & Shimada, A. (2024). Artificial intelligence in education: Implications for policymakers, researchers, and practitioners. Technology, Knowledge and Learning, 29(4), 1693–1710. https://doi.org/10.1007/s10758-024-09747-0
James, K. E., Tuidraki, H. D., & Tanzil, S. A. (2022). Postcolonial control of Fiji soccer and the return of subjugated knowledges: From the 1970s to the 2010s. Frontiers in Sports and Active Living, 4(1), 1-5. https://doi.org/10.3389/fspor.2022.1005733
Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability (Switzerland), 15(16), 1–27. https://doi.org/10.3390/su151612451
Kara Aydemir, A. G., & Can, G. (2019). Educational technology research trends in Turkey from a critical perspective: An analysis of postgraduate theses. British Journal of Educational Technology, 50(3), 1087–1103. https://doi.org/10.1111/bjet.12780
Kasim, S., Zakaria, M. Z., & Efrizoni, L. (2025). AI and the optimization of product placement : Enhancing sales through strategic positioning. International Journal of Advances in Artificial Intelligence and Machine Learning Vol, 2(1), 18–26. https://doi.org/10.58723/ijaaiml.v2i1.381
Kharbach, M. (2020). Understanding the ideological construction of the Gulf crisis in Arab media discourse: A critical discourse analytic study of the headlines of Al Arabiya English and Al Jazeera English. Discourse and Communication, 14(5), 447–465. https://doi.org/10.1177/1750481320917576
Khater, A. S., Zaaqoq, A. A., Wahdan, M. M., & Ashry, S. (2023). Knowledge and attitude of Ain Shams University Medical Students towards artificial intelligence and its application in medical education and practice. Educational Research and Innovation Journal, 3(10), 29–42. https://doi.org/10.21608/erji.2023.306718
Khosravi, H., Sadiq, S., & Amer-Yahia, S. (2023). Data management of AI-powered education technologies: Challenges and opportunities. Journal of Learning Letters, 1(1), 1–11. https://doi.org/10.59453/XLUD7002
Kim, F., Williams, L. A., Johnston, E. L., & Fan, Y. (2024). Bias intervention messaging in student evaluations of teaching: The role of gendered perceptions of bias. Heliyon, 10(17), 37140. https://doi.org/10.1016/j.heliyon.2024.e37140
Kim, S., Chung, E., & Lee, J. Y. (2018). Latest trends in innovative global scholarly journal publication and distribution platforms. Science Editing, 5(2), 100–112. https://doi.org/10.6087/kcse.133
Lee, G. T., Jiang, Y., & Hu, X. (2023). Brief report: Publications from mainland China, Hong Kong, and Taiwan in behavioral journals 1980–2021. Behavioral Interventions, 38(3), 793–803. https://doi.org/10.1002/bin.1947
Lee, J., Hicke, Y., Yu, R., Brooks, C., & Kizilcec, R. F. (2024). The life cycle of large language models in education: A framework for understanding sources of bias. British Journal of Educational Technology, 55(5), 1982–2002. https://doi.org/10.1111/bjet.13505
Legwegoh, A. F., & Fraser, E. D. G. (2015). Food crisis or chronic poverty: Metanarratives of food insecurity in sub-saharan africa. Journal of Hunger and Environmental Nutrition, 10(3), 313–342. https://doi.org/10.1080/19320248.2014.962777
Luckin, R., Cukurova, M., & Kent, C. (2022). Computers and education : Artificial intelligence empowering educators to be ai-ready. computers and education: Artificial Intelligence, 3(1), 100076. https://doi.org/10.1016/j.caeai.2022.100076
Luckin, R., Cukurova, M., Kent, C., & du Boulay, B. (2022). Empowering educators to be AI-ready. Computers and Education: Artificial Intelligence, 3(1), 100076. https://doi.org/10.1016/j.caeai.2022.100076
Ngaage, L. M., Borrelli, M. R., Ketheeswaran, S., & Shores, J. T. (2023). Article factors influencing gender disparities in senior authorship of plastic surgery publications. Annals of Plastic Surgery, 91(6), 638–643. https://doi.org/10.1097/SAP.0000000000003709
Opesemowo, O. A. G., & Adekomaya, V. (2024). Harnessing artificial intelligence for advancing sustainable development goals in south africa’s higher education system: A qualitative study. International Journal of Learning, Teaching and Educational Research, 23(3), 67–86. https://doi.org/10.26803/ijlter.23.3.4
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), 2307. https://doi.org/10.29333/ejmste/13428
Pham, N., Pham Ngoc, H., & Nguyen-Duc, A. (2025). Fairness for machine learning software in education: A systematic mapping study. Journal of Systems and Software, 219(1), 112244. https://doi.org/10.1016/j.jss.2024.112244
Pranckutė, R. (2021). Scopus and Web of Science stands out for systematic reviews, offering comprehensive coverage across disciplines, including journals, conferences, and patents. Publications, 9(1), 1–59. https://doi.org/10.3390/publications9010012
Ramadhan, M. R. (2024). Pengaruh konsep keadilan dalam Al Qur’an dan relevansinya dalam hukum manusia, Journal of International Multidisciplinary Research, 2(11), 134-136. https://doi.org/10.62504/jimr972
Ramlan, H., Kasnawi, T., Manda, D., Kamaruddin, S., Syukur, M., & Suardi. (2023). Hierarchy of child exploitation by parents in Makassar city, Indonesia. International Journal of Arts and Humanities Studies, 3(4), 42–47. https://doi.org/10.32996/ijahs.2023.3.4.6
Richard, K., & Molloy, S. (2020). An Examination of emerging adult military men: Masculinity and U.S. military climate. Psychology of Men and Masculinity, 21(4), 686–698. https://doi.org/10.1037/men0000303
Sasilatha, T., & Suprianto, A. A. (2025). AI-driven approaches to power grid management : Achieving efficiency and reliability. International Journal of Advances in Artificial Intelligence and Machine Learning Vol, 2(1), 27–37. https://doi.org/10.58723/ijaaiml.v2i1.380
Sohrabi, C., Franchi, T., Mathew, G., Kerwan, A., Nicola, M., Griffin, M., Agha, M., & Agha, R. (2021). PRISMA 2020 statement: What’s new and the importance of reporting guidelines. International Journal of Surgery, 88(2), 39–42. https://doi.org/10.1016/j.ijsu.2021.105918
Tri, M. F., & Nataliani, Y. (2021). Analisis pengaruh penilaian asesor terhadap kinerja guru mata pelajaran dengan k-means clustering. Indonesian Journal of Computing and Modeling, 4(1), 14–22. https://doi.org/10.24246/icm.v4i1.5063
Udah, H. (2024). Decolonising research for justice: Ethical imperatives and practical applications. International Journal of Qualitative Methods , 23(1), 2-4. https://doi.org/10.1177/16094069241294040
Ullah, R., Asghar, I., & Griffiths, M. G. (2023). An integrated methodology for bibliometric analysis: A case study of internet of things in healthcare applications. Sensors, 23(1), 67. https://doi.org/10.3390/s23010067
Vieriu, A. M., & Petrea, G. (2025). The impact of Artificial Intelligence (AI) on students’ academic development. Education Sciences, 15(3), 1–12. https://doi.org/10.3390/educsci15030343
Wang, Q. (2022). “The very interesting finding suggests that”: A cognitive frame-based analysis of interest markers by authors’ geo-academic location in applied linguistics research articles. Frontiers in Psychology, 13(1), 2-5. https://doi.org/10.3389/fpsyg.2022.1020854
Wilcox, E. S., Chimedza, I. T., Mabhele, S., Romao, P., Spiegel, J. M., Zungu, M., & Yassi, A. (2020). Empowering health workers to protect their own health: A study of enabling factors and barriers to implementing healthwise in Mozambique, South Africa, and Zimbabwe. International Journal of Environmental Research and Public Health, 17(12), 1–17. https://doi.org/10.3390/ijerph17124519
Yakir, J., Valentin, O., & Rosario, T. (2023). Bibliometric analysis of youtube platform research trends using the vosviewer application. Journal Emerging Technologies in Education, 1(1), 69–81. https://doi.org/10.55849/jete.v1i1.175
Zong, R., Zhang, Y., Stinar, F., Shang, L., Zeng, H., Bosch, N., & Wang, D. (2023). A crowd–AI collaborative approach to address demographic bias for student performance prediction in online education. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 11(1), 198–210. https://doi.org/10.1609/hcomp.v11i1.27560
Downloads
Additional Files
Published
Issue
Section
License
Online Learning in Educational Research is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with Online Learning in Educational Research agree to the following terms:
Copyright Retention: Authors retain the copyright of their work without any restrictions.
Publishing Rights: Authors retain the right to publish and distribute their work without any restrictions.
License Agreement: By publishing with Online Learning in Educational Research, authors agree that their work will be licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA). This license allows others to share and adapt the work, provided that appropriate credit is given, any changes are indicated, and the new creations are licensed under the same terms.
