Artificial Intelligence Supported Online Assessment and Evaluation in Higher Education: A Systematic Review With SWOT Analysis

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dc.contributor.authorUstun, Aysin Gaye
dc.contributor.authorKayali, Bunyami
dc.contributor.authorYavuz, Mehmet
dc.date.accessioned2026-09-01T15:52:36Z
dc.date.available2026-09-01T15:52:36Z
dc.date.issued2026
dc.departmentBayburt Üniversitesi
dc.description.abstractArtificial intelligence-supported online assessment and evaluation (AI-SOAE) systems have the potential to transform assessment and evaluation processes in higher education; however, there is a need for a comprehensive evaluation of the pedagogical, technical, and ethical dimensions of these systems. In this regard, the study systematically examined the characteristics of AI-SOAE systems within the framework of a SWOT analysis. A systematic literature review method was used in the research. Ninety-eight studies published between 2018 and 2025 in the Web of Science (WoS), Scopus, and Education Resources Information Centre (ERIC) databases were analysed in accordance with PRISMA guidelines. The findings show that the strengths of AI-SOAE systems include personalised feedback, advanced assessment processes, increased efficiency, and data-driven decision support mechanisms. In contrast, technical infrastructure limitations, algorithmic biases, data management issues, and negative user experiences were identified as the weaknesses of the systems. The analysis also reveals that AI-SOAE systems offer significant opportunities in terms of pedagogical transformation, digitalisation, and institutional competitiveness; however, they face threats such as data security, ethical concerns, risks to academic integrity, and limited empirical evidence. Consequently, AI-SOAE systems offer context- and application-dependent potential for supporting assessment and evaluation practices in higher education. Effectively realising this potential depends on strengthening technical infrastructure, managing algorithmic risks, and developing transparent, ethical, and institutional policy frameworks. By synthesising the literature in the field of AI-SOAE in a structured manner, this study provides a comprehensive assessment for researchers, educators, and policymakers.
dc.identifier.doi10.1177/21582440261423669
dc.identifier.issn2158-2440
dc.identifier.issue2
dc.identifier.scopus2-s2.0-105037728726
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1177/21582440261423669
dc.identifier.urihttps://hdl.handle.net/20.500.12403/8487
dc.identifier.volume16
dc.identifier.wosWOS:001753863700001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSage Publications Inc
dc.relation.ispartofSage Open
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20260820
dc.subjectArtificial Intelligence
dc.subjectOnline Learning
dc.subjectAssessment And Evaluation
dc.subjectHigher Education
dc.subjectSystematic Literature Review
dc.titleArtificial Intelligence Supported Online Assessment and Evaluation in Higher Education: A Systematic Review With SWOT Analysis
dc.typeReview Article

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