Artificial intelligence (AI) is increasingly utilized in higher-education assessment; however, existing research remains fragmented, with limited synthesis regarding the interplay of fairness, transparency, pedagogy, and governance. To address this gap, this systematic review analyzed 47 studies published between 2019 and 2025 across Western, Gulf, South Asian, and East Asian contexts, employing the PRISMA 2020 framework. Among these studies, 32 addressed fairness, 29 examined transparency, 34 explored pedagogical implications, and 22 investigated governance practices. Quantitative evidence demonstrated that AI achieved greater scoring consistency than human graders in over two-thirds of fairness-focused studies. Conversely, more than half of the transparency studies identified inadequate or partial disclosure of AI decision processes. Pedagogical studies indicated AI-enhanced feedback frequency and revision opportunities in approximately 70% of cases, although teacher mediation was necessary to mitigate over-reliance. Governance findings showed that fewer than one-third of institutions had established policies or audit mechanisms for ethical AI use. Based on these patterns, the review proposes a governance-anchored model that integrates fairness and transparency with pedagogical design, providing a coherent framework for institutions aiming to implement AI-based assessment responsibly and equitably.
Maha Alfaleh (2026) studied this question.