Development and evaluation of eduvate CBT as an integrated artificial intelligence powered assessment ecosystem
Year: 2026
Type: article
Abstract: The growth of digital assessment has intensified concerns about examination integrity, grading efficiency, fairness, and responsible artificial intelligence (AI). This study evaluates Eduvate CBT, an integrated role-based assessment ecosystem combining examination administration, AI-assisted proctoring, automated objective grading, reviewable violation evidence, and learning analytics. A four-week quantitative evaluation covered 250 undergraduate examination sessions across four computing courses, with usability data from 15 instructors and 5 administrators. At the session level, proctoring achieved 94.8% accuracy (95% CI 91.3–96.9), 94.6% precision, 96.6% recall, and an F1-score of 95.6%. Automated grading agreed with instructor consensus for 742 of 750 sampled responses (98.9%; 95% CI 97.9–99.5) and processed the cohort in under 10 s, compared with an estimated 23.1 h of manual grading. The aggregate System Usability Scale score was 87.4 (SD = 5.8; 95% CI 84.7–90.1). Analytics identified six low-performing items in algorithmic complexity, demonstrating how assessment evidence can prompt instructional review. The findings support the feasibility of the integrated workflow, although generalisability is limited by the single-institution design, absence of a competing-system control, and unavailable formal inter-rater reliability estimates.
Source: Discover Education
Authors: Peace Awofesobi, Obiseye Obiyemi
Institution: Osun State University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,390
OpenAlex ID: W7222823342