Assessing the impact of artificial intelligence adoption on higher education assessment effectiveness: a dimensional analysis of plagiarism detection, adaptive testing, predictive analytics, and faculty readiness

The study examines how Artificial Intelligence implementation affects Assessment Efficiency in Bahraini universities through four assessment methods which include plagiarism detection, adaptive testing, predictive analytics and faculty readiness metrics. A cross-sectional study that used a convenience sampling method, as well as data collection through the use of a web-based form, was conducted among the 293 academic staff of higher educational institutions in Bahrain both public and private. The data collected were analyzed using SPSS v28 and Structural Equation Modelling (SEM), which was run in SmartPLS software. The proposed model accounted for 46.6% of the variation in AE (R 2 = 0.466; modified R 2 = 0.458), indicating modest explanatory capacity. All four factors showed significant associations according to hypothesis testing results. Adaptive testing showed the strongest association with assessment effectiveness ( β = 0.329, t = 4.694, p < 0.001, f 2 = 0.128) because it functions as the fundamental mechanism which achieves equality and inclusion. Plagiarism detection was significantly associated with assessment effectiveness ( β = 0.188, t = 2.697, p = 0.004, f 2 = 0.035) as was predictive analytics ( β = 0.179, t = 2.838, p = 0.002, f 2 = 0.030). The results demonstrate that both methods can effectively safeguard academic honesty while enabling institutions to detect academic misconduct at an early stage. Faculty preparedness showed a small but significant association with assessment effectiveness ( β = 0.145, t = 1.982, p = 0.024, f 2 = 0.025). However small is its effect; still, it is an enabler of the most power. This work helps in creating clarity regarding the relative significance of the technical and the human variables regarding evaluation. Operationally, it throws light on the buoyant attitude of Bahraini higher education providers toward the incorporation of adaptive technologies, the consolidation of quality assurance practices, the expansion of predictive analytics capabilities, and the refinement of pedagogical staff training.