Evaluating Student Readiness for Computer-Based and AdaptiveAssessment in Engineering Education in Nigeria

Abstract

The rapid integration of digital technologies in higher education has transformed assessment practices, with computer-based and adaptive assessment systems gaining increasing attention as viable alternatives to traditional methods. However, concerns remain about whether students in resource-constrained environments are ready to engage effectively with these systems. This study, therefore, investigates the readiness of engineering undergraduate students for computer-based and adaptive assessment systems in higher education. A cross-sectional survey research design was adopted, targeting undergraduate engineering students, with 190 participants selected as the study sample. A structured questionnaire employing a five-point Likert scale was used to collect data on digital tool usage, perceived effectiveness, engagement, confidence, and infrastructural challenges. Data were analysed using descriptive statistics, correlation analysis, regression modelling, and reliability testing, all conducted with Python-based analytical tools. The findings reveal a moderate level of digital readiness among students, with relatively higher scores in collaboration and confidence. Critical barriers were identified, including poor internet connectivity, unstable power supply, and insufficient training. Regression analysis indicated that digital learning variables contribute to variations in student confidence, though multicollinearity among predictors was observed, while reliability testing yielded a Cronbach's alpha of 0.55, reflecting moderate internal consistency. The study concludes that although students demonstrate a positive disposition toward digital and adaptive assessment systems, effective implementation demands substantial institutional investment in infrastructure and capacity development. It is therefore recommended that higher education institutions in resource-constrained contexts prioritise digital infrastructure upgrades and structured training programmes to support the scalable and equitable adoption of adaptive assessment in engineering education.