Artificial intelligence-based formative assessment to improve academic performance in university students
Keywords:
Formative Assessment, Artificial Intelligence, Academic Performance, University Students, HealthAbstract
In university settings characterized by high diversity in learning styles, levels of prior preparation, and academic pacing, traditional formative assessment often fails to provide timely and specific feedback. Optimizing the teaching–learning process frequently requires the integration of emerging technologies such as Artificial Intelligence (AI). Accordingly, the objective of this study was to evaluate the implementation of an educational intervention incorporating AI-based formative assessment to improve the academic performance of university students in physical activity and health sciences. The study selected a representative and sufficient sample of professors (n= 143) and university students (n= 52) from different degree programs in physical activity and health sciences. Faculty perceptions of the field of application were assessed, and an experimental group (n= 26) received an AI-supported formative intervention, with its effects subsequently evaluated. The faculty assigned high ratings across all analyzed dimensions, recognizing AI as an efficient resource for enhancing monitoring and quality in university learning. At the intragroup level, the experimental group of students showed significant improvements across all dimensions (p< 0.001), whereas the control group, which maintained traditional teaching methods, exhibited modest and non-significant gains. At the intergroup level, significant differences were confirmed in favor of the experimental group (p< 0.001) across all dimensions (Feedback, Learning Monitoring, Progress in Activities, Outcomes Achieved, and Autonomous Learning). These findings demonstrate that AI-based formative assessment had a positive and relevant effect on the academic performance of students in the experimental group.
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