Towards technology-enhanced learning: A novel machine learning approach in education 4.0

The growing interest from the industrial and scientific community has paved the way for an increased concentration on Education 4.0 and Artificial Intelligence in particular. These smart technologies have led to significant changes, particularly within the education sector, where various hardware and software components can now track, analyze, and support students' learning performance and activity. The shift to e-learning underscored the need to enhance assessment mechanisms to ensure fairness and reliability. To address this issue, we developed a machine learning model capable of extracting patterns from students' answer sheets in a more objective and quicker assessment process. Our system deploys sophisticated Natural Language Processing (NLP) and fraud detection techniques to strengthen academic integrity. We implemented this model in both classroom and online learning environments, validating it through a simulated exam case study. The results indicate a significant improvement in assessment reliability and efficiency compared to traditional methods.