Implementation of an early alert system in quizzes of a high complexity subject in higher education: Improvement of student performance and teacher perception

Abstract

Early Alert Systems (EAS) play a fundamental role in education by supporting the learning process and evaluating student performance. In this study, an innovative EAS designed to specifically identify weaknesses in Cognitive Skills (CS) in first-year higher education students is presented, focusing on a challenging course at a South American university. Through big data technology, approval rates linked to various cognitive skills were evaluated using quizzes. Subsequently, teachers, after analysis and dialogue, applied adapted strategies to strengthen these skills in their classes, which were evaluated in subsequent exams. The sample under study included 1,691 students from various health majors enrolled in a complex subject. The experimental group (994 students) that participated in the EAS was compared with a control group (697 students). Evaluations validated by the academic team were used, applying three quizzes throughout the 2022-20 academic period, and the results were analysed with the Power BI computer tool, generating online reports that highlighted CS by section. The EAS, based on teacher surveys, is innovative and it also positively impacts student achievement, evidenced in overall approval rates, by teacher and section. In addition to promoting collaboration among professors, it also improves the teaching quality and suggests a positive impact on the learning of complex subjects in Higher Education Institutions (HEIs). This comprehensive approach to early monitoring of student performance shows promise for the ongoing improvement of educational quality.