Impact of Active Learning Modality on Admission to Higher Education

Abstract

One of the most important problems of the Ecuadorian system of public higher education in exact sciences is the low approval rate of applicants, which results in a delay in entering the University, greater fiscal investment in human and technological resources, and wasted access to the university due to subsequent desertion. Recognizing the advantages of the application of an innovative teaching-learning methodology, called Active Learning, compared to the traditional methodology and building a forecast model for academic performance in the admission system can be favorable to reduce this problem. The objective of this work is to determine through a binary logistic regression model if the innovative methodology of Active Learning in the Admission System of a Public University will allow a learning process of higher academic performance at the end of the admission course compared to the application of the traditional learning model. The study population is made up of 558 applicants who applied to the intensive course in February 2020, whose data have been provided by the University Admissions Office. The modality that the applicant follows in the admission course is the predictor that mainly affects the academic performance. The most relevant conclusion of this study is that the application of the Active Learning methodology in admission allows a process of better academic performance compared to the application of the traditional methodology.