Assessing and Classification of Academic Efficiency in Engineering Teaching Programs

This research uses a three-phase method to evaluate and forecast the academic efficiency of engineering programs. In first phase, university profiles are created through cluster analysis. second these is evaluated Data Envelopment Analysis. Finally, machine learning model trained validated categories efficiency. The study population corresponds 256 programs in Colombia data correspond national examination quality education 2018. results, two were identified with levels 92.3% 97.3%, respectively. Random Forest presents an Area under ROC value 95.8% prediction profiles. proposed structure evaluates predicts programs’ efficiency, evaluating between institutions similar characteristics, avoiding negative bias toward those that host students low educational levels.