Interpretation of computational thinking evaluation results for enrollment prediction

Abstract

During two generations (2016 and 2017) the computational thinking evaluation has been carried out in order to establish learning scenarios for new students, such interventions have been made in the Programming methodology course, it belonging to the career of Information Technology at the Technological University of Puebla in México. The results have led a personalized education for students, recognizing previous skills as well as trying to correct those missing, so that it acquires the competences respective, credit the course and improve the retention percentage of the first quarter. In this sense, when detecting possible skill gaps, is it possible to predict what will be the impact to maintain or decrease enrollment during and the end of quarter? The present work aims to answer the question by the results interpretation obtained from the computational thinking evaluation to 242 new students, generation 2018. Initially, it was stablished which would be the student's situation during and the end of four months from September to December based on the correct assessment reagents; three categories were determined: 1. Sure desertion, 2. Safe permanence, 3. Variable permanence. Later, 50 students who enrolled the next quarter (January-April 2019) were revised if they had been predicted properly; using a survey, the familiarity of key concepts of the subject Programming methodology was obtained with the aim of determining a correspondence with the evaluation of computational thinking skills, as well as the established situation, consequently, establishing the validity of predicting the enrollment.