SUCCESS FACTORS FOR FIRST-YEAR STUDENTS IN ENGINEERING DEGREES. PROPOSALS FOR IMPROVING THE ACADEMIC PERFORMANCE

Abstract

The aim of this paper is to analyse the main determinants of the academic results obtained by first-year undergraduate students enrolled at the School of Engineering (ETSI) of the University of Seville in the 2015/16 academic year. By conducting a survey of students, and after the corresponding statistical treatment of the information obtained, it is possible to identify and quantify the vector of characteristics that contributes to the academic success of an ETSI student. The proposed methodology consists of two stages: (1) Determining the individual efficiency of each student using the Data Envelope Analysis (DEA) technique. The efficient student will be the one who obtains the best results (qualification-learning) from the resources used: fundamentally, study and class attendance. The DEA technique will make it possible to identify the group of efficient students and the necessary improvements in the case of non-efficient students. (2) Measuring the effect on academic performance of each student's intrinsic characteristics (personal and environmental). A multiple regression analysis identifies the determinants of academic success, either in terms of input-output efficiency or in terms of marks obtained. The determination of efficient students in the management of academic resources allows the creation of study groups of students located in similar areas of the "efficiency frontier", which encourages, among other aspects, proactive and collaborative learning, the variation of behaviour in an efficient way and the development of the necessary competences. In addition, the analysis of the factors determining academic success may constitute, for ETSI's Board, a tool for reflection (which can be updated each year) on the teaching activity at the Centre; a tool aimed at proposing recommendations (to students and lecturers) that have been empirically tested. Keywords: teaching innovation, academic performance, DEA, linear regression, success factors, students in Engineering degrees.