This data article presents data on the results in national assessments for secondary and university education in engineering students. The data contains academic, social, economic information for 12,411 students. The data were obtained by orderly crossing the databases of the Colombian Institute for the Evaluation of Education (ICFES). The structure of the data allows us to observe the influence of social variables and the evolution of students' learning skills. In addition to serving as input to develop analysis of academic efficiency, student recommendation systems and educational data mining. The data is presented in comma separated value format. Data can be easily accessed through the Mendeley Data Repository (https://data.mendeley.com/datasets/83tcx8psxv/1).

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

This research develops an academic production function for the educational process of industrial engineers in Colombia. The proposed function objectively analyses the relationships between the academic competencies obtained in secondary education and the university. The data used correspond to the standardized tests of 4,977 students at the end of high school and university. In the first stage of the model, the structure of the production function was empirically evaluated using a Partial Least Square - Structural Equation Modeling approach. Consequently, in the second stage, the efficiency of the relationships in the academic production function is estimated using Data Envelopment Analysis. The Goodness of Fit index of the empirical model was 0.89, thus, confirming the relationships between the construct's variables. The model validates four transformation relationships and subsequently estimates the efficiency of the interactions in the production function. The average efficiency results of the model in its constant scale are 16.30%, 2.17%, and 5.43%. In conclusion, the model explains the capacity of universities to transform inputs (basic competencies of the secondary school) into desired outputs (professional academic competencies). Additionally, the model analyses professional performance from the interactions among academic competencies.

Las instituciones universitarias se enfrentan a retos de competitividad que se enmarcan en las exigencias de la sociedad, los cambios de preferencia de los estudiantes y la evolución tecnológica; esto plantea la necesidad de generar herramientas objetivas para la toma de decisiones que permitan identificar las instituciones que están aportando efectivamente a la formación de profesionales de alto nivel. En el presente trabajo se desarrolla una metodología bajo el enfoque Seis Sigma para medir el desempeño del sistema educativo. Ahora, para evaluar la metodología se utilizan datos del examen colombiano para la evaluación de la calidad en la educación superior para el área de Ingeniería. Los resultados muestran que el nivel sigma del sistema educativo colombiano se encuentra en Z= 2,17 y un rendimiento Y= 75%, lo cual dentro de los criterios establecidos en la investigación es considerado un nivel Aceptable. Como aporte significativo del estudio se presenta una estructura para la evaluación, monitoreo y mejoramiento de la de educación universitaria utilizando el enfoque Seis Sigma. La estructura propuesta es replicable y reproducible a cualquier entorno educativo donde se implementen exámenes estandarizados.

This research aims to design a helpful methodology for estimating universities' relative impact on students as a sustainability factor in higher education. To this end, the research methodology implemented a two-stage approach. The first stage involves the relative efficiency analysis of the study units using Fuzzy Data Envelopment Analysis. The second stage consists of a predictive evaluation of the efficiency of the study units. Consequently, among the most relevant results of the research, it is observed that the methodology identifies the institutions that need to strengthen the academic competencies of the industrial engineering program. Additionally, we developed a benchmark analysis called Efficient Route to help inefficient units achieve efficiency, associating efficiency, and sustainability as pillars of higher education processes.

This research aims to design a quality management tool in education. The methodology comprises two stages: first, the construction of the decision tree model, and second, the efficiency evaluation. For the validation and development of this research, the data modelled corresponds to the standardized exams for higher education in Colombia of ninety industrial engineering degrees. Among the results, the citizenship skills (CC_PRO) generate the most significant contribution to the model. On the other hand, the written communication competence (CE_PRO) generates a minor contribution to the model. In addition, the most relevant result of the research is the design and validation of a tool to estimate educational efficiency using the efficiency analysis tree (EAT) and data enveloping analysis (DEA) models. The proposed tool allows the generation of specific targets to increase the level of efficiency of universities through the nodes of the decision tree, which contributes to the spectrum of knowledge on models for educational management. In conclusion, this research presents a tool for the management of educational processes through the analysis of efficiency using EAT, estimating the efficiency of universities and setting the foundations for forecasting future efficiency scenarios.