Assessing and Classification of Academic Efficiency in Engineering Teaching Programs

Abstract

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.

Academic efficiency of engineering university degrees and its driving factors. A PLS-DEA approach

“…On the contrary, their construction relies on the available data; some authors criticize quantitative approaches to estimate educational performance, considering that academic results cannot be adequately measured. However, recent studies show the use of standardized test results to measure students' levels of achievement (Bernal et al, 2020, p. 11;De La Hoz et al, 2021).…”

“…Now, the general idea behind the DEA methodology is that the efficiency of a DMU is determined by its ability to transform inputs into desired outputs. On the other hand, it is essential to remember that the DMUs used must be comparable, so inputs and outputs must have homogeneous units (De La Hoz et al, 2021).…”

Efficiency of Public and Private Service Delivery: The Case of Secondary Education

“…Meričková et al (2020) dealt with measuring and evaluating of the performance of secondary education in the Slovak Republic and proposed possible performance indicators in terms of public grammar schools. Also other authors (Ferro and D'Elia, 2020;De La Hoz, Zuluaga and Mendoza, 2021) address the question of measuring efficiency in education from a variety of perspectives. Cordero-Ferrera, Pedraja-Chaparro and Salinas-Jimenez (2008) focused on different possibilities of measuring efficiency in the education sector, aiming to define the most appropriate model for the evaluation of schools.…”

Efficiency analysis trees as a tool to analyze the quality of university education

“…In summary, the DEA technique estimates the observations' efficiency levels, taking into account the deviations in the production frontier (isoquant curve formed by the inputs and outputs of the system). The DEA model is non-parametric and, as has been mentioned, by means of the production frontier analysis, it estimates the efficiency of the DMUs [14], [15]; then, using the DMUs, the efficient frontier is constructed taking into account the estimated efficiency levels. On the other hand, several authors claim that the DEA tool is suitable for estimating the performance of DMUs in the public and private sectors [16].…”