Assessing and classification of academic efficiency in engineering teaching programs
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Date
2021-03-31
Authors
De la Hoz Domínguez, Enrique José
Zuluaga Ortiz, Rohemi Alfredo
Mendoza, Adel
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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.
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Citation
De La Hoz, E., Zuluaga, R. and Mendoza, A. (2021) ’Assessing and Classification of Academic Efficiency in Engineering Teaching Programs’, Journal on Efficiency and Responsibility in Education and Science, vol. 14, no. 1, pp. 41-52 https://doi.org/10.7160/eriesj.2021.140104.