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This study explores data mining techniques for predicting student dropout in higher education. The research compares different methodological approaches, including alternative algorithms and variations in model specifications. Additionally, we examine the impact of employing either a single model for all university programs or separate models per program. The performance of models with students grouped according to their position on the program study plan was also tested. The training datasets were explored with varying time series lengths (2, 4, 6, and 8 years) and the experiments use academic data from the University of Porto, spanning the academic years from 2012 to 2022. The algorithm that yielded the best results was XGBoost. The best predictions were obtained with models trained with two years of data, both with separate models for each program and with a single model. The findings highlight the potential of data mining approaches in predicting student dropout, offering valuable insights for higher education institutions aiming to improve student retention and success. © 2023 Associacao Portuguesa de Sistemas de Informacao. All rights reserved.

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Technological developments related to renewable energy led to a decrease on the prices of generation and allowed the penetration of distributed energy resources in power systems. This context, combined with other factors, such as the development of electric vehicles, enabled the rapid evolution of Smart Grids. As a consequence, Distribution System Operators (DSOs) have been investing in this field to keep up with its deployment. This work presents a case study that compares a set of European DSOs regarding their investment in Smart Grid projects. The methodology underlying this study is based on the construction of composite indicators using the Data Envelopment Analysis technique. Furthermore, we evaluate the evolution in the DSOs performance between 2013 and 2017 using a Malmquist index. The results are discussed in the light of their contribution to the definition of public policies in the energy field. © 2021, Springer Nature Switzerland AG.

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