On Data Protection Regulations, Big Data and Sledgehammers in Higher Education

Abstract

Universities in Latin America commonly gather much more information about their students than allowed by data protection regulations in other parts of the world. We have tackled the question of whether abundant socio-economic data can be harnessed for the purpose of predicting academic outcomes and, thereby, taking proactive actions in student attention, course planning and resource management. A study was conducted to analyze the data gathered by a private university in Ecuador over more than 20 years, to normalize them and to parameterize a Multi-Layer Perceptron neural network, whose best-performing configuration would be used as a benchmark for the comparison of more recent and sophisticated Artificial Intelligence techniques. However, an extensive scan of hyperparameters for the perceptron—exploring more than 12,000 configurations—revealed no significant relationships between the input variables and the chosen metrics, suggesting that there is no gain from processing the extensive socio-economic data. This finding contradicts the expectations raised by previous works in the related literature and in some cases highlights important methodological flaws.

Implementing Continual Learning Scenarios: Review of a Ml Technqiue

“…Before transformers, recurrent neural networks (RNN) were the go-to solution for natural language processing. Numerous efforts have since continued to push the boundaries of recurrent language models and encoder-decoder architectures [38,24,15]. Recurrent models typically factor computation along the symbol positions of the input and output sequences.…”

The Current Application Status of Big Data Information Technology in Higher Education: A Bibliometric Analysis from 2013 to 2023

“…Some scholars also indicate that big data brings risks of privacy disclosure [2]. Other scholars suggest that in the face of the development of information and big data, teachers and students must master relevant technologies, which may pose a learning burden on them [3].…”