School performance prediction: Ensuring fairness for disadvantaged students

This project aims to analyse the impact of socio-economic indices on the
prediction of students’ school performances and ensure fairness in this process.
The context a student is living in can affect their performance, but this should
not be considered a deciding factor. Given the sensitive nature of these
features, it is essential to avoid any form of bias in the training of predictive
models that utilise this data. To investigate the relevance of these factors, the
project will consider a real case-study dataset about students’ performance
and social inequality. Benchmark classifiers will be trained, deploying
mitigation techniques to reduce the effects of biases in the dataset and ensure
a fair evaluation prediction is achieved. The results will help highlight
connections between disadvantaged student situations and their performance,
providing useful insight to ensure equality.