AIMC Topic: Student Dropouts

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Using machine learning techniques for predicting the dropout of undergraduate students in Brazilian courses of statistics.

Anais da Academia Brasileira de Ciencias
This research aims to propose a machine learning approach to classify dropout outcomes among students in Statistics undergraduate programs in Brazil, identifying the most important factors associated with this phenomenon. This study uses microdata fr...

FairEduNet: a novel adversarial network for fairer educational dropout prediction.

Scientific reports
As artificial intelligence becomes increasingly prevalent in education, ensuring educational fairness has emerged as a critical concern. Algorithmic bias can lead to inequitable predictions, resulting in the unfair allocation of educational resources...

A hybrid framework of statistical, machine learning, and explainable AI methods for school dropout prediction.

PloS one
Student dropout is a significant challenge in Bangladesh, with serious impacts on both educational and socio-economic outcomes. This study investigates the factors influencing school dropout among students aged 6-24 years, employing data from the 201...

Statistical and machine learning models for predicting university dropout and scholarship impact.

PloS one
Although student dropout is an inevitable aspect of university enrollment, when analyzed, universities can gather information which enables them to take preventative actions that mitigate dropout risk. We study a data set consisting of 4,424 records ...

Model interpretability on private-safe oriented student dropout prediction.

PloS one
Student dropout is a significant social issue with extensive implications for individuals and society, including reduced employability and economic downturns, which, in turn, drastically influence social sustainable development. Identifying students ...

Student dropout prediction through machine learning optimization: insights from moodle log data.

Scientific reports
Student attrition and academic failure remain pervasive challenges in education, often occurring at substantial rates and posing considerable difficulties for timely identification and intervention. Learning management systems such as Moodle generate...

Machine learning predicts upper secondary education dropout as early as the end of primary school.

Scientific reports
Education plays a pivotal role in alleviating poverty, driving economic growth, and empowering individuals, thereby significantly influencing societal and personal development. However, the persistent issue of school dropout poses a significant chall...

Application of the performance of machine learning techniques as support in the prediction of school dropout.

Scientific reports
This article presents a study, intending to design a model with 90% reliability, which helps in the prediction of school dropouts in higher and secondary education institutions, implementing machine learning techniques. The collection of information ...

A survival analysis based volatility and sparsity modeling network for student dropout prediction.

PloS one
Student Dropout Prediction (SDP) is pivotal in mitigating withdrawals in Massive Open Online Courses. Previous studies generally modeled the SDP problem as a binary classification task, providing a single prediction outcome. Accordingly, some attempt...

Deep learning-based school attendance prediction for autistic students.

Scientific reports
Autism Spectrum Disorder is a neurodevelopmental disorder characterized by deficits in social communication and interaction as well as the presence of repetitive, restricted patterns of behavior, interests, or activities. Many autistic students exper...