We found that dropout prediction fortunately works almost equally on groups induced by various grouping factors. However, in the case of STEM majors, the predictor collection can vary as a …

In this paper, we investigate the issue of using protected at- tributes in college dropout prediction in real-world contexts. Protected attributes are traits or characteristics based on which discrimination is …

We proposed a student's dropout prediction model using an intuitionistic fuzzy set and an XGBoost algorithm called STOU2PM. The system that collected student datasets from 2012 to 2022 consisted …

Mar 13, 2023 · While multiple studies have presented viable models of higher education dropout prediction [2, 33], these models left room for improvement or, at least, exploration [24]. Selected …

Fairness Over Time: A Nation-wide Study of Evolving Bias in Dropout Prediction. In Proceedings of the Twelfth ACM Conference on Learning @ Scale (L@S ’25), July 21–23, 2025, Palermo, Italy.

We demonstrate how existing MOOC dropout prediction pipelines can be made interpretable, all while having predictive performance close to existing tech-niques. We explore each stage of the pipeline …

Prior studies on MOOC dropout prediction have encountered several challenges and limitations. First, these studies often relied on complex feature extraction processes, making it dificult to gen-eralize …

Furthermore, we analyze real-world data from a course dropout prediction model to answer RQ2. Specifically, we use Newcombe’s Hybrid score method and bootstrapping to con-struct confidence …

In order to measures the impact of mastery versus performance feedback on students’ reported achievement motivation orientations, this study experimentally manipulates the effects of …

We invite research and practice papers that address the “convergence of communities” in LAK and bring a novel perspective and approach for reflecting on the field.