Early prediction of student performance in CS1 programming courses.

ABSTRACT: There is a high failure rate and low academic performance observed in programming courses. To address these issues, it is crucial to predict student performance at an early stage. This allows teachers to provide timely support and interventions to help students achieve their learning objectives. The prediction of student performance has gained significant attention, with researchers focusing on machine learning features and algorithms to improve predictions. This article proposes a model for predicting student performance in a 16-week CS1 programming course, specifically in weeks 3, 5, and 7. The model utilizes three key factors: grades, delivery time, and the number of attempts made by students in programming labs and an exam. Eight classification algorithms were employed to train and eva

SUBMITTER: Llanos J 

PROVIDER: S-EPMC10702991 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature