A Borgaonkar, M Stadlman, S Salili, A Miri - Journal of STEM Education …, 2022 - jstem.org

Prediction of Students' Performance via Machine Learning: Perspective for Virtual Learning.

Stem education interventions

Borgaonkar, Miri

GSID: qOZadgYI0GkJ

Excerpt

Lack of student persistence and retention is significantly hurting the US in producing required number of qualified graduates, especially in STEM fields. Although a lot of factors contribute to students falling off track, one of the controllable factors is the identification of at-risk students followed by an early intervention. Predicting the performance of students enables educators to single out struggling and highly talented students. Struggling students are often identified very late into an academic year, thus leaving little to no time for seeking …