Enhancing data pipelines for forecasting student performance: integrating feature selection with cross-validation

Educators seek to harness knowledge from educational corpora to improve student performance outcomes. Although prior studies have compared the efficacy of data mining methods (DMMs) in pipelines for forecasting student success, less work has focused on identifying a set of relevant features prior to...

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Detalles Bibliográficos
Autores principales: Bertolini, Roberto, Finch, Stephen J., Nehm, Ross H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8591701/
https://www.ncbi.nlm.nih.gov/pubmed/34805485
http://dx.doi.org/10.1186/s41239-021-00279-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8591701/
https://www.ncbi.nlm.nih.gov/pubmed/34805485
http://dx.doi.org/10.1186/s41239-021-00279-6

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