Using interpretable machine learning approaches to predict and provide explanations for student completion of remedial mathematics
Crossref DOI link: https://doi.org/10.1007/s10639-024-12647-6
Published Online: 2024-05-10
Published Print: 2024-11
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Mgonja, Thomas https://orcid.org/0000-0002-3099-4048
Text and Data Mining valid from 2024-05-10
Version of Record valid from 2024-05-10
Article History
Received: 23 August 2023
Accepted: 21 March 2024
First Online: 10 May 2024
Declarations
:
: I have no conflict of interest to disclose.