Using educational data mining to predict sub-Saharan African science, technology, engineering, and mathematics students’ academic performance: a systematic review.
| dc.contributor.advisor | Govender, Irene. | |
| dc.contributor.advisor | Quilling, Rosemary Diane. | |
| dc.contributor.author | Mhlongo, Langelihle Lucky. | |
| dc.date.accessioned | 2024-05-09T10:47:27Z | |
| dc.date.available | 2024-05-09T10:47:27Z | |
| dc.date.created | 2023 | |
| dc.date.issued | 2023 | |
| dc.description | Masters Degree. University of KwaZulu-Natal, Pietermaritzburg. | |
| dc.description.abstract | Abstract available in PDF. | |
| dc.identifier.doi | https://doi.org/10.29086/10413/22989 | |
| dc.identifier.uri | https://hdl.handle.net/10413/22989 | |
| dc.language.iso | en | |
| dc.rights | CC0 1.0 Universal | en |
| dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | |
| dc.subject.other | Educational data mining (EDM). | |
| dc.subject.other | Data mining. | |
| dc.subject.other | EDM in educational systems. | |
| dc.subject.other | Effectiveness of EDM. | |
| dc.subject.other | Factors Examined in EDM. | |
| dc.title | Using educational data mining to predict sub-Saharan African science, technology, engineering, and mathematics students’ academic performance: a systematic review. | |
| dc.type | Thesis | |
| local.sdg | SDG4 |