Using academic analytics to predict dropout risk in engineering courses
The increase of data generated and stored in the educational databases makes it possible to obtain essential information about the teaching and learning process. School dropout and performance problems continue to represent issues which challenge teachers, researchers and higher education institutio...
Main Author: | |
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Other Authors: | , , |
Format: | conferenceObject |
Language: | eng |
Published: |
2020
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Subjects: | |
Online Access: | http://hdl.handle.net/10198/21093 |
Country: | Portugal |
Oai: | oai:bibliotecadigital.ipb.pt:10198/21093 |