Computer or teacher: Who predicts dropout best?
IntroductionMachine learning algorithms use data to identify at-risk students early on such that dropout can be prevented. Teachers, on the other hand, may have a perspective on a student’s chance, derived from their observations and previous experience. Are such subjective perspectives of teachers...
Main Authors: | Irene Eegdeman, Ilja Cornelisz, Chris van Klaveren, Martijn Meeter |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-11-01
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Series: | Frontiers in Education |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/feduc.2022.976922/full |
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