Publicação
Trus4ed: decoding the conditions for trust in teachers and machine learning models for 4th grade predictions
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Xufre, Patrícia | |
| dc.contributor.advisor | Nunes, Luís Catela | |
| dc.contributor.author | Pereira, Alexandra Costa | |
| dc.date.accessioned | 2024-10-30T09:35:15Z | |
| dc.date.available | 2024-10-30T09:35:15Z | |
| dc.date.issued | 2024-01-10 | |
| dc.date.submitted | 2024-01-10 | |
| dc.description.abstract | Effectively predicting student failure is crucial for timely resource allocation and preventing academic difficulties. This thesis explores conditions where machine learning model predictions should be trusted over teachers' judgments, recognizing potential disparities. Beginning with model building, one investigates the impact of both teachers' and students' features on the model-teacher interplay. Contrary to expectations, teachers' features do not significantly influence this dynamic, but a closer analysis of students' reveals the significance of psychological factors and academic achievement levels. The model exceeds for high achieving students and those with more distinctive psychological patterns. This research provides relevant insights into shaping reliable educational predictions in diverse academic scenarios. | pt_PT |
| dc.identifier.tid | 203600584 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/174304 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | UID/ECO/00124/2013 | pt_PT |
| dc.subject | Machine learning in education | pt_PT |
| dc.subject | Predictive modeling | pt_PT |
| dc.subject | Economics of education | pt_PT |
| dc.subject | Interplay teacher-model | pt_PT |
| dc.title | Trus4ed: decoding the conditions for trust in teachers and machine learning models for 4th grade predictions | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Economics from the Nova School of Business and Economics. | pt_PT |