Abstract
We present a generalisation of the IRT framework that allows to discriminate between examinees. Our model therefore introduces examinee parameters that can be optimised with Expectation Maximisation-like algorithms. We provide
empirical results on PISA data showing that our approach leads to a more appropriate grouping of PISA countries than by test scores and socio-economic indicators.
empirical results on PISA data showing that our approach leads to a more appropriate grouping of PISA countries than by test scores and socio-economic indicators.
| Originalsprache | Englisch |
|---|---|
| Titel | Proceedings of the International Conference on Educational Data Mining |
| Redakteure/-innen | Olga Cristina Santos, Jesus Gonzalez Boticario, Cristobal Romeo, Mykola Pechenizkiy, Agathe Merceron, Piotr Mitros, Jose Maria Luna, Cristian Mihaescu, Pablo Moreno, Arnon Hershkovitz, Sebastian Ventura, Michel Desmarais |
| Seitenumfang | 2 |
| Erscheinungsort | Madrid |
| Herausgeber (Verlag) | National University for Distance Education (UNED) |
| Erscheinungsdatum | 2015 |
| Seiten | 604-605 |
| ISBN (Print) | 978-84-606-9425-0 |
| Publikationsstatus | Erschienen - 2015 |
| Extern publiziert | Ja |
| Veranstaltung | 8th International Conference on Educational Data Mining - EDM 2015 - Madrid, Spanien Dauer: 26.06.2015 → 29.06.2015 Konferenznummer: 8 http://educationaldatamining.org/EDM2015/ |
Fachgebiete und Schlagwörter
- Informatik
- Wirtschaftsinformatik
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