Košík

0580447 - ÚI 2024 RIV BE eng A - Abstrakt
Štěpánek, Lubomír - Dlouhá, Jana - Martinková, Patrícia
Machine-learning prediction of test item difficulty using item text wordings: Comparison of algorithms’ and domain experts’ predictive performance.
The 10th European Congress of Methodology (EAM2023) Book of Abstracts. Ghent: Ghent University, 2023. s. 26-26.
[EAM2023: European Congress of Methodology /10./. 11.07.2023-13.07.2023, Ghent]
Grant CEP: GA ČR(CZ) GA21-03658S; GA TA ČR(CZ) TL05000008
Institucionální podpora: RVO:67985807
Klíčová slova: item difficulty * machine learning models * item text wording
Obor OECD: Education, general; including training, pedagogy, didactics [and education systems]
https://eam2023.ugent.be/images/eam2023_abstracts_book.pdf
Trvalý link: https://hdl.handle.net/11104/0349220