dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Brinkhuis, Matthieu | |
dc.contributor.author | Vries, Wiebe de | |
dc.date.accessioned | 2023-04-12T00:00:58Z | |
dc.date.available | 2023-04-12T00:00:58Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/43774 | |
dc.description.abstract | In this thesis, we have analysed multiple-choice and text questions within faculties using deviation profiles. Three methods were used to calculate these deviation profiles, a naive percentage-based, an IRT-based approach and a proportional IRT-based approach. The results of these analyses were contradictory. Further research is needed to examine whether examinees score better on
multiple-choice or text questions. We also analysed differential item functioning for two groups
based on their preferred language. The result of this analysis was that within some faculties, there
seems to be DIF present within tests. Further research is needed to verify whether this is true for
the entire test set. We also discuss future works based on this thesis and the test set used. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | In this thesis, we have analysed multiple-choice and text questions within faculties using deviation profiles. Three methods were used to calculate these deviation profiles, a naive percentage-based, an IRT-based approach and a proportional IRT-based approach | |
dc.title | Balance in test results : Ways higher education students reach test scores within Utrecht University | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | balance;test;results;item response model;item response theory; analysis | |
dc.subject.courseuu | Artificial Intelligence | |
dc.thesis.id | 15626 | |