The paper focuses on the analysis of the performance of university students, with reference to first year compulsory courses. The main goal is to compare the exams in terms of difficulty, discrimination and use of the grades. Moreover, the paper aims at assessing how student careers depend on student and course characteristics. The analysis exploits an Item Response Theory approach where exams are treated as items, with a 2-Parameter Logistic model for the probability to pass the exams and a Graded Response Model for the ordinal items representing grades of passed exams. Course characteristics, such as the average student rating on teacher’s clarity, directly affect the items, whereas student characteristics, such as the type of high school, indirectly affect the items via the latent ability, even if some direct effects are allowed by fitting a MIMIC model with Differential Item Functioning. The analysis shows that IRT-MIMIC modelling is a flexible and powerful tool giving insights into the peculiarities of the exams and the role of course and student characteristics.

An IRT-MIMIC model for the analysis of university student careers / B.Bertaccini; L.Grilli; C.Rampichini. - In: QUADERNI DI STATISTICA. - ISSN 1594-3739. - STAMPA. - 15:(2013), pp. 95-110.

An IRT-MIMIC model for the analysis of university student careers

BERTACCINI, BRUNO;GRILLI, LEONARDO;RAMPICHINI, CARLA
2013

Abstract

The paper focuses on the analysis of the performance of university students, with reference to first year compulsory courses. The main goal is to compare the exams in terms of difficulty, discrimination and use of the grades. Moreover, the paper aims at assessing how student careers depend on student and course characteristics. The analysis exploits an Item Response Theory approach where exams are treated as items, with a 2-Parameter Logistic model for the probability to pass the exams and a Graded Response Model for the ordinal items representing grades of passed exams. Course characteristics, such as the average student rating on teacher’s clarity, directly affect the items, whereas student characteristics, such as the type of high school, indirectly affect the items via the latent ability, even if some direct effects are allowed by fitting a MIMIC model with Differential Item Functioning. The analysis shows that IRT-MIMIC modelling is a flexible and powerful tool giving insights into the peculiarities of the exams and the role of course and student characteristics.
2013
15
95
110
Goal 4: Quality education
B.Bertaccini; L.Grilli; C.Rampichini
File in questo prodotto:
File Dimensione Formato  
QdS Bertaccini_Grilli_Rampichini copia_conforme + frontespizioweb.pdf

Accesso chiuso

Tipologia: Pdf editoriale (Version of record)
Licenza: Tutti i diritti riservati
Dimensione 387.49 kB
Formato Adobe PDF
387.49 kB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/840696
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact