The Department of Statistics and Operations are organising the third and last seminar, which will be held on Tuesday, May 17 2022, which will be delivered by Prof. Liberato Camilleri. Please find here below the abstract of this seminar.
Scaling Procedures and Construct Validation in PISA 2018
The Programme for International Student Assessment (PISA) is an international comparative survey of educational achievement of 15-year-olds. The PISA programme investigates and compares the performance of education systems worldwide. Moreover, it assesses knowledge and life skills in reading, mathematical and scientific literacy rather than curricular domains. The first PISA study was conducted in 2000 and Malta participated in the 2009, 2015 and 2018 cycles.
This presentation describes the IRT models and their assumptions, as well as the IRT scaling approach used in PISA 2018. For each domain, a unidimensional multiple-group IRT model was fitted based on the two-parameter logistic model (2PL) for the binary item responses and the generalized partial credit model for the polytomous item responses. These models assume that the response probability to an item depends on the difference between the respondent’s trait level and the difficulty of the item. In addition, the model postulates that for every item, the association between this difference and the response probability depends on an additional item discrimination parameter. Moreover, this presentation describes how these models and methods were applied to the PISA 2018 data to produce the national and international item parameters and the plausible values for each domain.
In addition, PISA 2018 uses student, parent and head of school questionnaire information to generate scale score for a number of latent traits.
Finally this presentation compares attainment of Maltese students with other countries in each domain, and examine how this performance vary between the three cycles and between Maltese male and female students attending state, church and independent schools. Moreover, the presentation compares mean scale scores for latent variables between school types.