|Date and Time||Wednesday 1 September, 9:00 - 12:00, 13:00 - 16:00 CET (Geneva time)|
|Max Number of Participants||15 - fully booked|
|Registration Deadline||20 August 2021|
|Workshop Presenter||Plamen Mirazchiyski|
|Workshop Organisers||EERA Network 9|
International large-scale assessments and surveys (ILSAs) have complex sampling and assessment designs which needs to be taken into account when analyzing their data. This workshop provides information on the studies’ complexities and introduces a new software for analyzing their data – the R Analyzer for Large-Scale Assessments (RALSA). The software is written entirely in R and is open-source and free of charge. So far, RALSA is the only R package for analyzing ILSAs’ data which has a graphical user interface.
The workshop is organized as a mixture of presentations, demonstrations, exercises for the participants, and Q&A.
The first part of the workshop will introduce participants to ILSAs with specific stress on the complex sampling and assessment designs the studies employ to collect reliable and comparable data from the participating countries. The statistical complexities and issues for analysis stemming from these designs will be introduced with examples. The analytical methods will be introduced with all relevant details for analyzing the data, and the issues arising from the complex designs.
The second part will introduce the analysis software (RALSA). Its features will be explained and demonstrated through examples using both the command line and the graphical user interface.
The third part of the workshop will provide assignments for the participants which they will complete on their own with assistance from the instructor.
The last part of the workshop will be a short Q&A session where participants can ask for clarifications.
The workshop will use data from multiple European countries participating in the IEA’s International Computer and Information Literacy Study (ICILS) 2018 and the digital component of the IEA’s Progress in International Reading Literacy Study (ePIRLS) 2016. Although all studies RALSA currently supports have different designs and the analytical routines differ, the analysis steps in RALSA are the same, the software automatically applies the relevant estimation methods for each study.