The School of Quantitative Research Methods in Education (QRM, https://www.gu.se/en/qrm) is a research school and an emerging network funded by the Swedish Research Council. QRM aims to contribute to rebuilding of the competence of quantitative methodological knowledge in educational research in Sweden and elsewhere. The proposed workshop contributes to this aim by training basic competence in using the statistical environment, R, which is a widely used, open source project. However, using R is still relatively new in educational sciences.

R is an increasingly used statistical environment maintained by an international team of developers. The proposed workshop is intended for analysts and researchers who do not have yet the knowledge and experience using R. Working knowledge of basic statistics is required.

The workshop will begin with a brief overview of the R environment based on Venables, et al. (2014). Then, based on Grolemund (2014), the workshop leader will assist the participants to download R as well as RStudio, a software application that makes R easier to use.

Afterward, basic data management tasks will be demonstrated and practiced, including importing and exporting data. Then basic statistical analyses will be demonstrated and practiced using several R packages, including plotting the data. Exporting outputs will be also practiced. Finally, based on the workshop participants’ interest and pace of work, advanced statistical analyses will be demonstrated and practiced.

The workshop will end with informing the participants about resources to further develop their knowledge in R and commonly used R packages for working with international large-scale assessment (ILSA) data. Participants should bring a laptop. The workshop leaders will hand out the presentation slides beforehand and the R scripts in case of inquiry afterward.

Draft agenda:

• Introduction
• Downloading and installing R and RStudio
• Data management
• Basic statistical analyses
• Creating plots
• Advanced statistical analyses (Optional)
• Summary and further avenues and resourses

Data Practical tasks will be performed using publicly available data from the Second International Mathematics Study (1980) will be retrieved from the Center for Comparative Analysis of Educational Achievement (COMPEAT) website: https://www.gu.se/en/center-for-comparative-analysis-of-educational-achievement-compeat/studies-before-1995/second-international-mathematics-study-1980#Data---Population. COMPEAT is an infrastructure project with the general aim to build databases of international large-scale studies in educational achievement conducted by IEA and OECD before the year 2000 and to support secondary analyses of these data. Methods Basic statistics and optionally advanced statistical methods, such as regression analysis or item response theory modeling will be used.

By the end of the workshop, the participants are expected to have gained the following learning outcomes • Install R and Rstudio • Download and apply an R package • Effectively use the documentation of an R package • Perform basic data management tasks, such as computing or recoding variables, subsetting data in RStudio • Perform basic statistical analyses, including basic plots

Center for Comparative Analysis of Educational Achievement (nd). https://www.gu.se/en/center-for-comparative-analysis-of-educational-achievement-compeat Grolemund, G. (2014). Hands-On Programming with R: Write Your Own Functions and Simulations. https://rstudio-education.github.io/hopr Venables, W. N., Smith, D. M., & R Core Team (2014). An Introduction to R. https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf