Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 17th May 2024, 07:27:06am GMT

 
 
Session Overview
Session
09 SES 01 A: Getting Started with R in RStudio
Time:
Tuesday, 22/Aug/2023:
1:15pm - 2:45pm

Session Chair: Monica Rosén
Location: Gilbert Scott, EQLT [Floor 2]

Capacity: 120 persons

Research Workshop

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Presentations
09. Assessment, Evaluation, Testing and Measurement
Research Workshop

Getting started with R in RStudio

Monica Rosén, Erika Majoros

University of Gothenburg, Sweden

Presenting Author: Rosén, Monica; Majoros, Erika

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

Methodology, Methods, Research Instruments or Sources Used
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.

Conclusions, Expected Outcomes or Findings
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

References
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


 
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