QRM Conference 2023

"Using Geometric Data Analysis to Reveal Fields of Education" by Mikael Börjesson, Professor of Educational Sociology at the Department of Education,
Uppsala University

Workshop A

A longitudinal approach – is it possible? Yes!

Workshop leaders

• Alli Klapp, IPS, University of Gothenburg, alli.klapp@ped.gu.se
• Victoria Rolfe, IPS, University of Gothenburg, victoria.rolfe@gu.se 

Target group

• Researchers
• PhD students

Previous knowledge requirements

• Familiarity with large-scale data 

Learning outcomes

• Design a longitudinal study

The workshop is targeted towards researchers (in a wide sense!) interested in using a longitudinal design. Of course, this approach requires data that is longitudinal, offering repeated measures over time. The database Evaluation through Follow-up (UGU) is a longitudinal database meaning that we follow the same individuals through the educational system and repeat almost the same questionnaires in Grade 6, 9 and 12. We also have repeated measures of tests and grades through the education system which makes it possible to estimate growth over time. The workshop will start in basic prerequisites for longitudinal analyses and use the study Does grading affect educational attainment? A longitudinal study as an example on how to go about it! Taking part in this workshop will hopefully inspire you to design a longitudinal study of your own. A warm welcome!

Workshop B

Getting started with R in R Studio

Workshop leaders

• Håkan Forsberg , EDU, Uppsala University, hakan.forsberg@edu.uu.se
• Erika Majoros, IPS, University of Gothenburg, erika.majoros@gu.se 

Target group

• Researchers
• PhD students
• Teachers

Previous knowledge requirements

• Working knowledge of basic statistics is required

Learning outcomes

• Install R and RStudio
• Describe the key characteristics of the R environment
• Download and apply R packages of their interest
• Perform basic data management tasks completed during the workshop on their data
• Evaluate the applicability of the R environment in their research

The workshop provides an introduction to R, which is an increasingly used statistical environment maintained by an international team of developers, as well as RStudio, a software application that makes R easier to use. The overall aim is that participants will acquire knowledge and understanding of the basic elements of the statistical environment R, data management operations, and basic statistical analyses.

Workshop C

Performing Geometric Data Analysis (GDA)

Workshop leaders

• Mikael Börjesson, EDU, Uppsala University, mikael.borjesson@edu.uu.se
• Emil Bertilsson, EDU, Uppsala University, emil.bertilsson@edu.uu.se
• Tobias Dalberg, EDU, Uppsala University, tobias.dalberg@edu.uu.se

Target group

• Researchers
• PhD students
• Teachers

Previous knowledge requirements

• Basic statistical knowledge is required

Learning outcomes

• Be able to perform GDA

The workshop Performing Geometric Data Analysis (GDA) is consecrated to learning how to perform Geometric Data Analysis on two types of materials, contingency tables and survey data (individuals x variables). Geometric Data Analysis is a family of statistical methods originating from the work of French mathematician Jean-Paul Benzécris in the 1960s and 1970s. Best known are simple correspondence analysis, multiple correspondence analysis and Euclidean classification. More recently, the leading French representatives have been Henry Rouanet and Brigitte Le Roux. It is sufficient with basic statistical knowledge. The course targets researchers, PhD-students and teachers.

Workshop D

Latent variable modelling with lavaan in R

This workshop has been cancelled.

Please find the conference program including abstracts in pdf format by following this link.

The submissions can address a large variety of educational research questions using quantitative research methods relevant to e.g., national or international large-scale assessments, as well as matters of social recruitment, segregation, and inequality throughout the educational system. We also welcome submissions that target methodological considerations and challenges.