Download the conference program (2.28 MB)
The PIAAC workshops welcome researchers from different disciplines interested to work or already working with PIAAC data. It is expected that the participants have good empirical knowledge and experience in the respective statistical software. The workshop comprises lectures and practical sessions covering the following elements: (a) Theoretical and methodological input from the lecturers (see description of contents below); (b) Opportunity for participants to present their own research or research ideas with PIAAC data (optional); (c) Discussion of the questions outlined in the workshop regarding the data used and methods as well as specific feedback from the lecturers.
There will be no participation fees. The workshops will be limited to a maximum of 15 participants and will be conducted virtually. Please send your application with the respective subject "Workshop 2022 - Analyzing PIAAC data with SEM" OR Workshop 2022 - Analyzing PIAAC data with R" to the PIAAC Research Data Center (fdz-piaac(at)gesis(dot)org) by March 15, 2022.
Workshop: Analyzing PIAAC data with structural equation modeling in Mplus |
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Lecturer: Ronny Scherer (Centre for Educational Measurement at the University of Oslo) Date: March 22-23, 2022 (Time: 4 am – 9 am EST/ Time: 9 am – 2 pm CET) Place: Virtual (Zoom) Content: Structural equation modeling (SEM) represents a statistical approach to disentangle the relationships among latent and/or manifest variables, across groups, over time, and at different analytical levels. The potential of SEM has been recognized in many areas, including educational sciences, sociology, psychology, and business. This workshop provides an introduction to the principles and procedures of basic and more advanced SEM in the context of the international large-scale assessment PIAAC. Specifically, the following topics are covered: (a) Principles of structural equation modeling (model specification, identification, estimation, and evaluation), (b) Measurement models and confirmatory factor analysis, (c) Measurement invariance testing with few and many groups (including multi-group CFA, multilevel CFA, and the alignment method), and (d) Structural regression and indirect effects models (including multi-group and multilevel SEM). Participants can also present their own research or research ideas using PIAAC data and receive feedback on how to improve the analysis (optional). Data: PIAAC Public Use Files Software: SPSS and Mplus Schedule: Agenda (266 kB) Recommended reading: Maehler, D. & Rammstedt, B. (2020). Large-scale cognitive assessment: Analyzing PIAAC data. Series: Methodology of Educational Measurement and Assessment (MEMA). Springer: Cham. https://link.springer.com/book/10.1007/978-3-030-47515-4 |
For any questions please contact the RDC PIAAC (fdz-piaac@gesis.org).
Workshop: Analyzing PIAAC data using the R EdSurvey package |
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Lecturer: Paul Bailey1, Ting Zhang1, Saida Mamedova1, Emily Pawlowski1, Emmanuel Sikali2, Michael Lee1, Eric Buehler1, & Sinan Yavuz1 (1American Institutes for Research; 2National Center for Education Statistics) Date: March 22, 2022 (Time: 10 am – 2 pm EST/ 3 pm – 7 pm CET) Place: Virtual (Zoom) Content: This course will provide an overview of the PIAAC study and guidance in data analysis strategies, including the selection and use of appropriate plausible values, sampling weights, and variance estimation procedures. The course will train participants in the analysis of PIAAC data files using the R package EdSurvey, which was developed specifically to analyze large-scale assessment data with complex psychometric and sampling designs. Participants will learn how to
This course is designed for researchers and policy analysts across various sectors and organizations who are interested in learning how to analyze PIAAC data. Participants should have at least a basic knowledge of R software (e.g., have taken entry-level training in R programming), as well as of statistical techniques, including statistical inference and multiple regression. A working knowledge of plausible values and sampling theory would be helpful but is not required. Participants should bring a computer preloaded with the latest version of the R and RStudio software so that they can practice the analytical techniques covered in the lesson plan. Data: PIAAC Public Use Files Software: R Schedule: comming soon Recommended reading: Maehler, D. & Rammstedt, B. (2020). Large-scale cognitive assessment: Analyzing PIAAC data. Series: Methodology of Educational Measurement and Assessment (MEMA). Springer: Cham. https://link.springer.com/book/10.1007/978-3-030-47515-4 |
For any questions please contact the RDC PIAAC (fdz-piaac@gesis.org).

Keynote: Enhancing the Utility of International Large-Scale Assessments [Abstract (536 kB)] |
Dr. Irwin Kirsch (Educational Testing Service/ ETS, USA) Irwin Kirsch is the Ralph Tyler Chair in Large Scale Assessment and Director of the Center for Global Assessment at ETS in Princeton, NJ. In his role as director of the center he oversees several teams of research scientists, assessment designers and platform developers who are responsible for the development, management and implementation of various large-scale national and international assessments. Over the course of his career, Dr. Kirsch has worked in close collaboration with a number of state, national and international organizations including the World Bank, UNESCO, the International Association for the Evaluation of Educational Achievement (IEA), and the Organization for Economic Co-operation and Development (OECD) where he currently oversees the development and conduct of the two largest international assessments that provide policy makers and key stakeholders with national and international comparative data on literacy and workforce preparedness – PIAAC and PISA. In addition to his assessment work, Dr. Kirsch is a member of the ETS research management team, serves on the board of a non-profit literacy organization, and as a reviewer for several journals. He has also published numerous research articles and book chapters dealing with issues around designing, developing and interpreting cognitive-based scales and has written a number of policy reports using large-scale assessment data that focus on the growing importance of skills and their connections to life outcomes. Graphik recording of Keynote Speech (4.82 MB) (1.17 MB)
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Keynote: This Is A Skills World [Abstract (8.27 kB)] |
Prof. Dr. Rolf van der Velden (Maastricht University, The Netherlands) Rolf van der Velden is Professor at Maastricht University and director of the Research Centre for Education and the Labour Market (ROA). He is research fellow at the Graduate School of Business and Economics at Maastricht University (GSBE) and fellow of the Amsterdam Centre for Learning Analytics (ACLA). Van der Velden supervised several national and international studies on the transition from school to work, such as the international REFLEX project (see “The Flexible Professional in the Knowledge Society” by Allen & Van de Velden, 2011) and the “Higher Education as a Generator of Strategic Competences” project (called HEGESCO). Currently he coordinates the Netherlands Cohort Study on Education (https://nationaalcohortonderzoek.nl/) of the Netherlands Initiative for Education Research (NRO) and is advisor for the Programme for the International Assessment of Adult Competencies (PIAAC). His expertise is on transition from education to work (e.g., Humburg and van der Velden, 2015; Levels, van der Velden and Di Stasio, 2014), knowledge economy and the demand for 21st century skills (e.g., Humburg and van der Velden, 2017), and skills mismatches (e.g., van der Velden and Verhaest, 2017; van der Velden and Bijlsma, 2019; Fregin, Levels, and van der Velden, 2020). Graphik recording of Keynote Speech (5.77 MB)
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