GESIS Training Courses

Wiss. Koordination

Dr. Nora Skopek
Tel: +49 621 1246277

Administrative Koordination

Claudia O'Donovan-Bellante
Tel: +49 621 1246221

Analyzing PIAAC log file data

Dr. Frank Goldhammer, Krisztina Tóth

Datum: 07.04.2017 ics-Datei

Veranstaltungsort: Mannheim B2,8


The PIAAC 2012 study was the first fully computer-based large scale assessment in education. Using computers allowed not only to deliver innovative item formats and an adaptive test design, but also to collect a stream of user events (e.g., mouse clicks, text input) stored by the assessment system in log files. This data is interesting from a measurement point of view (e.g., to assess the quality of the response data), but also to address substantive research questions (e.g., to investigate the cognitive solution process). The process data gathered in PIAAC 2012 will be made available for researchers by the OECD in 2017. Therefore, this workshop will make participants familiar with the accessibility, structure and content of PIAAC log file data. In particular, we will present and provide a tool, the PIAAC LogDataAnalyzer that allows to extract log data from PIAAC xml log files. Users can select among pre-defined generic and task-specific aggregate variables (e.g., the number and sequence of page visits) and export them into a wide format. Furthermore, complete log data can be transformed and exported into a long format. The workshop will also include sample analysis to demonstrate how exported log data can be further processed in standard statistical software such as the R environment or Weka.


Empirical  researchers (educational sciences, psychology, etc.) who are interested in exploiting  PIAAC log file data from the cognitive assessment to address substantive or  measurement research questions.


Familiarity with
  • the structure and content of PIAAC log file data and derived variables
  • the PIAAC LodDataAnalyzer serving as tool to extract log data from PIAAC xml log files


Familiarity with  the PIAAC study (population, cognitive domains, sample items from Problem solving, Literacy, and Numeracy, etc.), basic knowledge in R, basic knowledge in  multivariate statistics. 


Referenteninformationen - Dr. Frank Goldhammer

Referenteninformationen - Krisztina Tóth

Weitere Informationen