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: 19th Aug 2026, 21:29:08 EET
|
Daily Overview |
| Session | ||
99 ERC SES 05 L: NW 09 Assessment, Evaluation, Testing and Measurement: New open data, new opportunities: A new international panel dataset on students’ math and science achievement including rich context data
Research Workshop | ||
| Presentations | ||
99. Emerging Researchers' Group (for presentation at Emerging Researchers' Conference)
Research Workshop New Open Data, New Opportunities: A New International Panel Dataset on Students’ Math and Science Achievement Including Rich Context Data IEA Hamburg, Germany Presenting Author:International large-scale assessments (ILSAs) have long been a cornerstone of comparative education research, offering valuable insights into trends in achievement and equity across countries. Yet, their cross-sectional nature has limited the ability to study the students’ learning progress over time. The TIMSS 2023 Longitudinal Study introduces panel data, that is, reassessing the same students one year later to capture individual learning gains in mathematics and science, marking a major innovation within major ILSAs. This workshop introduces this open-access international dataset, which provides new opportunities for researchers to study learning growth and its contextual determinants. Participants will gain an overview of the study design, including its panel structure, and contextual data from students, teachers, parents, and principals. The session will demonstrate how the data can be used to address questions about learning gains, classroom effects, and educational equity The workshop will include:
By engaging with this new resource, participants will discover how the TIMSS Longitudinal dataset can expand the boundaries of international educational research—identifying learning determinants thanks to the new longitudinal data, moving beyond simple comparisons between countries and cycles. | ||
