As part of our mission, IEA aims to advance research and innovation by actively promoting research projects and activities.
In 2021, the IEA R&D (Research and Development) Fund was created to improve the science and methodology of IEA studies, ensuring that they remain at the forefront of international large-scale assessments) in education.
Each year, the R&D Fund addresses a variety of key topics for ILSAs in education through open and thematic calls. We look forward to seeing how the future cycles of R&D funding further the work of IEA and research in the ILSA field.
IEA is delighted to have awarded 23 total projects with funding across three calls for R&D proposals. The proposals, focus on a diverse range of topics relevant to the work of IEA. Information on the awardees from Call 4 is here. See below for the full list of projects and the available outcomes.
| Title and Authors | Status | Outcome |
|---|---|---|
| An AI-Driven Approach to TIMSS Item Verification and Alignment Ummugal Bezirhan and Matthias von Davier | Outcome Forthcoming | |
| SMART: Survey Mode and Response Trends in TIMSS and PIRLS Context Questionnaires Yuan-Ling Liaw, Alec Kennedy, Rune Müller Kristensen, and Rolf Strietholt | Outcome Forthcoming | |
| Striving for More Inclusiveness: Understanding and Addressing Student Exclusions in TIMSS and PIRLS Sabine Meinck, Umut Atasever, Matthias von Davier, Rolf Strietholt, and Bethany Fishbein | Outcome Forthcoming | |
| Improving IEA Questionnaires for Use in Low- and Middle-Income Countries Oliver Neuschmidt, Clara Beyer, Sarah Howie, and Katherine Reynolds | Outcome Forthcoming | |
| Information Retrieval Using Retrieval-Augmented Generation on PIRLS Documents Widianto Persadha and Heiko Sibberns | Outcome Forthcoming | |
| Assessment Design for Accommodating Participants with Tailored Support Rolf Strietholt, Nurullah Eryilmaz, Julian Fraillon, Olga Kunina-Habenich, and Ana María Mejía-Rodríguez | Outcome Forthcoming | |
| A Two-Step Imputation Approact Combining Item-Reponse-Theory and Deep-Learning Methods in Large Scale Survey Assessments Peter van Rijn, Usama Ali, and Priyadarshini Dwivedi | Outcome Forthcoming |
| Title and Authors | Status | Outcome |
|---|---|---|
| An Examination on the Performance of Sampling Variance Estimators in ILSAs Umut Atasever | Outcome Forthcoming | |
| Field Trial Sample Size Andrés Christiansen | Outcome Forthcoming | |
| Using Large Language Models for Automatic Item Generation: Development and Validation for TIMSS Fourth Grade Marek Muszyński | Outcome Forthcoming | |
| Approximate Areas of Interest for Enhanced Understanding of Student Motivation and Task Interaction in IEA Assessments Artur Pokropek | Published | Final Report |
| Enhancing Cross-Cultural Comparisons in ILSAs: A Comprehensive Investigation and Guideline Development Using TIMSS 2019 Data Andrés Sandoval-Hernández | Outcome Forthcoming | |
| Dimensionality and Mode Effects in PIRLS 2016 and 2021: Evaluating the Comparability of Different Assessment Modes Rolf Strietholt | Outcome Forthcoming | |
| Gauging the Instructional Sensitivity of Ordinal Assessment Items Anne Traynor | Outcome Forthcoming |
| Title and Authors | Status | Outcome |
|---|---|---|
| CABE: Studying School-level Nonresponse within a Partial Identification Framework Diego Cortes, Jeff Dominitz, Maximiliano Romero, and Sabine Meinck | Published | Final report |
| Improving Scaling in Large-scale Assessment: A Variable Selection Approach to Latent Regression Yunxiao Chen, Motonori Oka, and Matthias von Davier | Published | Final report |
| Improving Data in Electronic Surveys Mojca Rožman, Andrés Christiansen, Rolf Strietholt, Jeppe Bundsgaard, Julian Fraillon, and Ronny Scherer | Published | Final report |
| To Mix or not to Mix Positively and Negatively Worded Items Isa Steinmann | Published | Final report |
| Improving Parental Occupation Procedures with AI Daniel Duckworth and Julian Fraillon | Published | Final Report |
| Operational Automatic Scoring of Text Responses in 2016 ePIRLS: Performance and Linguistic Variance Hyo Jeong Shin, Nico Andersen, Andrea Horbach, Euigyum Kim, Jisoo Baik, and Fabian Zehner | Published | Final report |
| Title and Authors | Status | Outcome |
|---|---|---|
| Using Neural Network Classification of the Automated Scoring of Images Responses in TIMSS 2023 Lale Khorramdel, Lillian Tyack, and Matthias von Davier | Published | Final report Journal article |
| Understanding Students' Computational Thinking Strategies Using Process Data in ICILS 2018 Qiwei He and Eugenio Gonzalez | Published | Final report |
| Validity and Measurement Properties in Technology-Enhanced Items: A Balancing Act Saskia Wool, Paul Drijvers, Remco Feskens, Dylan Molenaar, and Emmelien van der Scheer | Published | Part A final report Part B final report |
R&D's Call 4 is now closed. Thank you to all who submitted a research proposal. Information on this call's awarded projects can be found here.
The R&D program welcomes proposals from external researchers, regardless of their involvement in IEA studies, as well as staff and experts from study centers for IEA studies, and IEA staff. The award is based on merit only.
All proposals submitted for consideration must adhere to the following criteria:
- Proposals must be based on rigorous, ambitious, and technically sound research that is relevant to IEA ILSAs and studies.
- Projects must clearly relate to the methodology that IEA uses in one or more of its studies or relate to methods that would significantly improve IEA's work in the future.
- Submissions must propose specific approaches, innovations, and methods with tangible outcomes or recommendations that add value to IEA studies.
- Proposals may not duplicate the work that is ongoing at IEA.
For any questions regarding R&D, please contact rd@iea.nl.