R&D Outcomes

The study aimed to validate the quality of assessment items generated by Large Language Models for use in TIMSS fourth grade mathematics and science assessment. This publication includes the report, psychometric analysis supplement, and five annex documents. The IEA Research and Development call three has supported the research for this publication.

This publication is part of the IEA Research and Development Fund call three and aims to answer the question are linear paper-based and nonlinear computer-based reading comprehension measuring the same cognitive constructs?

The primary objective of this study is to examine the performance of the most widely used sampling variance estimators in international large-scale assessments (ILSAs): the Balanced Repeated Replication (BRR) method and the Jackknife Repeated Replication (JK2) method (both Half and Full variants). This publication is an outcome from the IEA Research and Development fund call three.

Awarded project from IEA's Research and Development Call 3, this study was designed to inform item-writing guidelines for educational tests that assess students’ current achievement or learning progress on school curriculum objectives.

Computer-based assessments collect process data to give insights into testees' response behaviors, strategies, and motivations. This project, supported by the IEA Research and Development Fund, assesses areas that help researchers enhance their understanding of student motivation and how they interact with tasks in large-scale assessments.

This paper uses teacher data from 28 educational systems participating in the ICILS 2023 field trial to investigate the differences between question formats.

Using data from ICILS 2013 and 2018, this research leverages technology to address educational and occupational research challenges, promoting greater inclusivity and precision in international studies.

This project reports on the feasibility of automatic scoring systems for text responses from the 2016 ePIRLS assessment.

Developing questionnaires for international large-scale assessments can be challenging. This white paper addresses questionnaire development for educational assessment projects and the language used in its items.

An outcome from the first R&D call, this report addresses the question how to evaluate the validity of results of international large-scale assessment programs (ILSAs) that incorporate technology-enhanced items, paying special attention for the comparability of results between countries.

This report informs and provides recommendations on technical standards and reporting in international large-scale assessments.

Using data from ICILS 2018, this report focuses on the nine countries and regions assigned to the computation thinking model to better understand missing responses.

The first outcome from the IEA R&D fund call two. This report discusses the construction of scaling models for large-scale assessments in education, applying methods to PIRLS 2016 data.

The first output from IEA's R&D call one, this report assesses how to validate human rater scores for graphical responses using AI.