Fusun Sahin is a researcher at AIR. Dr. Sahin has been contributing to the National Assessment of Educational Progress (NAEP) work in assessment operations, research, and reporting teams. She contributes to the NAEP project with her expertise in process data (i.e., log data that include record of examinees’ interactions within the digitally based assessments), where she investigates data quality, different ways to benefit from process data for operational decisions, and various research projects on response time and response behaviors of examinees. In her current role, Dr. Sahin also involves in research on the digitally based NAEP assessment especially for using process data to inform operational decisions such as design of the items, features, and system tools. She also examines the content and structure of the process data files and evaluates their usefulness for informing about valuable student actions. In addition, she leads various research activities using process data. She presented research in various conferences on topics including examinees’ testing behaviors and modeling response time.
Alongside her expertise in process data, Dr. Sahin contributes to the NAEP project with her experience in operational testing and psychometrics. She participates in reviewing deliverables for various operational stages of the NAEP assessment including assembly, administration, and reporting of the NAEP assessment. In addition, she reviews psychometric qualities of the assessments as well as various NAEP score and survey data files, technical reports, and white papers.
Dr. Sahin has extensive expertise in process data, psychometrics, and statistical analysis in the context of large-scale assessments. Her experiences prior to joining AIR include working with the log data files from the computer-based Programme for International Students Assessment (PISA), working with a high-stakes medical certification program, and various high-stakes assessments administered at the state and district levels. Dr. Sahin’s statistical experience include finite mixture modeling, structural equation modeling, hierarchical linear modeling, propensity score analysis, and regression models. Dr. Sahin has also authored three book chapters on using mobile phones for assessment.