Ting Zhang

Senior Researcher

Ting Zhang is a senior research scientist/psychometrician at AIR. Dr. Zhang currently serves as project director of the NCES Data R Project, in which she leads a team of statisticians and data scientists developing a statistical R package tailored for analysis of NCES national and international large-scale data including NAEP, TIMSS, and PISA. She has been the principal investigator of two other research projects that study validity issues pertaining to technology-based assessments. She also has provided the NCES and the NAEP Validity Studies panel the technical assistance they require to support NAEP data analyses and methodological research. She has been responsible for quality control review of NAEP reports, data files, and technical documentation.

Dr. Zhang received her Ph.D from University of Maryland – College Park in Human Development and Quantitative Methods. She obtained an AERA-NSF Dissertation Grant and an AERA SIG Outstanding Dissertation Award for her research on the role of reading comprehension in large-scale educational assessments. Her research interests focus on complex survey design and measurement validity.

Expertise
Education
International Comparisons in Education
National Assessment of Educational Progress (NAEP)

Ph.D., Human Development and Quantitative Methods, University of Maryland – College Park

Contact Ting Zhang

+1.202.403.5000
Related Work

Effects of Visual Representations and Associated Interactive Features on Student Performance on National Assessment of Educational Progress (NAEP) Pilot Science Scenario-Based Tasks

02 Apr 2020
As part of the transition to an entirely digitally based assessment (DBA), new types of NAEP items have begun to be developed that leverage the DBA environment to measure a wider range of knowledge and skills, including science scenario-based tasks that are the focus of this report.
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Weighted and Unweighted Correlation Methods for Large-Scale Educational Assessment: wCorr Formulas

12 Apr 2018
This report introduces the methodology used by the wCorr R package for computing the Pearson, Spearman, polyserial, polyserial, polychoric and tetrachoric correlations, with and without weights applied. Simulation evidence is presented to show correctness of the methods, including an examination of the bias and consistency. ...
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Analyses Using Achievement Levels Based on Plausible Values

24 Apr 2017
Achievement levels are important yardsticks in the National Assessment of Educational Progress (NAEP) program. In this document, we provide a detailed description of the plausible value method and demonstrate the method by replicating the analyses using SAS and comparing the replicated analysis results with those produced with NAEP Data Explorer. ...

NCES Data R Project - EdSurvey

The released EdSurvey Version 3.1 is an R statistical package tailored to processing large-scale education data with appropriate procedures to analyze these data efficiently, taking into account their complex sample survey design and the use of plausible values.
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Computer Familiarity and Its Relationship to Performance in Three NAEP Digital-Based Assessments

29 Jan 2016
Because NAEP is transitioning its paper-and-pencil assessments to a digital format, it is important to understand the relationship between students' familiarity with computers and their performance. This study, which analyzed three of NAEP's early digital-based assessments, found that home computer access was positively related to student performance. ...