Shudong Wang, PhD
Senior Psychometrician

Shudong Wang focuses on product design and development, including psychometric development of MAP Reading Fluency and MAP Growth Spanish Reading. His research interests include adaptive testing and generalized linear mixed-model applications in educational measurement and psychometric research. Dr. Wang has published over 20 peer-reviewed journal articles and book chapters. He has presented at numerous conferences, including NCME, AERA, and CCSSO, on topics such as CAT item selection and quality of student scoring, effects of CAT designs on content coverage and efficiency, and accuracy of student ability estimations. Prior to joining NWEA in 2009, he was a senior psychometrician at ETS. Dr. Wang holds a PhD in educational research methodology from the University of Pittsburgh.
Publications by Shudong Wang


Spanish MAP Growth Reading technical report
This technical report documents the processes and procedures employed by NWEA to build and support the Spanish MAP Growth Reading assessment.
By: Shudong Wang, Patrick Meyer, Carmen Hall, Teresa Krastel, Adam Withycombe
Products: MAP Growth, MAP Spanish
Topics: Assessments in Spanish, Computer adaptive testing, Test design


Calibration of Spanish MAP Growth Math tests
The calibration study was conducted to investigate the consequences of replacing the English MAP Growth Mathematics item parameters with the Spanish mathematics item parameters.
By: Shudong Wang, Xueming (Sylvia) Li
Products: MAP Growth, MAP Spanish


The major purpose of this paper is to investigate the effects of CAT test design and bank distribution on the content coverage and the efficiency of the tests.
By: Shudong Wang, Hong Jiao
Topics: Computer adaptive testing, Learning standards & alignment, Test design


This study, using real data, provides empirical evidence of construct and invariance construct of MAP scales across grades at different academic calendars for 10 different states.
By: Shudong Wang, Marth S. McCall, Hong Jiao, Gregg Harris
Topics: Measurement & scaling, Test design


The current investigative study uses a multiple-indicator, latent-growth modelling (MLGM) approach to examine the longitudinal achievement construct and its invariance for MAP Growth.
By: Shudong Wang, Hong Jiao, Liru Zhang
Topics: Growth modeling, Measurement & scaling


These studies are conducted based on assumptions under regular conditions for fixed test forms, such as no missing responses and normal distribution of unidimensional ability for a population.
By: Shudong Wang, Hong Jiao
Topics: Computer adaptive testing, Item response theory, Measurement & scaling


Examine construct validity of computerized adaptive test in K–12 assessments
The purpose of this study is to investigate the effect of missing data in computerized adaptive tests (CAT) on test construct validity.
By: Shudong Wang, Hong Jiao
Topics: Computer adaptive testing