Ann Hu, PhD
Director of Psychometrics and Analytics
Ann Hu works mainly on MAP Growth assessments. Her research interests include linking studies between formative and summative assessments, item bank development and maintenance, adaptive testing engines, test security, and norms studies. She has extensive experience in conducting psychometric analyses and research based on Rasch models and IRT, constructing fixed forms and CATs, and designing and conducting standard settings. Prior to joining NWEA in 2017, Dr. Hu worked at Data Recognition Corporation (DRC) on multiple large-scale achievement testing programs for Pennsylvania, Michigan, Oklahoma, Louisiana, Alabama, and Minnesota. Dr. Hu holds a doctorate in measurement, evaluation, and cognition from the University of Alberta. She also holds a bachelor’s degree in psychology and a MEd in educational psychology.
Publications by Ann Hu
This technical report is written to help measurement professionals and administrators evaluate the quality of the MAP Growth assessments.
Products: MAP Growth
Topics: Measurement & scaling, Item response theory, Test design
MAP Growth Spanish Technical Report- Addendum
This technical addendum report is written to help measurement professionals and administrators evaluate the quality of the MAP Growth’s Spanish assessments.
Products: MAP Growth, MAP Spanish
Topics: Equity, Item response theory, Measurement & scaling, Test design
Predicting Amira Reading Mastery Based on NWEA MAP Reading Fluency Benchmark Assessment Scores
This document presents results from a linking study conducted by NWEA in May 2024 to statistically connect the grades 1–5 English Amira Reading Mastery (ARM) scores with the Scaled-Words-Correct-Per-Minute (SWCPM) scores from the MAP Reading Fluency benchmark assessment taken during Fall and Winter 2023–2024.
Products: MAP Reading Fluency
Topics: Computer adaptive testing, Early learning, Measurement & scaling, Reading & language arts
Executive Summary: Content proximity spring 2022 pilot study
This executive summary outlines results from the Content Proximity spring 2022 pilot study, including information on the validity, reliability, and test score comparability of MAP Growth assessments that leverage this new item-selection algorithm.
Products: MAP Growth
Topics: Computer adaptive testing, Innovations in reporting & assessment, Test design
Content Proximity Spring 2022 Pilot Study Research Report
The purpose of this research report is to provide detailed information about updates to the MAP Growth item-selection algorithm. This brief includes results from the Content Proximity pilot study, including information on the validity, reliability, and test score comparability of MAP Growth assessments that leverage this new item-selection algorithm.
Products: MAP Growth
Topics: Computer adaptive testing, Innovations in reporting & assessment, Test design
MAP Growth linking studies: Intended uses, methodology, and recent studies
This document presents the intended uses and methodology of the MAP Growth linking studies, a description of the results provided in the linking study reports, and a summary of the recent linking studies conducted by NWEA to incorporate the new 2020 norms.
Products: MAP Growth
This report presents the results of a mode comparability study conducted through simulations to evaluate how scores from MAP Growth administered on the constraint-based engine (CBE) compare to those administered on the current MAP Growth engine known as COLO.
Products: MAP Growth
Topics: Measurement & scaling, Test design
