NAEP Doctoral Student Internship Alumni

Diversity in background and perspective leads to valuable advances in research through collaboration. The NAEP Doctoral Internship Program welcomes a diverse pool of applicants from across the United States.

NAEP Doctoral Student Internship Applicants, by acceptance status, state, and university attended: 2017–2023.

Intern Cohorts

Check out our alumni from previous cohorts and their projects below.

Name University Program Project
Radhika Kapoor Stanford University Education Process mining for mapping response sequences: NAEP Grade 4 Math items
Muhammad Talal Khan University of Hawaii at Manoa Economics Structural Topic Modeling Using the 2019 NIES Open-Ended Teacher Responses
Danielle Siegel University of California, Davis Quantitative Psychology Comparing Plausible Value Methodology and Direct Estimation using NAEP-like Data
Jazzmine Waugh University of Washington Biology: Data Science Linking NAEP Data with External Data to Explore Student Experiences During COVID

Name University Program Project
Yusuf Canbolat Indiana University Education Policy Investigating the Relationship between Air Pollution and Education Outcomes Using NAEP and County-level Data
Juno Yingzhi Dong University of California, Los Angeles Human Development and Psychology Creating an Interactive Tool– Shedding Light on Students who Perform Below NAEP Basic
Eric Ho University of California, Los Angeles School of Education, Social Research Methodology Operation REQUISITE – Re-envisioning Educational Quantitative User Information: Shiny Interface to Explore
Jacob Maibach University of Arizona Statistics How do 8th graders navigate NAEP mathematics? Exploring students’ navigational behaviors with process data
Yichi Zhang University of Southern California Quantitative Methods and Computational Psychology Investigating Measurement Invariance in NAEP Student Questionnaire Index Items

Name University Program Project
Bhashithe (Bash) Abeysinghe Georgia State University Computer Science Equation Editor Usage: A case from 2017 NAEP Grade 8 Mathematics
Matthew Davidson University of Washington Educational Measurement and Statistics The Use of Universal Design Features by English Learners: An analysis of NAEP 2017 Mathematics Grade 4
Kelly Guinn University of Iowa Criminology and Sociology of Education Behavioral Incidents, School Behavioral Climate, and Student Level Mathematics Achievement: Exploration of NAEP and SSOCS
Elsie Lee University of Michigan School of Information/Data Visualization Re-envisioning Quantitative Data: Access to internet at home and policy initiatives for broadband internet
Tabitha Wilbur Indiana University Sociology The Relationship between Algebra Skills, NAEP Performance, and Postsecondary Outcomes
Yi Yang Columbia University Measurement, Evaluation, and Statistics Identifying Response Time Thresholds for Solution Behaviors: Exploratory Study on Proces Data in NAEP Assessment
Haobai Zhang University of Delaware Education/Learning Sciences Evaluating Effects of Text-to-Speech on NAEP Mathematics Assessment

Name University Program Project
Ayse Cobanoglu University at Buffalo Educational Psychology and Quantitative Methods How is Mathematics Growth Related to the Growth in Working Memory in Early Grades? A Parallel Latent Growth Model of ECLS-K: 2011 Data
Trenton Combs University of Miami Research, Measurement, and Education Bayesian Joint Modeling of Latent Speed and Ability
Xin Qiao University of Maryland, College Park Measurement, Statistics and Evaluation Exploring Answer Change Behavior Using NAEP Process Data
Wan Hee Kim Purdue University Literacy and Language Education Exploring Technology Inequality Among Grade 8 “Digital Natives”: Impact of the Coronavirus Pandemic and School Close on Education
Huan “Hailey” Kuang University of Florida Research and Evaluation Methodology Is Test-Disengagement the Same Across Years? Comparison of Test Disengagement Between Different Years of PISA Process Data

Archived Video

Name University Program Project
Melanie Gonzalez University of Texas at Austin Developmental Psychology Does the relationship between TEL experience and TEL achievement differ by TEL learning source?
Manqian “Mancy” Liao University of Maryland, College Park Measurement, Statistics & Evaluation Insights from students’ calculator use
Monica Morell University of Maryland, College Park Measurement, Statistics & Evaluation Exploring item visits and students’ revisit behaviors: NAEP process data
R. Noah Padgett Baylor University Educational Psychology Teacher weights study: Investigating trimming methods for state level teacher inferences
Nixi Wang University of Washington Measurement & Statistics, Educational Psychology Exploring students’ non-response behaviors with process data
Tong Wu Purdue University at West Lafayette Educational Psychology Exploring speededness in NAEP digitally based assessment
Sinan Yavuz University of Wisconsin - Madison Quantitative Methods Program, Educational Psychology A comparison study of imputation methods: Imputing school-level NSLP

Name University Program Project
Ummugul Bezirhan Teachers College, Columbia University Measurement, Evaluation and Statistics Comparing Mantel-Haenszel and Wald DIF Detection methods under Matrix Sampling of Items
Emma Cohen Indiana University Sociology STEM Course-taking, Motivation, and NAEP Grade 12 Mathematics
Juanita Hicks University of North Carolina at Greensboro Educational Research Methodology Exploring Perceived Time Pressure and Speededness Using NAEP Process Data
Glenn Hui George Mason University Statistical Science Item Profiling: A Case Study of NAEP Grade 4 Mathematics Process Data, Test Speededness in NAEP
HyunJoo Jung University of Massachusetts Amherst Research, Educational Measurement, and Psychometrics Exploration of Issues with Applying Multistage Testing in NAEP: Evaluation of MST compared to Linear Assessment
Youngjun Lee Michigan State University Measurement and Quantitative Methods Construction of an IRT-based SES index for NAEP 2003-2017
Xinyu (Crystal) Ni Teachers College, Columbia University Applied Statistics, Measurement and Evaluation Mathematics Course-taking Patterns and NAEP Performance, Test Speededness in NAEP
Youmi Suk University of Wisconsin-Madison Quantitative Methods Program, Educational Psychology Effects of the Extended Time Accommodation (ETA) on Performance in NAEP Mathematics
Seyfullah Tingir Florida State University Measurement and Statistics Examining the Relationships Between Students’ Social-Emotional Learning (SEL) Competencies and Reading Achievement through a Bayesian Network Analysis
Mingqin Zhang University of Iowa Educational Measurement and Statistics Comparison of Weighted Composite, UIRT, and MIRT Ability Estimation Approaches in Routing Decisions in Multistage NAEP Assessment

Name University Program Project
Paris Adkins-Jackson Morgan State University Psychometrics Examining the Factor Structure of an SES Proxy with 2013 NAEP Grade 12 Math Assessment
Maisaa Alahmadi Morgan State University Psychometrics A Closer Look at National Gender Gaps in Reading, Mathematics, and Science Achievement
Tanesia Beverly University of Connecticut Measurement, Evaluation & Assessment Identifying Test-taking Behaviors Using Growth Mixture Models
Kendra DeLaine Howard University Educational Psychology NCES College Preparedness Project, LTT Framework Comparison Project
Andrew Iverson Washington State University Educational Psychology Language Minority Status, Reading Development, and Summer Reading Achievement Loss
Eva (Yujia) Li University of Connecticut, Storrs Educational Measurement, Evaluation and Assessment Reading Growth and Summer Loss: Helping Those Potentially at-Risk, Relationship between Teaching Strategy and Early Reading Growth: A Nationally Representative Sample
Bradlee Sutherland The Catholic University of America Applied Experimental Psychology Exploring Access to Digital Technologies at home and in school for Students in Grades 4, 8, and 12 by Selected Student Characteristics
Xiaying (James) Zheng University of Maryland College Park Measurement, Statistics, and Evaluation The Impact of Missing Contextual Questionnaire Data on Group Level Ability Estimation, A comparison of pairwise cumulative linking and concurrent calibration linking using NAEP data
Jinwang Zou University of Maryland College Park Measurement, Statistics, and Evaluation Reading motivation and achievement gap: Evidence from NAEP
title of plugged in news

EdSurvey 4.0.7 Released!

08-09-2024

Check out news about the latest release from the EdSurvey team here. And remember you can always access their e-book here.