NAEP Doctoral Student Internship Alumni

From Internship to Impact

The NAEP Doctoral Student Internship Program recognizes diversity in background and perspective as essential to fostering groundbreaking research and innovation. The program has grown over the years, embracing diverse talent from universities and doctoral programs across the United States representing academic disciplines including educational measurement and statistics, economics, data science, computer science, data visualization, psychology, education policy, sociology, and more.

The program’s acceptance rate remains competitive, with only a few positions available each year; however, candidates who align with the program’s commitment and dedication to excellence are encouraged to apply.

Alumni Across the Nation

The following interactive map highlights the origins of NAEP Doctoral Student Internship Program applicants and the esteemed institutions internship these alumni represent. Discover the breadth of the internship community and where program alumni have come from.

NAEP interns have been selected from a talented pool of candidates applying from across the nation.

Want to see your university on the map? Apply for the internship program and join us in driving innovation in education research!

Unlocking Potential in a Collaborative Environment

This doctoral-level internship program is designed to provide an enriching and comprehensive experience for advanced students. Interns engage in substantial research opportunities, applying their expertise to real-world challenges facing education and large-scale assessment.

The collaborative environment fostered in the program allows interns to network and connect not only with each other, but also with leaders in NAEP research and within their areas of interest. Interns are given access to experienced mentors who provide valuable feedback and career guidance, ensuring professional growth. Throughout the summer, interns are offered opportunities and training sessions to introduce them to NAEP and enhance their methodologies and professional practices.

The virtual program offers flexible scheduling and a supportive environment to pave the way for future career advancement. Many interns go on to publish their findings and present at research conferences following their participation in the program.

Internship Highlights

Scroll through the alumni photo album, which showcases highlights from recent internship activities, and read what some internship alumni have had to say about their experience.

Next Generation Innovators

Interns will dive into challenging projects that are designed to tackle real-world issues and require them to apply their skills and creativity in dynamic ways. These experiences not only enhance their technical expertise but also foster resilience and teamwork, preparing them for future success in their careers.

In a recent survey of alumni, 100% strongly agreed or agreed that the skills they developed and utilized during their internship are used frequently in their current roles.

Hear from Recent Alumni

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Intern Cohorts

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

2024 Cohort

Name	University	Program	Project
Naomi Duran	University of Illinois Urbana Champaign	Human Development & Family Studies	Projected and Actualized Post-COVID Public School Enrollments
Paulina Grekov	University of Wisconsin - Madison	Quantitative Methods	Mathematics learning environments and the coronavirus pandemic: Relationship across locale and key equity indicators
Adalin Ni	Vanderbilt University	Computer Science	Analyzing Response Changes in Constructed Response Items In NAEP Mathematics Grade 8 2022 Process Data
Saugat Pandey	Washington University	Computer Science	Exploring Equity in the Collection and Reporting of Data
Maggie Perkoff	University of Colorado Boulder	Computer Science + Cognitive Science	Can Large Language Models Transform Automated Scoring?: A Case Study with NAEP Mathematics Constructed Response Items
Dekyi Suolang	University of Michigan - Ann Arbor	Survey and Data Science	Handling Missing Contextual Data in Large-Scale Assessments: The Multiple Imputation Strategy
Winnie Wilberforce	Ohio State University	Quantitative Research, Evaluation and Measurement	Estimating Differential Course Difficulty in High School Mathematics Courses using NAEP as a Common Benchmark

2023 Cohort

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

2022 Cohort

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

2021 Cohort

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

2020 Cohort

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

2019 Cohort

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

2018 Cohort

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

2017 Cohort

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

Where Are They Now?

As a NAEP Doctoral Student Intern, you are part of the NAEP R&D community, which stays connected. Internship alumni have gone on to work in a variety of settings. Within the public sector, alumni are working at universities including Yale, Harvard, Columbia, and Boston College, or with state, federal, and international government agencies. Alumni have also gone on to work in the private and nonprofit sectors with companies including Apple, Google, Zillow, and Duolingo, as well as various research and professional organizations.