Center for Advancing Human Competencies

{"id":"image-grid-8512899","imageGridModuleTitle":"Meet our team","loadMoreBtnText":"Read More","contentViewer":"slide","textAlign":"left","readMoreLabel":"Read more","readLessLabel":"Read less","enableFullDescription":false,"imageGridModuleTheme":"ets-light","imageType":"image","mobileNoSlider":false,"noOfGrids":"three","enableLoop":false,"displayFullBorder":"false","contentCtas":[],"ctas":[{"ctaLabel":"Contact us","ctaLabelAccessible":"Contact us","ctaLink":"#target-signup","ctaTarget":true,"ctaType":"secondary-cta","enableGatedContent":false,"ctaArrow":false,"enableIcon":false}],"imageGridCards":[{"imageGridCardEyebrow":"ASSOCIATE VICE PRESIDENT","imageGridCardDescription":"\u003ch3\u003eLydia Liu\u003c/h3\u003e\r\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/research/lydia-liu-headshot.jpg","imageGridCardImageAlt":"Lydia Liu","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eDr. Liu\u003c/b\u003e is a globally recognized expert in the research and assessment of critical skills in education and the workforce. Her research develops both conceptual foundations and empirical applications for how critical skills are defined, assessed, and validated across educational and workforce contexts. Dr. Liu has authored or coauthored more than 110 peer‑reviewed journal articles, research reports, and book chapters in applied measurement, skills assessment, higher education, and science assessment. Her work has appeared in leading journals including Science, Nature Human Behavior, Educational Researcher, and Proceedings of the National Academy of Sciences. She has delivered over 130 invited seminars and peer‑reviewed conference presentations nationally and internationally. In recognition of her scholarly contributions, Dr. Liu was inducted as a Fellow of the American Educational Research Association (AERA) in 2023. She also received the 2019 Robert Linn Memorial Lecture Award and the 2011 National Council on Measurement in Education (NCME) Jason Millman Promising Measurement Scholar Award for her contributions to learning outcomes assessment in higher education and K–12 science assessment.\u003c/p\u003e\r\n\u003cp\u003eDr. Liu has managed federal and non‑federal grants and overseen more than $35 million in multi‑year projects funded by NSF, IES, World Bank, Gates Foundation, Overdeck Foundation, and other U.S. domestic as well as international agencies. She serves as a board member of ETS China and the Mastery Transcript Consortium. At ETS, Dr. Liu leads research support for K–16 education, workforce, and language assessment products and services, and drives social impact initiatives that connect measurement science with field‑based applications.\u003c/p\u003e\r\n\u003cp\u003eDr. Liu holds a bachelor’s degree in Science and English from the University of Science and Technology of China and a doctorate in Quantitative Methods and Evaluation from the University of California, Berkeley.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/loliu/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"DISTINGUISHED PRESIDENTIAL APPOINTEE","imageGridCardDescription":"\u003ch3\u003ePatrick Kyllonen\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/research/pat-k.jpg","imageGridCardImageAlt":"Patrick Kyllonen","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003ePatrick Kyllonen\u003c/b\u003e is Distinguished Presidential Appointee in the ETS Research Institute in Princeton, NJ. He received his Ph.D. from Stanford University, and authored Generating Items for Cognitive Tests (with S. Irvine, 2001); Learning and Individual Differences (with P. Ackerman \u0026amp; R. Roberts, 1999); Extending Intelligence: Enhancement and New Constructs (with R. Roberts and L. Stankov, 2008), and Innovative Assessment of Collaboration (with A. von Davier and M. Zhu, 2017), and over 100 journal articles and chapters. He coauthored four National Academy of Sciences reports, Education for Life and Work (2012), Measuring Human Capabilities (2014), Supporting Students’ College Success (2017), and Adult Learning in the Military Context (2024). He is an APA and AERA fellow, is serving on the editorial boards of several journals, including Intelligence: A Multidisciplinary Journal, where he is currently Guest Editor of a special issue, Models and Tools for Measuring and Understanding Intelligence in the Age of AI. He has recently published several papers on the use of AI in problem solving and evaluation of AI capabilities (e.g., General Scales Unlock AI Evaluation with Explanatory and Predictive Power [Nature]) and contributes to OECD’s AI and the Future of Skills initiative.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/patrick-kyllonen-4b53112/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"RESEARCH DIRECTOR ","imageGridCardDescription":"\u003ch3\u003eLei Liu\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/research/lei-liu.jpg","imageGridCardImageAlt":"Lei Liu","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eDr. Lei Liu\u003c/b\u003e is a leading scholar in K–12 STEM assessment, future-ready skills, and technology-enhanced educational innovation. Her work advances how complex competencies and durable skills are defined, developed, assessed, and validated, with expertise in scientific and mathematical reasoning, evidence-based argumentation, collaboration, communication, AI literacy, digital literacy, learning progressions, performance-based assessment, and AI-supported feedback.\u003c/p\u003e\r\n\u003cp\u003eAt ETS, Dr. Liu brings together learning sciences, educational measurement, and emerging technologies to generate authentic, actionable evidence of student learning. She has shaped innovative approaches to NGSS-aligned performance tasks, simulation-based assessments, virtual science labs, collaborative problem-solving assessments, conversation-based assessment, and automated scoring. Across these efforts, she demonstrates how meaningful STEM tasks can make students’ reasoning, collaboration, and communication visible while connecting disciplinary learning with durable skills.\u003c/p\u003e\r\n\u003cp\u003eDr. Liu has led and contributed to a substantial portfolio of externally funded research supported by federal agencies, philanthropic foundations, and international education agencies, including IES, NSF, NCES, the Gates Foundation, the Overdeck Family Foundation, and the Shanghai Municipal Educational Examinations Authority. Across this portfolio, she has helped build research-based assessment models, technology-enhanced tools, and validity evidence that inform classroom practice, large-scale assessment, and emerging skills initiatives.\u003c/p\u003e\r\n\u003cp\u003eDr. Liu has authored and coauthored more than 90 peer-reviewed publications across educational measurement, learning sciences, science education, skills assessment, AI in education, and educational technology. Her scholarly contributions were recognized with the NARST Doctoral Research Award the Evelyn Headley Award for Outstanding Dissertation. She earned her Ph.D. in Educational Psychology from Rutgers University and serves as an Adjunct Full Professor at the University of Pennsylvania.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/lei-liu-5b085014/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"RESEARCH DIRECTOR","imageGridCardDescription":"\u003ch3\u003eGuangming Ling\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/g-ling.jpg","imageGridCardImageAlt":"Guangming Ling","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eGuangming Ling\u003c/b\u003e is a research director in the area of higher education and workforce at ETS. His research focuses on assessment and training of durable skills; student learning outcomes assessments; and factors related to validity, reliability, and fairness issues in educational selections, covering a wide range of topics such as test mode effects, subscore reporting, test-taking motivation, computerized adaptive testing, and human- and machine-scoring of essay and speech responses.\u003c/p\u003e\r\n\u003cp\u003eDr. Ling has directed research projects related to a wide range of testing programs, including the GRE® test, the ETS® Major Field Tests, the HEIghten® outcomes assessment, the SAT® test, the TOEFL iBT®\u0026nbsp; test, and the Programme for Assessment of Readiness for College and Careers. In addition, he has been a key contributor to multiple projects funded by the Institute for Education and the fast-forward team, Skills for a New Economy. He holds a U.S. patent on technology that uses an automated scoring system to improve the accuracy and efficiency of scoring English-speaking responses.\u003c/p\u003e\r\n\u003cp\u003eDr. Ling has made more than 110 presentations at international and national conferences, including the International Meeting of the Psychometric Society, International Testing Commission, and American Educational Research Association. He has published more than 50 papers in peer-reviewed journals, including Nature, Human Behavior, Proceedings of the National Academy of Sciences, Exceptional Children, Child Development, Educational Assessment, Assessing Writing, and International Journal of Testing. He holds a Ph.D. in psychometrics (quantitative psychology) from Fordham University.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/guangming-bright-ling-07024830/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"RESEARCH ASSOCIATE","imageGridCardDescription":"\u003ch3\u003eAmy Adair Midyett\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/amy-midyett.jpg","imageGridCardImageAlt":"Amy Adair Midyett","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eDr. Amy Adair Midyett\u003c/b\u003e is a Research Associate at the ETS Research Institute, where she uses learning science principles and AI techniques to design, develop, and evaluate tools for STEM teaching, learning, and assessment. Her recent work has focused on developing AI-supported assessments of student reasoning and collaboration, including tools that engage students in working with AI agents on STEM tasks.\u003c/p\u003e\r\n\u003cp\u003eWhether designing performance assessments grounded in evidence-centered design, building automated scoring models, or evaluating the efficacy of AI systems, Amy is committed to bridging research and practice to create meaningful and effective educational tools for students and teachers.\u003c/p\u003e\r\n\u003cp\u003eA former high school math and robotics teacher, Amy holds a B.A. in Mathematics from Louisiana State University and an M.A. and Ph.D. in Education, with a concentration in Learning Sciences, from Rutgers University, where she was a National Science Foundation Graduate Research Fellow.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca href\u003d\"https://www.linkedin.com/in/amy-adair/\"\u003eLikendIn profile\u003c/a\u003e\u003c/p\u003e\r\n\u003cp\u003eGoogle Scholar: \u003ca rel\u003d\"noopener noreferrer\" href\u003d\"https://scholar.google.com/citations?user\u003dyLRBn_4AAAAJ\u0026amp;hl\u003den\u0026amp;oi\u003dao\" target\u003d\"_blank\"\u003ehttps://scholar.google.com/citations?user\u003dyLRBn_4AAAAJ\u0026amp;hl\u003den\u0026amp;oi\u003dao\u003c/a\u003e\u003c/p\u003e\r\n\u003cp\u003eResearch Gate: \u003ca rel\u003d\"noopener noreferrer\" href\u003d\"https://www.researchgate.net/profile/Amy-Adair-6\" target\u003d\"_blank\"\u003ehttps://www.researchgate.net/profile/Amy-Adair-6\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"ASSOCIATE MEASUREMENT SCIENTIST","imageGridCardDescription":"\u003ch3\u003eDiego Figueiras\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/diego-f.jpg","imageGridCardImageAlt":"Diego Figueiras","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eDiego Figueiras\u003c/b\u003e is an Associate Measurement Scientist in the ETS Research Institute. He joined ETS in 2024 after completing his Ph.D. in Industrial/Organizational Psychology at Montclair State University. He also holds a bachelor’s degree in Psychology from Rutgers University.\u003c/p\u003e\r\n\u003cp\u003eHis research integrates psychometrics, machine learning, and artificial intelligence to improve the measurement of skills, personality, and workplace outcomes. At ETS, he has contributed to the validation and optimization of the PSQ and GRE, including research on long-term GRE predictive validity using Google Scholar indicators of scholarly productivity and meta-analytic studies of graduate-school success. He has developed psychometric methods for shortening personality inventories, investigated response-faking resistance in personality assessment, and evaluated the validity of synthetic data for assessment research.\u003c/p\u003e\r\n\u003cp\u003eHis recent work focuses on AI-enabled assessment, including the use of generative AI for assessment development, automated scoring of open-ended workplace responses, and the measurement of AI literacy. Across his projects, he examines issues of reliability, validity, fairness, and practical utility in educational and workforce settings. He has presented his research at national conferences and collaborates on initiatives related to workforce skills, durable skills, and technology-enhanced assessment.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/diego-figueiras-ph-d-012644123/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"SENIOR RESEARCH SCIENTIST","imageGridCardDescription":"\u003ch3\u003eLin Gu\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/lingu.jpg","imageGridCardImageAlt":"Lin Gu","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eDr. Lin Gu\u003c/b\u003e is a senior research scientist at the Research Institute of Educational Testing Service (ETS), a global education and talent solutions organization based in the U.S.\u0026nbsp; She received her Ph.D. in Second Language Acquisition from the University of Iowa.\u003c/p\u003e\r\n\u003cp\u003eBroadly trained in language pedagogy, language testing, and educational measurement, she focuses her research on advancing scientific knowledge of language teaching, learning, and assessment in the digital era. Her work has led to AI-augmented educational solutions that are well grounded in learning principles and measurement theories and have provided support to operational testing and learning programs, including language proficiency tests, student learning outcomes assessment, graduate school admissions tests, and teacher professional development programs. Most recently, the scope of her research expanded to include transferrable and durable skills. Related to skills assessment, she led and contributed to conceptual framing, assessment prototyping, and scoring of multiple skills, including communication, collaboration, and research inquiry skills.\u003c/p\u003e\r\n\u003cp\u003eDr. Gu has published and presented widely in language learning, assessment, and higher education. Her most recent publications include topics such as automated feedback on speaking assessment, AI-powered language learning, and assessment.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/lin-gu-05860618/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"RESEARCH ASSOCIATE","imageGridCardDescription":"\u003ch3\u003eZach Hesson\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/zach-hesson.jpg","imageGridCardImageAlt":"Zach Hesson","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eZach Hesson\u003c/b\u003e is a Research Associate in the area of higher education and workforce, ETS Research Institute. He earned his Ph.D. in Industrial/Organizational Psychology from the Florida Institute of Technology and joined ETS shortly after defending his dissertation in 2026. His dissertation examined decent work, job insecurity, employee experiences, and performance, with a particular focus on promoting healthy and sustainable work environments. Zach has co-authored a book chapter on cross-cultural work psychology and has contributed to the development of a comprehensive measure of self-regulatory demands. His work is driven by a passion for understanding how changes in working conditions affect employees\u0027 experiences, well-being, and perceptions of job continuity. At ETS, Zach is contributing to multiple projects, such as investigating the validity evidence for GRE associated with long-term outcomes in the workforce (e.g., through Google Scholar index), as well as evaluating the measurement properties and validity of skills assessment in the higher education space.\u0026nbsp;\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/zacharyhesson/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"SENIOR MEASUREMENT SCIENTIST","imageGridCardDescription":"\u003ch3\u003eChing-Ni Hsieh\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/ching-ni-hsieh-gray.jpg","imageGridCardImageAlt":"Ching-Ni Hsieh","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eChing-Ni Hsieh\u003c/b\u003e is a Senior Measurement Scientist at ETS whose work focuses on advancing the design, validation, and interpretation of language and skills assessments. Trained in second language studies, she has led and contributed to research on young learner assessment, TOEFL and TOEIC validation research, assessing speaking and writing skills, automated speech feedback and scoring, and technology-assisted language learning and assessment. Her scholarly work includes articles in leading journals such as TESOL Quarterly, Language Testing, and Language Assessment Quarterly, book chapters, and research reports. She has delivered keynote speeches, conference presentations, seminar talks, teacher-training workshops, and webinars for audiences across Asia, Europe, North America, South America, and online. Dr. Hsieh is currently ETS’s leading scientist for the OECD PISA Vocational Education and Training (PISA-VET) initiative, an international effort to measure occupation-specific and employability skills in vocational education. Her PISA-VET work focuses on designing defensible performance-based assessments that support authentic, comparable, and policy-relevant evidence about learners’ skills.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/ching-ni-hsieh-38a80820/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"RESEARCH ASSOCIATE","imageGridCardDescription":"\u003ch3\u003eEuvelisse (Nicole) Jusino del Valle\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/research/nicole.jpg","imageGridCardImageAlt":"Euvelisse (Nicole) Jusino del Valle","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eEuvelisse Jusino del Valle\u003c/b\u003e is a research and program professional with experience supporting education research, AI-enabled product development, grant operations, fiscal governance, and cross-functional project coordination. In her role as a Research Associate at ETS, she supports a complex portfolio spanning commercial contracts, philanthropic grants, and federal programs, contributing to budget monitoring, workflow optimization, project administration, and stakeholder-facing deliverables.\u003c/p\u003e\r\n\u003cp\u003eHer work includes supporting research and operational activities for initiatives involving conversational AI, workforce readiness, assessment, and international education projects. She has contributed to the development of interactive educational AI chatbot work, including conversational flow and prompt framework design.\u003c/p\u003e\r\n\u003cp\u003eJusino del Valle has facilitated international focus groups for the OECD-supported PISA-VET project, provided Spanish translation and cultural localization for the Colombian cohort, and helped develop accessible multimedia materials.\u003c/p\u003e\r\n\u003cp\u003eBefore joining ETS, she held roles in career coaching, biotechnology operations, nonprofit program management, adult education, and K–12 science instruction, building a multidisciplinary foundation across education, compliance, workforce readiness, and project leadership.\u003c/p\u003e\r\n\u003cp\u003eJusino del Valle holds an MBA in Project Management, a BS in Biotechnology, and a BA in Chemistry Education. She also earned a Distance Learning Certification and is a coauthor of a 2025 publication in Education Sciences on designing an AI chatbot to support scientific argumentation.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/euvelisse-jusino-del-valle-681874395/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"RESEARCH SCIENTIST","imageGridCardDescription":"\u003ch3\u003eTeresa M. Ober\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/research/t-ober.jpg","imageGridCardImageAlt":"Teresa M. Ober","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eTeresa M. Ober\u003c/b\u003e, Ph.D., is a Research Scientist in the ETS Research Institute whose work focuses on defining and measuring the human capabilities that matter in an AI-shaped world. Her research integrates educational psychology, psychometrics, learning sciences, and AI-enabled methods to examine how individuals develop and demonstrate capabilities across educational and workforce contexts.\u003c/p\u003e\r\n\u003cp\u003eA central theme throughout Dr. Ober\u0027s career has been understanding how people learn and adapt in technology-mediated environments. Her prior research examined engagement, motivation, cognitive load, and self-regulation in digital learning systems, educational games, and assessment environments. Using process data and behavioral indicators, this work explored how learners engage with challenging tasks and evaluate their performance, leading to a broader interest in competencies that support success across dynamic educational and professional contexts. This work has been published in outlets such as Computers \u0026amp; Education, Journal of Computer Assisted Learning, AERA Open, and Journal of Psychoeducational Assessment.\u003c/p\u003e\r\n\u003cp\u003eBuilding on this foundation, Dr. Ober\u0027s more recent work has expanded to competency-based education and future-ready skills. She has developed conceptual frameworks and validity arguments for communication, digital literacy, AI literacy, collaboration, culturally responsive personalized learning, and AI competencies for teaching. This research focuses on defining important competencies and identifying the evidence needed to support defensible claims about their growth and application. This work has appeared in Teachers and Teaching: Theory and Practice, Competency-Based Education Research Journal, and\u0026nbsp; Practical Assessment, Research, and Evaluation.\u003c/p\u003e\r\n\u003cp\u003eHer current research extends this work to the challenges of learning and working with AI. She has examined how established capabilities, such as adaptability and communication, and emerging capabilities, such as AI literacy, shift as AI becomes embedded in learning and work. Her work contributes to evidence models, frameworks, and assessment approaches that help distinguish which capabilities are enduring, which are evolving, and what constitutes trustworthy evidence of competency in human-AI environments. She has also applied AI-enabled research and measurement approaches, including large language models, topic modeling, qualitative analysis workflows, and process-data methods. Recent studies using these approaches have been published in the Journal of Educational Data Mining, with related work appearing in proceedings of the International Conference on Artificial Intelligence in Education and the International Workshop on AI Literacy Education for All.\u003c/p\u003e\r\n\u003cp\u003eBefore joining ETS, Dr. Ober was an Assistant Research Professor and Postdoctoral Research Associate in the Department of Psychology at the University of Notre Dame, where she contributed to externally funded research on educational assessment, learner experiences, adaptation to change, and equity in educational settings. She served as a Co-I on NSF- and IES-funded projects and as Co-PI on Spencer Foundation-funded work. Dr. Ober earned a Ph.D. in Educational Psychology from the Graduate Center of the City University of New York, an M.A. in Cognitive Studies in Education from Teachers College, Columbia University, and a B.A. in Psychology from Cornell University.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/teresaober/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n\u003cp\u003eGoogleScholar: \u003ca rel\u003d\"noopener noreferrer\" href\u003d\"https://scholar.google.com/citations?user\u003dbVEYUnMAAAAJ\u0026amp;hl\" target\u003d\"_blank\"\u003ehttps://scholar.google.com/citations?user\u003dbVEYUnMAAAAJ\u0026amp;hl\u003c/a\u003e\u003c/p\u003e\r\n\u003cp\u003eResearch Gate: \u003ca rel\u003d\"noopener noreferrer\" href\u003d\"https://www.researchgate.net/profile/Teresa-Ober\" target\u003d\"_blank\"\u003ehttps://www.researchgate.net/profile/Teresa-Ober\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"ASSOCIATE RESEARCH SCIENTIST","imageGridCardDescription":"\u003ch3\u003eTim Oxendahl\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/t-oxendahl.jpg","imageGridCardImageAlt":"Tim Oxendahl","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eDr. Oxendahl\u003c/b\u003e is an Associate Research Scientist at ETS whose work focuses on the development and assessment of critical skills in educational settings. His research interests include human–AI collaboration, technology-enhanced assessment, and the application of data-driven methods to understand learning and performance.\u003c/p\u003e\r\n\u003cp\u003eAt ETS, Dr. Oxendahl contributes to research initiatives focused on collaboration, communication, and other durable skills needed for success in school, work, and civic life. His research and professional experience span the intersection of technology and human performance, with a focus on translating scientific evidence into practical solutions for real-world contexts.\u003c/p\u003e\r\n\u003cp\u003ePrior to joining ETS, Dr. Oxendahl completed his bachelor’s degree in psychology at Portland State University, as well as master’s and doctorate degrees in Industrial-Organizational Psychology at Rice University.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/timoxendahl\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"ASSOCIATE MEASUREMENT SCIENTIST","imageGridCardDescription":"\u003ch3\u003eErin Renfrow-Symon\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/erin-renfrow-symon.jpg","imageGridCardImageAlt":"Erin Renfrow-Symon","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eDr. Erin Barno Renfrow-Symon\u003c/b\u003e is an associate measurement scientist working at the intersection of teacher education, assessment design, and generative AI. Her research develops the conceptual foundations and technical infrastructure for simulation-based assessments in which teachers interact with LLM-generated personas to rehearse high-leverage teaching practices. Applying evidence-centered design, she makes the relationship between task design and learning opportunity specifiable and traceable so turn-by-turn interaction data can reveal new insights into teaching competencies.\u003c/p\u003e\r\n\u003cp\u003eAs Co-PI on Gates-funded projects, she collaborates with instructional coaches in New York City public schools to use simulation-based practice experiences to support teachers\u0027 mindsets toward, and implementation of, equitable mathematics instruction. Within the Praxis team, she leads research on multi-agent LLM simulation for teacher learning and assessment.\u003c/p\u003e\r\n\u003cp\u003eA former secondary mathematics teacher and instructional coach in Boston, Dr. Renfrow-Symon holds an M.S.T. in secondary mathematics education from Boston College and a Ph.D. in STEM curriculum and instruction from Boston University.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/erin-barno/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"SENIOR STRATEGY \u0026 RESEARCH ANALYST","imageGridCardDescription":"\u003ch3\u003eJonathan Rochkind\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/rochkind.jpg","imageGridCardImageAlt":"Jonathan Rochkind","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eJonathan Rochkind\u003c/b\u003e is a senior strategy and research analyst in the ETS Research Institute. He leads ETS’s work on the Programme for International Student Assessment (PISA) Vocational Education and Training (VET): a collaboration with the Organisation for Economic Co-operation and Development (OECD) to develop a large-scale assessment of occupation-specific and general employability skills in vocational education and training. In this role, he supports cross-functional research and business development efforts focused on building assessment frameworks, designing and piloting innovative tasks, and translating evidence into actionable insights for education and workforce stakeholders.\u003c/p\u003e\r\n\u003cp\u003eJonathan also contributes to ETS initiatives that measure durable, transferable skills (e.g., problem solving, communication, collaboration, adaptability), including work on Skills for the Future (SFF) and ETS skills prototyping efforts. Across his work, he draws on deep experience in mixed-method research, needs sensing, public engagement, and program/policy evaluation, and has led projects and partnerships spanning K–12, higher education, workforce, and career pathways. Prior to his current role, he served in leadership roles at ETS in policy evaluation and research administration and was previously the Vice-President of Research at Public Agenda, a research and public engagement nonprofit. He earned a B.A. in philosophy and political science from the University of Wisconsin–Madison and completed graduate studies in philosophy at the University of Massachusetts Amherst.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/jon-rochkind/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"SENIOR RESEARCH PROJECT MANAGER","imageGridCardDescription":"\u003ch3\u003eYuan Wang\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/yuan-wang.jpg","imageGridCardImageAlt":"Yuan Wang","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eYuan Wang\u003c/b\u003e is a senior research project manager in the Research \u0026amp; Development division at ETS. She joined the organization after receiving her M.A. in TESOL from Teachers College, Columbia University in 2009. She also holds an M.A. in journalism and a B.A. in English, both from Nanjing University in China.\u003c/p\u003e\r\n\u003cp\u003eShe currently works in the Center for Education and Career Development at ETS. Previously at ETS, she worked as a producer in the AI Research Labs on projects related to automated content generation and packaging and as a research project manager in the English Language Learning and Assessment and the Foundational and Validity Research groups. Her research interests include learning through collaboration, teaching and assessing English listening and speaking skills, vocabulary learning and pedagogy, content analysis of curriculum and assessment materials, feedback on speaking and writing performances, and teacher development in all those areas. She won the 2019 ETS Presidential Award for her participation in the Teaching Academic English project. She has presented in internal and external seminars, conferences, and workshops, and published in a variety of peer-reviewed journals and books.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/yuan-wang-06795484/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"RESEARCH PROJECT MANAGER","imageGridCardDescription":"\u003ch3\u003eField M. Watts\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/field-watts.jpg","imageGridCardImageAlt":"Field M. Watts","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eDr. Field M. Watts\u003c/b\u003e is a Research Project Manager in K-12 Research at ETS, where he leads and contributes to research on artificial intelligence (AI), assessment, and STEM learning. His work focuses on understanding and measuring student reasoning, designing AI-supported formative assessment systems, and advancing the responsible use of AI to support learning in STEM education. At ETS, he has helped develop and evaluate AI-enabled tools that provide automated feedback on students’ scientific argumentation, reasoning, and modeling, while collaborating with educators to ensure these systems are meaningful, trustworthy, and practical for classroom use.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\r\n\u003cp\u003eDr. Watts contributes to multiple federally and privately funded initiatives and serves as Co-PI on an IES grant focused on the automatic measurement of student reasoning in scientific argumentation. His research combines learning sciences, evidence-centered design, qualitative and quantitative methods, and machine learning to investigate how students learn and how technology can support that learning. In addition, he contributes to research on STEM pathways and postsecondary success, including a Gates Foundation-funded project examining how calculus preparation aligns with STEM disciplinary demands. This work explores how evidence-based curricular and instructional supports can help broaden participation and success in STEM fields.\u003c/p\u003e\r\n\u003cp\u003eBefore joining ETS, Dr. Watts was a Postdoctoral Research Associate at the University of Wisconsin-Milwaukee. His earlier research explored undergraduate students’ mechanistic reasoning in chemistry and developed machine learning and natural language processing approaches to analyze students’ written explanations and provide automated formative feedback. Dr. Watts has authored or co-authored more than 30 peer-reviewed journal articles, conference proceedings, and book chapters spanning educational measurement, STEM education, learning analytics, and AI in education. He received an NSF Graduate Research Fellowship and holds a Ph.D. and M.S. in Chemistry from the University of Michigan, along with B.S. degrees in Chemistry and Mathematics from Oklahoma State University.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/field-watts/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n\u003cp\u003eGoogle Scholar: \u003ca rel\u003d\"noopener noreferrer\" href\u003d\"https://scholar.google.com/citations?user\u003dmTvDVQEAAAAJ\u0026amp;hl\u003den\" target\u003d\"_blank\"\u003ehttps://scholar.google.com/citations?user\u003dmTvDVQEAAAAJ\u0026amp;hl\u003den\u003c/a\u003e\u003c/p\u003e\r\n"},{"imageGridCardEyebrow":"SENIOR MEASUREMENT SCIENTIST","imageGridCardDescription":"\u003ch3\u003eKevin M. Williams\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/williams.jpg","imageGridCardImageAlt":"Kevin M. Williams","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cp\u003e\u003cb\u003eKevin Williams\u003c/b\u003e is a Senior Measurement Scientist in the ETS Research Institute, joining ETS in 2016.  He received his Ph.D. in personality psychology with a minor in quantitative psychology from the University of British Columbia in 2008.  After coauthoring the seminal research article introducing the Dark Triad of personality, his research has expanded to include investigations into the predictive validity and malleability of noncognitive constructs in workplace contexts, validity research for high school equivalency tests, psychometric evaluations of novel psychological assessments, response bias in job performance evaluations, career and technical education (CTE) pathways, educational and career experiences of underrepresented groups, the use of artificial intelligence in assessment development, and identifying skills for the new economy through employer expectations. Collectively, Dr. Williams’ research has been cited over 12,000 times, and he has received awards for his conference presentations and journal articles.\u003c/p\u003e\r\n\u003cp\u003eIn addition to consistent activity as a journal article author and conference presenter, Dr. Williams frequently serves as an ad hoc reviewer for a wide range of book chapters and journal manuscripts. Dr. Williams currently serves on the executive committee for Division 5 (Quantitative and Qualitative Methods) of the American Psychological Association as editor for “The Score”, the Division’s quarterly newsletter. Prior to joining ETS, his professional experience included the development and validation of psychological and licensure assessments for stakeholders in educational, workplace, clinical, health care, law enforcement, and correctional fields.\u003c/p\u003e\r\n\u003cp\u003eVisit to \u003ca rel\u003d\"noopener noreferrer\" target\u003d\"_blank\" href\u003d\"https://www.linkedin.com/in/kevinmwilliamsphd/\"\u003eLinkedIn profile\u003c/a\u003e\u003c/p\u003e\r\n"}]}