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Department of Human Development and Quantitative Methodology (HDQM)

NSF QRM Scholars Program

Quantitative Research Methods for STEM Education Scholars Program

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Welcome to the NSF-funded Quantitative Research Methods for STEM Education Scholars Program (NSF QRM Scholars Program)

The NSF QRM Scholars Program pairs early-career education researchers with quantitative mentors to help researchers develop their skills in design, measurement, and analysis. The program offers a year-long training that includes an initial intensive virtual Training Institute on fundamental quantitative methodology, on-going live-stream (or in-person) workshops, and access to quantitative expertise through ongoing interaction with the assigned mentor. The institute and the subsequent workshops will focus specifically on the data analysis skills, measurement issues, and design principles most applicable to STEM Education researchers. In addition, Scholars receive access to a state-of-the-art statistical computation and software server for the duration of their Scholar year.

Throughout the year, Scholars will design and implement a study of their choice with the support of their quantitative mentor and a content area mentor proposed by the Scholar. At the culmination of the program, Scholars will attend a day-long Capstone Conference to share their work.

Applications for the 2022-23 cohort are now open! The priority deadline is September 18, 2022.

See our application page for detailed instructions.

As part of the NSF QRM Scholars Program, you will

  • Improve your capacity as an early career faculty or postdoctoral fellow to apply best-practices design, measurement, and data analysis strategies and techniques to your own research;
  • Collaborate with a dedicated quantitative mentor throughout the program year;
  • Strengthen your peer-support network by connecting with fellow Scholars during the virtual Training Institute, participating in social media conversations with other Scholars during the program year, and sharing your research with your cohort; and
  • Gain the skills to work on multidisciplinary teams and develop professional relationships with quantitative methodologists to enhance the methodological rigor of your own research after the completion of the program year.

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Applications for the 2022-23 cohort are now open! The priority deadline is September 18, 2022.

Applying to the NSF QRM Scholars Program

The NSF QRM Scholars Program is an NSF-funded project aimed at building capacity in STEM Education research. The program admits 20 new Scholars each year and provides quantitative research training, workshops, mentorship, and opportunities for Scholars to share their work with a broader audience. Following a virtual Training Institute, Scholars will receive mentorship and training throughout the year, which they may complete while at their home institution.

To be eligible for the 2022-23 cohort of the NSF QRM Scholars Program, you must:

  • be early career faculty or a postdoctoral fellow at a US institution during the 2022-2023 academic year;
  • be within 10 years of having earned a terminal degree; and
  • have a research focus related to issues of access and equity of underrepresented populations in STEM within either PK-12 or postsecondary settings.

The NSF QRM Scholars Program is intended to be diverse, and we encourage submissions from applicants who identify with traditionally underrepresented groups or backgrounds.

If you are accepted and choose to join the 2022-23 NSF QRM Scholars Program, you will be required to engage in the following Program activities:

  • Attend the 3-day VIRTUAL Fall Training Institute (Oct. 21, 22, & 28, 2022);
  • Attend the 2-day IN-PERSON Winter Training Institute at University of Maryland, College Park (Feb. 24-25, 2023 -- note that funds will be provided for travel to the University);
  • Participate in at least 8 virtual live-stream or asynchronous workshops throughout the year (dates TBD; workshops range from 1-3 days);
  • Attend regular virtual check-ins with your Methods Mentor Team;
  • Participate in ongoing peer discussions via the moderated social media group;
  • Dedicate sufficient “on-your-own” time to make satisfactory progress on your identified Scholar project throughout the year; and,
  • Upon successful completion of the Program, serve as a peer mentor to fellow Scholars.

Please see our FAQ for any additional details regarding the above activities.

 

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TRAINING INSTITUTE

The NSF QRM Scholars Program offers a year-long training starting with intensive Training Institutes on fundamental quantitative methodology, including research design, measurement, analysis, and collaboration.

Scholars will also participate in ongoing live-stream or asynchronous workshops and will have access to quantitative expertise through regular interaction with an assigned methods mentor team. The institutes and workshops will focus specifically on the data analysis skills, measurement issues, and design principles most applicable to STEM education researchers.

An example of the topics and activities we will engage in during the training institutes is provided below. Detailed information about the training institute schedule will be provided to accepted Scholars.

EXAMPLE OF TOPICS/ACTIVITIES

Introductions & Networking: Scholars, Mentors, and Facilitators

Keynote: Speaker TBA.

Quantitative Research Design: Threats to validity; Types of experimental and non-experimental Design; Practical experimental designs in education; Aligning design to the research questions

Measurement, Reliability, & Validity: What is measurement; Why its quality is important; Aspects of construct validity; Evidence of the quality of various aspects of validity

Selection of Measures: Instrument repositories; Use of extant data; Test bias; Invariance of measurement over time

Instrument Construction: Cognitive and non-cognitive measurement approaches; Steps of measure development

Measure Validation: Cognitive process model of responding; Use of cognitive interviewing for validation

Discussion on Mentoring: How to Work with Your Mentor with Dr. Kimberly Griffin

Hands-On Item Analysis for Validation: Inter-item correlation; Factor analysis for scale construction; Differential item functioning

Writing Session: Refine your research proposal & develop individual learning plan

Nested Data & Multilevel Modeling: Intraclass correlation; Analytic strategies to address nesting; Matching research question to analysis

Group Comparisons: Power; Treatment Effects; Moderation; Confounders/Covariates

Longitudinal Designs & Data Analysis: Benefits/affordances of longitudinal designs; Individual change and differences in rates of change

Meet the NSF Program Officer: Funding Mechanisms & NSF Agency Priorities with Dr. Finbarr Sloane, Program Director, National Science Foundation

Wrapping it Up: Scholar networking; Building your (online) community; Small group meetings with mentor(s) and review individual learning plans

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PROGRAM TEAM

The NSF QRM Scholars Program brings together quantitative methodologists, experts in STEM Education research, and graduate student liaisons to guide Scholars through the process of developing and implementing their research proposals. Scholars will be paired with one of our methodology experts, who will also lead workshops during the virtual Training Institute and throughout the year. Graduate student liaisons will work with Scholars to ensure that they have the assistance they need, and our STEM education experts will conduct monthly check-ins with Scholars to assess progress and provide additional support.

Meet our Team:

Program Directors

Laura M. Stapleton

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Laura M. Stapleton is chair of the Department of Human Development and Quantitative Methodology and a professor of Measurement, Statistics and Evaluation. She previously served as the interim dean of the College of Education and Associate Dean for Research, Innovation, and Partnerships. She is the Director of the NSF-funded Quantitative Research Methods Scholars Program, which trains 20 early career scholars who focus on STEM education equity and access. She currently serves as Associate Editor of AERA Open and each year teaches as part of the faculty of the National Center for Education Research funded Summer Research Training Institute on Cluster Randomized Trials at Northwestern University. She joined the faculty of the college in Fall 2011 after being on the faculty in Psychology at the University of Maryland, Baltimore County and in Educational Psychology at the University of Texas, Austin. She served as the Associate Director of the Research Branch of the Maryland State Longitudinal Data System Center from 2013-2018. Prior to earning her Ph.D. in Measurement, Statistics and Evaluation, she was an economist at the Bureau of Labor Statistics and, subsequently, conducted educational research at the American Association of State Colleges and Universities and as Associate Director of institutional research at the University of Maryland.

Gregory R. Hancock

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Gregory R. Hancock is Professor, Distinguished Scholar-Teacher, and Director of the Measurement, Statistics and Evaluation program in the Department of Human Development and Quantitative Methodology at the University of Maryland, College Park, and Director of the Center for Integrated Latent Variable Research (CILVR). His research interests include structural equation modeling and latent growth models, and the use of latent variables in (quasi)experimental design. His research has appeared in such journals as Psychometrika, Multivariate Behavioral Research, Structural Equation Modeling: A Multidisciplinary Journal, Psychological Bulletin, Psychological Methods, British Journal of Mathematical and Statistical Psychology, Journal of Educational and Behavioral Statistics, Educational and Psychological Measurement, Review of Educational Research, and Communications in Statistics: Simulation and Computation. He also co-edited the volumes Structural Equation Modeling: A Second Course (2006; 2013), The Reviewer's Guide to Quantitative Methods in the Social Sciences (2010; 2019), Advances in Latent Variable Mixture Models (2008), Advances in Longitudinal Methods in the Social and Behavioral Sciences (2012), and Advances in Latent Class Analysis: A Festschrift for C. Mitchell Dayton (2019). He is past chair of the SEM special interest group of the American Educational Research Association (three terms), serves on the editorial board of a number of journals including Psychological Methods, Structural Equation Modeling: A Multidisciplinary Journal, and Multivariate Behavioral Research, chairs the Statistical and Research Methodology grant panel of the Institute of Education Sciences, and has taught over 100 methodological workshops in the United States, Canada, and abroad. He is a Fellow of the American Educational Research Association, the American Psychological Association, and the Association for Psychological Science, and received the 2011 Jacob Cohen Award for Distinguished Contributions to Teaching and Mentoring by the American Psychological Association.

Tracy M. Sweet

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Tracy Sweet is an Associate Professor in the Measurement, Statistics and Evaluation program in the Department of Human Development and Quantitative Methodology. She completed her Ph.D. in Statistics at Carnegie Mellon University. Her research focuses on statistical social network models with particular focus on the types of multilevel network models needed for education data. Her recent work on network models includes modeling networks as mediators and cluster analysis on networks. Her research also includes data science methods; a recent project focuses on how data science methods such as machine learning algorithms should be applied to multilevel data.

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Methodology & STEM Education Experts

Kimberly Griffin

Kimberly Griffin

Dr. Kimberly Griffin is Dean of the College of Education and a Professor in the Higher Education, Student Affairs, and International Education Policy Program (Student Affairs Area of Specialization). She also serves as the editor of the Journal of Diversity in Higher Education. Dr. Griffin earned her doctoral degree in Higher Education and Organizational Change from UCLA, her Master's degree in Education Policy and Leadership at the University of Maryland, and her Bachelors degree from Stanford University in Psychology. Prior to completing her doctoral work, Dr. Griffin worked in higher education administration, primarily focusing in the areas of diversity recruitment, admissions, and retention in undergraduate and graduate education.

Jeffrey R. Harring

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Dr. Harring is a Professor in the Measurement, Statistics, and Evaluation (EDMS) program in the Department of Human Development and Quantitative Methodology at the University of Maryland. Prior to joining the the EDMS faculty in the fall of 2006, Dr. Harring received an M.S. degree in Statistics in 2004, and completed his Ph.D. in the Quantitative Methods Program within Educational Psychology in 2005, both degrees coming from the University of Minnesota. His research on mixture modeling, longitudinal methods, and structural equation modeling has appeared in such journals as Psychometrika, Psychological Methods, Multivariate Behavioral Research, Journal of Educational and Behavioral Statistics, Structural Equation Modeling, and Sociological Methods & Research. Dr. Harring is an Associate Editor of Psychometrika and is an editorial board member of three other flagship quantitative methods journals.

Hong Jiao

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Dr. Hong Jiao is a full professor at the University of Maryland (UMD), College Park specializing in educational measurement and psychometrics in large-scale assessment. She received her doctoral degree from Florida State University. Prior to joining the faculty in Measurement, Statistics, and Evaluation at UMD, she has worked as a psychometrician at Harcourt Assessment for over four years. She has served as a committee member, co-chair, and chair on several committees for NCME, AERA Division D, and the Psychometric Society. She also serves on the Research and Psychometric committee for the PARCC consortium testing programs. Charing the Technical Advisory Committee (TAC) for the Maryland state testing programs and as director for Maryland Assessment Research Center (MARC), she works with TAC members and the MARC team to help the state to provide rigorous testing programs to the state test stakeholders. She co-organized several conferences and co-edited the books on different cutting-edge topics in assessment including technology-enhanced innovative assessment and the applications of artificial intelligence in assessment. She has published and presented on a variety of topics, including multilevel IRT modeling, modeling complex local item dependence in innovative assessments, mixture item response theory modeling, integrating responses and response time for cognitive diagnosis.

Yang Liu

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Yang Liu is currently an Associate Professor in the Measurement, Statistics, and Evaluation program of the Department of Human Development and Quantitative Methodology at University of Maryland, College Park. He earned his Ph.D. degree in Quantitative Psychology and M.S. degree in Statistics from the University of North Carolina at Chapel Hill. His research focuses on statistical models for item response data, procedures for assessing goodness of model fit, and quantification of uncertainty in statistical decision-making. He is also interested in applications of item response models to psychological, educational, and health-related research. Dr. Liu's Personal Website.

Peter M. Steiner

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Peter M Steiner is a Professor in the Measurement, Statistics, and Evaluation (EDMS) program in the Department of Human Development and Quantitative Methodology at the University of Maryland. Prior to joining the EDMS faculty in fall of 2019, he was a faculty member of the Department of Educational Psychology at the University of Wisconsin-Madison (2010-2019), a research associate at the Institute for Policy Research at Northwestern University (2007-2010), and a researcher and Assistant Professor at the Institute for Advanced Studies in Vienna, Austria (1997-2007). Peter M Steiner received a master’s and doctorate degree in Statistics from the University of Vienna and a master’s degree in Economics from the Vienna University of Economics and Business Administration. His research on causal inference, replication, and factorial surveys has appeared in such journals as Psychological Methods, Multivariate Behavioral Research, Journal of Educational and Behavioral Statistics, Evaluation Review, Sociological Methods & Research, Journal of Causal Inference, or the Journal of the American Statistical Association. In 2019, he received the Causality in Statistics Education Award of the American Statistical Association.

Ebony Terrell Shockley

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Dr. Terrell Shockley is the College of Education's Executive Director of Teacher Education; she is also an Associate Clinical Professor for the Department of Teaching and Learning, Policy and Leadership. She provides collegewide oversight for educator preparation and supervises assessment, recruitment, school partnerships, and accreditation. During the start of the COVID-19 pandemic, she initiated, coordinated, and launched UMD's #EdTerpDialogues to provide a space for the community to engage in discussions about critical issues in online learning, wellness, and social justice. From 2012 to 2020, Dr. Terrell Shockley directed the Master's Certification (MCERT) Program for graduate students seeking an M.Ed. and certification in art education, dance education, elementary education, English education, mathematics education, physical education, science education, social studies education, Teachers of English for Speakers of Other Languages (TESOL), and world languages education. Under her leadership, the MCERT program appeared on the National Education Association's website as a featured teacher residency model: https://www.youtube.com/watch?v=jfWrNWbdyjs and 100% of the MCERT teacher candidates seeking positions as classroom teachers receive jobs each year. Prior to 2012, she served as a PK-12 educator and instructional specialist as she holds certifications in administration and leadership, secondary science, ESOL, special education, and literacy.

Ji Seung Yang

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Dr. Yang is an Associate Professor of Measurement, Statistics, and Evaluation (EDMS) in the Department of Human Development and Quantitative Methodology at the University of Maryland. Before joining the EDMS faculty in the fall of 2013, Dr. Yang worked as a postdoctoral researcher at University of California - Los Angeles (UCLA) where she received her Ph.D. in the Social Research Methodology Program (focus: Advanced Quantitative Methods in Educational Research) within the School of Education and Information Studies in 2012. Prior to joining UCLA, she earned her M.A. and B.A. in Education at Yonsei University, Korea. Dr. Yang's research interests focus on measurement and advanced quantitative research methods in social sciences. The research interests encompass 1) development of statistical models that incorporate measurement errors in the frameworks of Item Response Theory, Generalizability Theory, Hierarchical Linear Modeling, and Latent Variable Modeling, and 2) development of multilevel/multidimensional item response model with efficient computation.

Shujin Zhong

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Shujin Zhong is a Postdoctoral Associate in the Measurement, Statistics and Evaluation program in the Department of Human Development and Quantitative Methodology. Her work supports the NSF-funded Quantitative Research Methods Scholars Program. She received her Ph.D. from the Social Research Methodology program at the University of California, Los Angeles (UCLA). Methodologically, her research focuses on educational measurement, latent variable modeling, causal effects under selection on observables, social network analysis, and research design. She is also interested in the application of methods in the field of higher education and STEM education.

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Graduate Student Liaisons

Yi Feng

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Yi earned her master's degree in EDMS in 2018 and is currently pursuing her PhD in the EDMS program. Before that, she received a master's degree in Applied Psychology at New York University and spent two years conducting empirical research on adolescents' socio-emotional development at Purdue University. The experience of dealing with data and applying different analytic methods to answer various research questions contributed to her interest in quantitative methodology. Yi’s research interests include SEM, LGM, random variability modeling, power analysis, and planned missing data designs.

Francesca D. Henderson

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Francesca is a native San Diegan who is in her first year of doctoral studies in Mathematics Education. As a previous math teacher, vice principal, and a career educator she ultimately wants to work to empower teachers and students to use math as a tool to both understand and change the world. She joins the QRSM team excited to work with scholars on their path to utilize quantitative methods in their research.

Ashani Setha Jayasekera

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Ashani graduated from the University of Maryland, Baltimore County in 2020 with a bachelor’s degree in Mathematics and minors in Statistics and Psychology. While there, she worked in the Pediatric Psychology Lab researching the impact of COVID-19 on undergraduate students' learning during the initial shutdown in the spring of 2020. Her experiences with data and answering research questions using different analytic methods to answer led her to the EDMS program and earning a master’s degree and pursuing a doctoral degree in quantitative methodology.

Tessa L. Johnson

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Tessa is a PhD student in the Measurement, Statistics and Evaluation program in the Department of Human Development and Quantitative Methodology at the University of Maryland, College Park. She received her Master of Science in Educational Research from Georgia State University. Tessa’s research has centered around creating and improving statistical methods for analyzing complex data structures in a longitudinal context, such as modeling time as an outcome in latent growth models, accounting for similarities among schools when modeling student mobility in longitudinal studies, and exploring the development of ensembles of social networks in the classroom over time.

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2021-22 COHORT

The 2021-22 Cohort of QRM Scholars pursue cutting-edge research from across the STEM Education field with a focus on equity and inclusion. Scholars are paired with mentors and receive quantitative training to guide them as they conduct high-quality research and prepare proposals for grant funding.

Meet the 2021-22 Cohort:

Yejun Bae

Carolina University

 

 

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Elizabeth Frechette

University of Oklahoma-Tulsa

 

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Afiya Fredericks

University of the District of Columbia

 

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Inah Ko

University of Michigan

 

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Yu-Tung Kuo

North Carolina A&T State University

 

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Rachel Lambert

University of California Santa Barbara

 

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Jillian Lauer

New York University

 

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Kelly Lazar

Clemson University

 

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Johanna Massey

Alabama A&M University

 

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Rob Moore

University of Florida

 

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Angel Miles Nash

Chapman University

 

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Emine Ozturk

University of North Dakota

 

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Soyoung Park

Western Kentucky University

 

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Anthony Peña

Claremont Graduate University

 

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Rachel Renbarger

Western Michigan University

 

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Brooke Rumper

Temple University

 

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Jack Simons

Mercy College

 

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Erin Scott-Stewart

Southern University and A&M College

 

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Jennifer Tsan

University of Chicago

 

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Colleen Uscianowski

University of Cincinnati

 

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FAQ

We are excited to work with a new cohort for this year's NSF QRM Scholars Program. Below are answers to some of our most frequently asked questions. If the answer to your question is not provided below, please contact us at nsf-qrm-scholars@umd.edu.

Eligibility

  • Who is eligible to participate in the program?

    To be eligible for the NSF QRM Scholars Program, you must be full-time faculty or a postdoctoral fellow at a U.S. academic institution within 10 years of earning a terminal degree and have a research focus related to issues of access and equity of underrepresented populations in STEM within either PK-12 or postsecondary settings. The NSF QRM Scholars Program is intended to be diverse, and we encourage submissions from applicants who identify with traditionally underrepresented groups/backgrounds.

  • How do you define "early career"?

    Early career scholars who are full-time faculty or postdoctoral fellows at U.S. academic institutions who are within 10 years of earning a terminal degree are eligible to apply.

  • Do you have to be a tenure-track faculty member to apply?

    The NSF QRM Scholars Program is intended to serve early career faculty in academic institutions who engage in STEM Education research. Applicants do not need to be tenure-track to apply. Postdoctoral fellows are eligible as are clinical faculty who received their doctoral degrees within the past 10 years.

  • Do I have to be a U.S. citizen to be eligible?

    There are no citizenship requirements for acceptance into the program. However, applicants must be employed by a U.S. academic institution to be eligible to participate.

  • How do you define "academic institution"?

    Eligibility is restricted to individuals employed by a degree-granting institution in the United States that offers associate's degrees or higher and participates in the Title IV federal financial aid programs.

  • I am a researcher in a STEM field with interest in STEM education. Would I be eligible even if I am not currently an education researcher?

    You don't have to be an "education researcher" to be eligible, you just need a proposed project that is related to STEM education.

  • Am I the right fit for this program?

    "In my doctoral program, I took courses in item response theory, structural equation modeling, and meta analysis. I sometimes use Monte Carlo simulations to calculate power for my research studies."

    No, you are not a fit for our program. We are sure that you will be successful in your quantitative ventures, but this program is designed for those scholars who were unable to fit such coursework in their graduate studies.

    "I took one research methods course that covered quant methods in my program but focused on qualitative inquiry methods and took courses in ethnography, case study, and constant-comparative methods."

    Yes! You sound like a great fit. NSF is interested in training folks who have the important knowledge base in STEM education but could not fit quantitative courses into their doctoral program. Scholars with the skills to conduct both qualitative and quantitative inquiry are needed to answer the important questions posed by the current state of our education system.

    "I did take several quant classes in my doctoral program, such as multilevel modeling and factor analysis. But, to be honest, I haven’t used these methods since I graduated and I don’t really remember what I supposedly learned."

    Yes! It sounds like you had (and have) the interest but just need a reminder! We can remind you! (As long as you don’t mind a little repetition).

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Application Materials

  • What information needs to be included in the Statement of Interest?

    Applicants should describe their background and personal goals in relation to their eligibility for the NSF QRM Scholars Program. A description should be provided as to how the applicant's proposed project aligns with the goals of the NSF QRM Scholars Program. In total, the Statement of Interest should be no more than 1 page maximum (single-spaced).

    The applicant will also describe a tentative research project or proposal that they would like to work on over the Scholar year using the structured abstract format (for details, see the answer below). However, the components of the structured abstract will not be included in the statement of interest, but rather will be copied and pasted individually into text boxes provided in the application form.

  • How do I write a structured abstract?

    We are interested to learn about what YOU are interested to learn about. You can propose to work during the academic year on a specific research project or you can propose to work on a federal or foundation grant proposal for funding (e.g., perhaps an NSF proposal). We are interested in identifying participants whose aim is to study and address inequities in the educational system regarding STEM education.

    The application system will prompt you to include information on the following components of your proposed research ((50 words maximum per section):

    Background/Context: Present the relevant background information. Purpose/Research Questions: Identify the purpose of the research / primary research questions. Population of Interest: Describe the population of interest for this research, potentially including units of observation (e.g., schools, students, teachers), settings, etc. Type of Research Design: Describe the proposed research design (e.g., randomized controlled trial, observational study, secondary data analysis), if known. Data Description (and Data Collection Plan): Indicate the status of your data collection and describe the proposed data sources (e.g., cross-sectional, longitudinal, secondary data, achievement, attitudes, knowledge, behaviors). Discuss your data collection plan if applicable. Proposed Analysis: Discuss the plan for analyzing data, if known.

    Your responses to each component of the sturctured abstract must be 50 words or fewer. For more information on writing a structured abstract, see Mosteller, Nave, and Miech (2004).

  • How specific does my description of the research project or proposal need to be?

    With only about 300 words (see the structured abstract details above), we are not expecting too much detail, just a general tentative description of your research questions and population of interest. If you already know the type of design or data collection you would like to do, feel free to share that. However, it is also important to note two things: 1) once you are at the Training Institute, you might change your research focus or choose to collaborate with another scholar that you meet; 2) you can describe either a research project that you want to conduct or a proposal that you want to write to seek funding.

  • Does my proposed project have to involve quantitative research methods?

    We are specialists in quantitative methods and are best suited to help mentor you in quantitative research, so your proposal should be quantitative in nature. That said, we don't expect you to come into the program with a vast wealth of experience using quantitative methods, and you don't have to propose to use the most complex model you can think of for your quantitative analysis. (Did someone call for a parallel process growth mixture latent transition analysis with fuzzy clustering? Anyone? No?) Your proposed research will be tentative and should provide a general idea about the population of interest an the research questions to be addressed. You aren't required to identify a specific quantitative method to use in your proposal at all as your analysis plan will likely change after you've received some quantitative training and mentorship.

  • What are the goals of the NSF QRM Scholars Program?

    NSF was seeking research methods institutes to "build capacity in STEM education research." And that is what we are aiming to do. We would be honored to train and collaborate with researchers who will make a difference! Specifically, we hope that you will exit our program with: 1) quant skills, 2) ideas of how to collaborate with quant methodologists who specialize in advanced approaches, 3) a cadre of fellow STEM education researchers with whom you can commiserate and celebrate, and 4) a completed research study or proposal. Not bad for a year’s worth of work!

  • Do I need to have a Google Scholar profile set up before I apply?

    Yes. We ask you to do that for several reasons. First, it provides us with an external source to validate some of your application information. Second, it increases your research profile (if you did not already have a GS profile set up). Finally, as with any funded project, the funders are interested in finding out if the funded program "makes a difference." Following those applicants who participated in the program as compared to those who did not will provide us one piece of evidence regarding the efficacy of our training program.

    For more information on setting up your Google Scholar profile, please read the setup instructions from Google or this step-by-step guide created by the University of Oklahoma University Libraries.

  • What should be included in the Administrative Letter of Support?

    This very short letter just needs to indicate that the supervisor understands that you will be attending the mandatory training institutes along with eight virtual live-stream workshops during the Scholar year. This letter should be no more than 1 page maximum (single-spaced).

  • What should I highlight in my 2-page CV? My current CV is way more than the maximum of 2 pages!

    Let's be honest, we cannot really evaluate your CV in terms of your content area preparation or regarding the significance of your research proposal (heck, we are quantitative methodologists, after all, what do we know about those things?) But what we are interested in is: do you have the passion to address equity issues in STEM education? Do you have the desire to add to your quantitative toolkit? And are you 10 years out from your terminal degree at an institution in the US?

  • How do I submit my application?

    Applications must be uploaded and submitted via the application portal (see the Applications page for the link and the application instructions documentation). The application portal requires that the main written components of the application be uploaded as PDF documents. More information about process and procedures deadlines can be found on the Applications page.

  • Can I save my progress and return to my application?

    The application portal is managed via InfoReady (see the Applications page for the link and the application instructions documentation). The applicant will be required to register and create an account before you can submit an application. The system will then allow applicants to save their progress and continue at a later date. Only one application may be submitted by each applicant. Note that if you have not submitted a saved application by the deadline, your application will not be received by the review committee. Incomplete applications will not be reviewed.

    That said, the portions of the application requiring manual entry are relatively brief, including the participant’s name and contact information, a link to their Google Scholar page, a brief abstract outlining the Scholar’s proposed research, and PDF uploads for additional components of their application (Statement of Interest, Research Letter of Support, and Administrative Letter of Support). The application can reasonably be uploaded in a single sitting taking no more than 20 minutes.

  • Do you accept applications over email?

    Applications must be submitted via the application portal. No submissions will be accepted over email. Incomplete applications will not be accepted.

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Time Commitment & Program Benefits

  • What is the time commitment of participating in the Program?

    Scholars must commit to participating in the mandatory multi-day training institutes and at least 8 virtual workshops throughout the year, which will be provided live-streamed or asychronously. Workshops last between 1 and 3 days. Scholars must commit to attending regular meetings with their Methods Mentor Team. In addition, Scholars will be asked to engage in peer discussions via the moderated social media group. Finally, Scholars will need to dedicate sufficient "on-your-own" time to make satisfactory progress on their chosen research proposal throughout the Scholar year.

    Following the Scholar year, Scholars will serve as peer mentors for the incoming cohort following the successful completion of their program.

  • How much time will I need to dedicate to working on my Scholar project throughout the year outside of our training institutes and online workshops?

    The training institutes and virtual workshops are intended primarily as instructional time to help you learn advanced quantitative skills that will help you add to your research toolkit (see the Training Institute page for the topics/activities list). While there will also be time for you to work on your individual workplan during the Training Institute and there will be social time to build ties with your fellow Scholars and quantitative mentor, the bulk of the work on your Scholar project will be completed during the year from your home institution. We will have regular mentorship calls with you to help check in with your progress. One of the goals of the program is for you to have completed your Scholar project by the end of your Scholar year. You are likely much more familiar with your work style than we are, but we would recommend that you dedicate regular time to working on your project to ensure that you are able to reach this goal.

  • How much time will I need to dedicate to engaging with peer Scholars via social media throughout the Scholar year?

    Current Scholars will engage with their peers via a moderated group on social media. The goal of this interaction is to promote Scholar-to-Scholar interactions. There is no direct requirement for the maximum amount of time Scholars will dedicate to engaging with their peers over social media, but at minimum, Scholars should schedule time to regularly check in with the group and create and respond to posts as needed.

    Though it should go without saying, any repeatedly disruptive or inappropriate behaviors in any aspect of the Program, including on social media, will not be tolerated.

  • What are my obligations following the Scholar year?

    Scholars will serve as peer mentors for the incoming cohort following the successful completion of their Scholar year.

  • What do Scholars get out of participation?

    Scholars receive a year of training in quantitative research methods, a year of access to a state-of-the-art statistical computation and software server, a year of one-on-one mentorship from an expert in quantitative methodology, and a lifelong peer network of STEM Education researchers. In addition, Scholars will have the opportunity to meet and interact with the National Science Foundation program officer who oversees the Division of Research on Learning in Formal and Informal Settings for STEM Education research funding.

  • How do I ensure success in working with my Methods Mentor Team throughout the year?

    Dr. Terrell Shockley from the University of Maryland will hold regular check-ins with the Scholars to ensure that partnerships are functioning smoothly. In addition, during the Training Institute, Scholars will attend a session on how to work effectively with their mentors.

  • If accepted, how do I maintain good standing during my Scholar year?

    In order to maintain good standing within the Program, Scholars must attend the mandatory training institutes, participate in virtual workshops throughout the year, participate in check-ins with their Methods Mentor Team, engage in peer discussions via the moderated social media group, and make satisfactory progress on their chosen research proposal. For individuals who are not making progress or participating within any of these areas, the Program Team will work to help support the Scholar in completing their activities. If the Scholar is then unable to participate, the Scholar may discuss exiting the program with their Mentor. We understand that sometimes life happens, and every effort will be made to retain Scholars in the Program. The number one key to success in this Program is open and ongoing communication with your Mentor Team.

    Though it should go without saying, any repeatedly disruptive or inappropriate behaviors in any aspect of the Program, including on social media, will not be tolerated.

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Travel Information

  • Will I need to travel to the University of Maryland, College Park?

    Scholars will need to be able to attend the 2-day Winter Training Institute (Feb 24-25, 2023). Funding will be provided for travel to University of Maryland, College Park. Otherwise, Scholars will participate in the program from the comfort of their home institutions. To ensure that these regular virtual interactions can occur, applicants must attest that they have access to a reliable internet connection and webcam-enabled computer.

  • Will I need to pay for my own travel?

    Travel to the mandatory 2-day In-Person Winter Training Institute will be provided for accepted Scholars.

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