AERA Fellowship Program on the Study of Deeper Learning
AERA Fellowship Program on the Study of Deeper Learning
Call for Proposals

The AERA Fellowship Program on the Study of Deeper Learning online application is now available.

Deadline Now Passed

Information Webinar Recording from November 1, 2023

Download the AERA PowerPoint slides and AIR PowerPoint slides from the webinar.

The American Educational Research Association (AERA) invites proposals from early career education researchers and postdoctoral scholars to enhance the use of the Deeper Learning data set. Now accepting proposals for its next cohort of scholars, the AERA Fellowship Program on the Study of Deeper Learning (AERA-SDL) supports postdoctoral and early career scholars in education research and thereby fosters excellence and rigor in the next generation of faculty members, research scientists, and scholars examining education topics and issues. The AERA-SDL permits undertaking research projects using the Deeper Learning data and the design and implementation of professional development and training around these data. The Deeper Learning data collected by the American Institutes for Research (AIR) include a wealth of information from schools, students, and teachers at a sample of Deeper Learning network high schools and non-network high schools. AIR scholars and scientists with expertise on the Deeper Learning data are collaborating with AERA in this Fellowship Program. The program is supported by the William and Flora Hewlett Foundation.

Scope of Program and Purpose
The AERA-SDL Fellows Program will provide professional guidance and training for up to eight postdoctoral-level and early career scholars to undertake substantive research using the Deeper Learning data set. The aim is to contribute to knowledge and engender a culture of use for addressing significant questions about education and learning with these data.

The Deeper Learning data set includes student survey data examining opportunities to engage in deeper learning, intra- and inter-personal competencies, and students’ perceptions of their schools. The Deeper Learning student assessment data come from the Program for International Student Assessment (PISA), specifically the PISA-Based Test for School (PBTS) in English language arts, mathematics, and science. High school graduation and postsecondary enrollment information is also available for the students as part of this data set. Teacher survey data provide further information about each school’s academic culture and the relationships between faculty, administrators, and students. Qualitative data such as school case reports, scored teacher assignments, unscored student work samples, and interviews with principals provide rich details of the educational setting and school context. Topics addressed in the case reports and interviews include school culture and climate, school vision and goals, structures supporting deeper learning, instructional strategies, school leadership, teacher collaboration opportunities, and deeper learning network supports.

The combination of these unique and multiple data sets allows researchers to address questions connecting students’ high school experiences and achievement with high school graduation, postsecondary trajectories and degree completion, and workforce participation. Key staff members at AIR who are working with the Deeper Learning data are collaborating with AERA to facilitate data access and to develop training using these data sets.

Illustrative Topics
The Deeper Learning data allow researchers to explore many possible topics as well as methodological studies. Research projects that emphasize topics around diversity, equity, and inclusion are encouraged. Some examples of research projects that might be conducted using the Deeper Learning data are listed below (but many other research topics are equally appropriate to study for these data).

For scholars interested in psychometrics and/or item response theory:

The Deeper Learning data set includes item-level data from student surveys and teacher surveys. Scholars could examine alternative ways to construct scales using item-level data and could analyze whether items appear to measure constructs equally well for different groups of students or teachers.

For scholars interested in propensity score modeling:

Previous studies used propensity score modeling to determine the impact of attending a Deeper Learning network school on student outcomes. Interested scholars could examine how using different strategies to estimate propensity scores (e.g., adding different sets of predictors and/or interaction terms, using different statistical packages) would affect the estimated propensity scores.

For scholars interested in trajectories in postsecondary education:

National Student Clearinghouse data for all students in the sample are available for those students pursuing college and other postsecondary education. These data have information on postsecondary education enrollment for each term that a student is enrolled and on degree completion. Scholars may consider exploring different ways of examining students’ postsecondary trajectories using this detailed data, and they may examine different types of institutions that students attend by merging with the Integrated Postsecondary Education Data System.

For scholars interested in analyzing teacher assignments:

The data set includes teacher-provided examples of classroom assignments for which students would need to demonstrate deeper learning skills (e.g., critical thinking, communication skills, collaboration, etc.,). Scholars may consider alternative methods of assessing teacher assignments for their level of rigor and alignment with deeper learning.

For scholars interested in secondary school instructional approaches and structures:

The qualitative data set includes interview and focus group transcripts from school leaders, teachers, and students, as well as summary case reports from Deeper Learning network schools. Scholars may consider alternative methods to analyze the qualitative data and may examine different topics areas related to instructional approaches and school structures within Deeper Learning network high schools.  

Data Access
AIR will provide the fellows with remote access to the data and software to conduct analyses. Fellows will access these restricted data through the AIR secured data system. All data users must complete a data confidentiality agreement.

To be eligible for the AERA-SDL, scholars must have been awarded a doctorate between 2012 and 2023 or anticipate being awarded a doctorate by August 2024 in education research or another social or behavioral science discipline or interdisciplinary field, such as sociology, economics, psychology, psychometrics, or political science. Applicants must be U.S. citizens or U.S. permanent residents. Underrepresented racial and ethnic minority researchers and women are strongly encouraged to apply.

Information About the Deeper Learning Data
Applicants should be familiar with the principles and framework of the Deeper Learning study and the instruments used to collect the data. For further information about the SDL project, visit, where there are links to the following reports from the study:

  • The Shape of Deeper Learning: Strategies, Structures, and Cultures in Deeper Learning Network High Schools
  • Providing Opportunities for Deeper Learning
  • Evidence of Deeper Learning Outcomes
  • Deeper Learning and High School Graduation: Is There a Relationship?
  • School Features and Student Opportunities for Deeper Learning: What Makes a Difference?
  • Student Survey Documentation
  • Teacher Survey Documentation

Requirements and Expected Outcomes
At the conclusion of the program, fellows will prepare a draft manuscript of their research in journal-ready format. In addition to publishing peer-reviewed journal articles, fellows may produce research reports, policy briefs, and presentations at professional meetings related to this research. It is anticipated that scholars will complete work required for the AERA-SDL fellowship by Fall, 2025.

Award Components
Funding: Fellows will receive funding up to $35,000 to support their research projects using Deeper Learning data and to participate in workshops, courses, and other trainings to enhance their research skills and learn about the Deeper Learning data.

Study Overview and Data Training Workshop: At the beginning of the Fellowship Program, fellows will participate in a Study of Deeper Learning Overview and Data Training Workshop led by AIR researchers. During this training the fellows will obtain access to the Deeper Learning datasets and an orientation to the data structures, file formats, and other technical documentation.

Research Institute: At the 2025 AERA Annual Meeting in Denver, the fellows will present their research in an invited poster session along with other early career researchers supported by the AERA Grants Program and other prestigious fellowship programs. The poster session will allow fellows to showcase their studies and receive immediate feedback and guidance from senior researchers, scholars, deans of graduate schools and of colleges of education, and others in the education research community. The AERA Annual Meeting brings together over 15,000 researchers, scholars, and policy makers to present their research, share knowledge, and build research capacity through over 2,500 substantive sessions. The fellows will participate in sessions offered at the meeting and will benefit from professional development and networking activities. Finally, the fellows will participate in a research institute directly after the annual meeting that will address issues such as building a research agenda, publishing research, and attaining tenure. This institute is intended to help the fellows as they begin to prepare manuscripts based on their Deeper Learning project.

Application Instructions
All applications for the AERA Fellowship Program on the Study of Deeper Learning must be completed using the AERA online application portal by 11:59 p.m. Pacific Standard Time on Monday, March 4, 2024 (extended from January 31). Late applications and supporting materials will not be accepted. Please combine items 1–6 listed below into one PDF document (include your name and institution in header) and upload it to the online application portal. Each application must include:

  1. Abstract of the proposed project
  2. Proposal narrative (limited to 6 single-spaced pages) that addresses the following:
  • Statement of how this research advances the current state of knowledge in the field, substantively and/or methodologically.
  • Theoretical or conceptual framework or data model for the research.
  • Brief review of relevant research/policy literature.
  • Research questions, hypotheses to be tested.
  • Description of methodology, including the SDL instrument(s) and justification for selecting data file to address research question; any additional or supplemental data sample (e.g., groups used and exclusions to sample); list of variables from the SDL data to be used and rationale for using them; and clarification of variables and analytic techniques. For information about the SDL instruments and data files, visit
  • Data analysis plan and statistical model or formulas, appropriately defined. Conceptual or figural model depicting the design of the study (can be included in an appendix and does not count toward the page limit).
  • Brief dissemination plan for this research, including proposed conferences to present the findings and potential scholarly journals to publish the research.

3. References cited and any appendices.

4. Proposed budget up to $35,000 over a twenty month period. The budget must include items such as course buyout, graduate assistance, equipment, and conference expenses. Note institutions may not charge indirect fees to this award.

5. Applicant’s curriculum vitae (limited to 2 pages), which should include:

  • Research and academic employment history
  • Relevant graduate courses in statistics and methodology
  • Relevant publications and presentations
  • Relevant professional affiliations and/or memberships

6. List 2 or 3 senior scholars (name, institution, and email address) AERA could potentially contact for a reference.

Please combine items 1–6 as one PDF document and upload it through online application portal.

To be eligible for funding, fellows may not accept other or pending support for the same project. If offered more than one major grant or fellowship for the same project, the other award(s) must be declined in order to accept AERA-SDL funding.

Evaluation Criteria
The AERA-SDL initiative aims to support rigorous and methodologically sound research that expands our knowledge of schools, schooling issues, classroom practices, children and youth, and other educational topics. These studies cut across a broad range of theoretical perspectives and analytical plans to address the following criteria:

  • What is the potential for the study to advance knowledge and understanding in the discipline and/or the education field?
  • What is already known on the issue?
  • How appropriate is the SDL data set for addressing the research questions? How well does the analytic plan fit the data?
  • Is the applicant qualified to carry out the proposed study?
  • Do the research procedures, methods, approaches, etc., align with the study objectives?

Review and Selection Process
The AERA-SDL Advisory Committee, comprised of senior scholars and researchers, will review and evaluate the proposals. Reviews are treated as confidential documents. In some cases the applicant will receive an explanation of the decision to award or decline funding; however, AERA is unable to provide proposal feedback to all applicants.

Award Notification
AERA will notify all applicants of their proposal outcome in Spring 2024. All decisions and communication will be through email. Awards to fellows must be administered through their university or institution, unless otherwise approved. Note that institutions cannot charge for indirect or administrative costs.

Please address any questions to George L. Wimberly, AERA Director of Professional Development,  or 202-238-3200.

About AERA
AERA is concerned with improving the educational process by encouraging scientific inquiry related to education and evaluation and by promoting the dissemination and practical application of research results. AERA’s more than 25,000 members are faculty, researchers, graduate students, and other distinguished professionals with rich and diverse expertise in education research. AERA members’ areas of inquiry span education science and intersect with other social science disciplines and fields, such as anthropology, economics, psychology, sociology, and political science.

About AIR
Established in 1946, the American Institutes for Research (AIR) is an independent, nonpartisan, not-for-profit organization that conducts behavioral and social science research on important social issues and delivers technical assistance, both domestically and internationally, in the areas of education, health, and workforce productivity.