AERA Virtual Research Learning Series

AERA Virtual Research Learning Series


Professional Development and Training Courses
Available On-Demand from Series Originally Offered May - September 2020

Fee Per Course $35

(Includes access to all course materials)

All courses register here
What Would it Take to Change Your Inference? Quantifying the Discourse about Causal Inferences in the Social Sciences
Recorded on May 19, 2020
Duration: 3 Hours 28 Minutes ​
Kenneth Frank, Michigan State University
Statistical inferences are often challenged because of uncontrolled bias. There may be bias due to uncontrolled confounding variables or nonrandom selection into a sample. We will turn concerns about potential bias into questions about how much bias there must be to invalidate an inference. For example, we will transform challenges such as “But the inference of a treatment effect might not be valid because of preexisting differences between the treatment groups” to questions such as “How much bias must there have been due to uncontrolled preexisting differences to make the inference invalid?” By reframing challenges about bias in terms of specific quantities, this course will contribute to scientific discourse about uncertainty of causal inferences. In Part I, we use Rubin’s causal model to interpret how much bias there must be to invalidate an inference in terms of replacing observed cases with counterfactual cases or cases from an unsampled population (e.g., Frank et al., 2013). In Part II, we quantify the robustness of causal inferences in terms of correlations associated with unobserved variables or in unsampled populations (e.g., Frank, 2000). Calculations will be presented using the app with links to STATA and R modules. In Part III, we extend to nonlinear models, interaction effects, specific study designs (e.g., regression discontinuity), and thresholds for inferences. The format will be a mixture of presentation, individual exploration, and group work. Participants should be comfortable with the general linear model (e.g., multiple regression) and statistical inference.
How to Get Published: Guidance from Emerging and Established Scholars
Recorded on May 21, 2020
Duration: 3 Hours 51 Minutes ​
Patricia A. Alexander, University of Maryland,
College Park
(course director)
Yuting Sun, University of Maryland, College Park
Anisha Singh, University of Maryland, College Park
Jannah Fusenig, University of Maryland,
College Park

Eric Schoute, University of Maryland, College Park
Julianne van Meerten, University of Maryland, College Park
DeLeon Gray, Michigan State University;
North Carolina State University

  Matthew McCrudden, Pennsylvania State University
Panayiota Kendeou,University of Minnesota
Diane Schallert, University of Texas, Austin
Sofie Loyens, University College Roosevelt
P. Karen Murphy, Pennsylvania State University 
Alexandra List, Pennsylvania State University
This course will provide graduate students and early career faculty with critical information about how to publish. The course will begin with an overview of the nuts and bolts of academic publishing. Following this, scholars will present detailed sessions that cover the entire publishing process—from conceptualizing studies to preparing well-crafted manuscripts targeted to relevant journals. More specifically, sessions led by top scholars will cover institutional and career fit, how to be a productive writer, finding equilibrium in academia, contemporary publishing topics and how to select appropriate journals, quality quantitative research, quality qualitative research, and ethical issues in publishing. Question-and-answer sessions will follow each presentation to allow course participants to interact with the scholars about the topics presented. Further, at the end of the course there will be a final presentation that addresses any lingering questions and concerns. Each participant will be provided with materials, including handouts and work samples that elaborate the important points shared during the course.
Sharing Your Research with the World
Recorded on June 3, 2020
Duration: 3 Hours 50 Minutes 
Jenny Grant Rankin, U.S. Department of State
(Fulbright Specialist Program) and Mensa
This course focuses on how to communicate research to large, diverse audiences. It is appropriate for participants who have researched (or are currently researching) any topic within the education field and who want their findings to reach as many people as possible in order to help as many students as possible. Participants will learn about a variety of opportunities, how to land those opportunities, and strategies to maximize the opportunities to share their work with varied audiences. The course covers branding (websites, social media, message, pitch, etc.), speaking (TED talks, conferences, media interviews, NPR/radio, etc.), and writing (book deals, journals, magazines, etc.). Sections involve audience participation, interaction, and hands-on activities to apply concepts to participants’ circumstances. Attendees will also learn about resources available to women and traditionally underrepresented groups so more diverse perspectives are represented in field dialogue. In addressing significant professional development issues (e.g., writing and speaking strategies), this course will encourage more dynamic, memorable research presentations and accessible, widespread communication of education research findings.
Introduction to Systematic Review and Meta-Analysis
Recorded on June 4, 2020 
Duration: 3 Hours 54 Minutes 
Terri D. Pigott, Georgia State University
(course director)
Amy L. Dent, University of California - Irvine

  Joshua R. Polanin, American Institutes for Research
Joseph Taylor, University of Colorado, Colorado Springs
This interactive course will introduce the basics of systematic review and meta-analysis. Topics covered include developing a research question, searching the literature, evaluating and coding studies, conducting a meta-analysis, and interpreting results for various stakeholders. Course activities will include lecture, hands-on exercises, small-group discussion, and individual consultation. The target audience includes those new to systematic review and meta-analysis as well as those currently conducting either type of project. Knowledge of basic descriptive statistics is assumed.
The Future is Here: Analyzing NAEP Process Data Using R
Recorded on June 10, 2020 
Duration: 3 Hours 31 Minutes 
Emmanuel Sikali, U.S. Department of Education
(course co-director)
Ruhan Circi, American Institutes for Research
(course co-director)
Fusun Sahin, American Institutes for Research
  Xiaying Zheng, American Institutes for Research
Juanita Hicks, American Institutes for Research
Soo Youn Lee, American Institutes for Research
Tiago A. Caliço, American Institutes for Research
This course will introduce the unique features of National Assessment of Educational Progress (NAEP) process data to researchers and provide necessary guidance on how to appropriately prepare and analyze this new data type. NAEP process data consist of time-stamped records of student actions (e.g., highlighter use, calculator use, answer selection, item navigation) within the test delivery system. These time-stamped records are collected at every part of the NAEP assessment (i.e., tutorial, cognitive section, and student questionnaire) across multiple subject areas (e.g., mathematics, reading, science). For this course, participants will use a NAEP mathematics process data file. For each student in this file, there are individual actions that the student made, while interacting with a) the items presented, b) the physical computer, and c) the testing environment.
The course will provide participants with hands-on practice training in analyzing NAEP process data using the R statistical analysis language. Participants will learn how to create new variables from process data, such as item response time, and how to conduct analysis tailored to various research questions, through a mixture of instructors’ demonstrations of data analyses and visualization. The course is designed for advanced graduate students as well as researchers in academia, the private sector, government, and nonprofit organizations who are interested in learning how to integrate response process data into their research. Participants should have at least basic knowledge of the R programming language, as well as of statistical techniques including statistical inference and clustering. Participants need access to R and RStudio. To familiarize yourself with some aspects of the NAEP assessment and get a general idea of some of the process data elements that are collected during the assessment, please explore the NAEP Grade 8 Mathematics Tutorial using this link here. Detailed instructions will be sent to participants before the course.
How to Write About Qualitative Research
Recorded on August 6, 2020  
Duration: 3 Hours 36 Minutes 
Marcus B. Weaver-Hightower, Virginia Tech
This interactive course aims to help beginning qualitative researchers—whether they are graduate students writing a qualitative dissertation or those learning qualitative methods so they can do mixed methods research—learn some of the key expectations, practices, and conventions of writing traditional qualitative research. The course focuses on writing, perhaps the least discussed topic in qualitative methods texts and courses. Participants will learn about, discuss, and practice the following key qualitative writing skills: Writing to Show You Were There; Writing About and With Qualitative Data; Writing Valid Qualitative Findings, Assertions, and Conclusions; Writing About Qualitative Methods; and Basic Revision Strategies. Although course participants can be relative beginners, they should have basic familiarity with qualitative research methodology and practices. Participants are encouraged to bring a small writing sample (or small sample of data) for group critique and discussion. The course will end with an open question-and-answer period to work on participants’ particular challenges with writing.
Empowerment Evaluation
Recorded on August 26, 2020  
Duration: 3 Hours 47 Minutes 
David M. Fetterman, Fetterman and Associates
This course will highlight how empowerment evaluation produces measurable outcomes with case examples ranging from high tech companies such as Google and Hewlett-Packard to work in rural Arkansas and squatter settlements in South Africa. Employing lecture, activities, demonstration, and discussion, the course will introduce participants to the theory, concepts, principles, and steps of empowerment evaluation as well as the technological tools to facilitate the approach. Empowerment evaluation builds program capacity and fosters program improvement. It teaches people to help themselves by learning how to evaluate their own programs. Key concepts include: a critical friend, cycles of reflection and action, and a community of learners. A dashboard is used to compare annual goals with quarterly progress.
Using Factor Analysis for Survey Design and Validation
Recorded on September 1, 2020 
Duration: 3 Hours 38 Minutes 
Katherine Picho, Howard University (course director)
Marie Plaisime, Howard University
This interactive course provides a primer on survey development and the use of factor analysis to validate surveys. It is intended for educators (including administrators) and researchers at all levels, from novice to more experienced, who are either developing, implementing, or contemplating the use of questionnaires for research, program evaluation, or educational purposes. This course expounds on exploratory factor analysis as a crucial tool in the instrument validation process. It includes interactive presentations, small-group activities to practice skills, useful resource materials, and time for discussion with the instructor. Attendees will need access to SPSS or Stata.
Co-Decolonizing Research Methods: Toward Research Sustaining Indigenous and ‘Other’ Community Engaged Ways of Knowing
Recorded on September 15, 2020 
Duration: 3 Hours 48 Minutes 
Lorri Many Rivers Johnson Santamaría, Mixteco
Indígena Community Organizing Project (MICOP)
(course director)
  Cristina Corrine Santamaria Graff, Indiana
University—Purdue University at Indianapolis
For those interested or engaged in research produced by or serving Indigenous peoples or people of Color in the United States directly or indirectly impacted by colonization, this course provides a way forward toward authentic collaboration with stakeholders and interested parties. An interactive course, it features lecture, group work, and direct interactions with Mixteco/Indígena community members who are active researchers serving their community as part of an authentic collaboration with state and county funding partners. Latinx and Black/African American parents of children with dis/abilities in Indiana will also share university/community-based co-created research efforts serving their communities. The course aims to increase participants’ opportunities to co-plan, reenvision, and co-create collaborative research opportunities with community stakeholders and organizations representative of multilingual, migrant, Indigenous, Latinx, Black/African American, and dis/ability perspectives. Participants will leave the course able to (1) reframe notions of traditional research; (2) understand the importance of sacred space and “being” with communities pre-inquiry; (3) support communities’ identification of community-serving research needs, questions, and approaches; (4) co-create thought forms by sharing traditional research methods—allowing for adaptation, change, or innovation; and (5) facilitate community-engaged research methods and efforts. The ideal audience for this course includes graduate students, active researchers, and community members such as women and underrepresented minoritized people interested in shifting power differentials in collaborative research. There are no prerequisite skills or knowledge required. Potential assignments include three readings made available by email to registrants prior to the course.

George L. Wimberly, Ph.D.
Virtual Research Learning Series, Director
For more information please contact