May 2024
The 2024 AERA Virtual Research Learning Series will begin on June 4. This webinar series includes four professional development and training courses designed to increase research knowledge and expand research capacity. Expert instructors will share knowledge across multiple topics including quantitative and qualitative research methods, statistical techniques, using large-scale datasets, and implementing artificial intelligence in education research. The series runs through July 2.
All courses will provide dynamic instruction with active discussion, access to course materials, and Q&A with participants. The cost of each course is $40 for AERA members and $55 for non-members. Registration includes not only the four-hour real-time class experience but also continued on-demand access to the recorded course through the AERA Virtual Research Learning Center.
“We are pleased to once again offer a strong series of high-quality professional development courses, led by an excellent group of instructors,” said AERA Executive Director Felice J. Levine. “Graduate students, postdoctoral scholars, and researchers who are interested in enhancing their research skills will find these training opportunities valuable.”
The 2024 courses include:
RL2024-1: Causal Moderated Mediation Analysis—A Causal Investigation of Heterogeneity in Mediation Mechanisms: Methods and Software Tuesday, June 4, 1–5 pm ET Instructor: Xu Qin (University of Pittsburgh)
The purpose of this course is to introduce the definition, identification, estimation, and sensitivity analysis of causal moderated mediation effects under the potential outcomes framework. Participants will also learn to apply a user-friendly R package to conduct the analysis and visualize results.
RL2024-2: Artificial Intelligence (AI) Uses in Education Research Tuesday, June 11, 1–5 pm ET Instructors: Min Sun (University of Washington), Lavi Aulck (University of Washington)
This course will focus on preparing education researchers to use state-of-the-art tools in artificial intelligence (AI) and machine learning in educational contexts. It will cover topics such as applications of AI in education for prediction and classification, model evaluation via performance metrics, human feedback in AI model development, randomized control trials, and cost-benefit analysis.
RL2024-3: Understanding and Using Nationally Representative Survey Data from the RAND American Educator Panel Thursday, June 27, 1–5 pm ET Instructors: Julia Heath Kaufman (RAND Corporation), Sy Doan (RAND Corporation), Kate Brittain (Kitamba)
This course provides faculty, students, and other researchers with a primer on use and analyses of the many free teacher and principal survey datasets available through the RAND American Educator Panels (AEP).
RL2024-4: Putting Feelings Where They’re Useful: Using Emotions as Data in Qualitative Analysis Tuesday, July 2, 1–5 pm ET Instructors: Hilary Lustick (University of Massachusetts – Lowell), Abeer Hakouz (University of Massachusetts – Lowell), Xiaoye Yang (University of Massachusetts – Lowell)
In this course, instructors will review the emotion coding technique, which applies a set of reflexive questions to a chunk of data (Lustick, 2021), and will examine some of the complexities of naming and reflecting on emotions during data analysis.
Early registration is encouraged. The full course descriptions indicate whether participants will need access to any software.
Questions about the courses can be directed to profdevel@aera.net.