For a second summer, the American Educational Research Association is offering a series of online courses for researchers on using data, software and productivity tools in research.
The Virtual Research Learning Series is composed of six individual four-hour courses taught by expert university professors in the applicable methodology. The first course in the series, on using freeware to create qualitative data visualizations, occurs on June 2 and the last, on multimodal analysis, occurs on July 8. The fee for each course is $55, and that covers access to all course materials and on-demand course recordings.
All courses start at 1 p.m. ET.
For more information, or to register, click the button below:
Qualitative Data Analysis and Dynamic Visualizations Using Freeware: Mapping, Organizing, and Visualizing | Wednesday, June 2
Instructor: Manuel Gonzalez Canche, University of Pennsylvania
Democratizing Data Science lifts computer programming restrictions and offers open software access to conduct qualitative and mixed method research. This course introduces an analytic framework and free software (Mapping, Organizing, and Visualizing Interdependent Events) for dynamically capturing the evolution of knowledge prospectively (i.e., ethnographic or extended on-site observations) or retrospectively (i.e., interviews, essays, social media posts).
Why Aren’t You Writing? Clearing Obstacles to Productivity | Tuesday, June 8, 2021
Instructor: Sharon Zumbrunn, Virginia Commonwealth University
Appropriate for graduate students and seasoned academics, this hands-on course will be a straightforward guide to helping participants begin to understand and overcome the psychological, emotional, and logistical hurdles that can get in their way of being productive writers. Specifically, this course will intertwine a discussion of the research underlying the ways academic writers often sabotage their success with practical strategies designed to help session participants build a healthier relationship with writing to ultimately write more with less pain.
Using R Software for Item Response (IRT) Model Calibrations | Tuesday, June 15, 2021
Instructors: Ki L. Cole, Oklahoma State University (course director); Insu Paek, Florida State University; Sohee Kim, Oklahoma State University
This interactive training course will introduce the concepts of unidimensional IRT models and provide instruction, demonstration, and hands-on opportunities of using the free R software to estimate commonly used IRT models. Participants will receive a discount code for Using R for Item Response Theory Model Applications, written by the course instructors. The target audience for this course includes graduate students, practitioners, and researchers interested in advancing their knowledge of IRT and enhancing skills of using R to do IRT analysis. A basic understanding of IRT is highly recommended.
Analyzing Large-Scale Assessment Data Using R | Tuesday, June 22, 2021
Instructors: Emmanuel Sikali, National Center for Education Statistics (course director); Paul Bailey, American Institutes for Research; Ting Zhang, American Institutes for Research; Martin Hooper, American Institutes for Research; Michael Lee, American Institutes for Research; Yuqi Liao, American Institutes for Research
This course will introduce the unique design features of large-scale assessment data and provide guidance in data analysis strategies, including the selection and use of appropriate plausible values, sampling weights, and variance estimation procedures (i.e., jackknife approaches). This course is designed for individuals in government, universities, private sector, and nonprofit organizations who are interested in learning how to analyze large-scale assessment data with plausible values. Participants should have at least basic knowledge of R software as well as statistical techniques.
Designing Adequately Powered Cluster and Multisite Randomized Trails to Detect Main Effects, Moderation, and Mediation | Wednesday, July 7, 2021
Instructors: Nianbo Dong, University of North Carolina at Chapel Hill; Benjamin Kelcey, University of Cincinnati; Jessaca Spybrook, Western Michigan University
The purpose of this workshop is to train researchers and evaluators how to plan efficient and effective cluster and multisite randomized studies that probe hypotheses concerning main effects, mediation, and moderation. Participants will be introduced to the free PowerUp! software programs designed to estimate the statistical power to detect mediation, moderation, and main effects across a wide range of designs. The target audience includes researchers and evaluators interested in planning and conducting multilevel studies that investigate mediation, moderation, or main effects.
Multimodal Analysis and Social Semiotics for Qualitative Analysis in Educational Research | Thursday, July 8, 2021
Instructors: Mary McVee, University at Buffalo, SUNY; Ryan Rish, University at Buffalo, SUNY; Angel Lin, Simon Fraser University; Qinghua Chen, Simon Fraser University
This course introduces scholars to multimodal analysis via social semiotics using diverse perspectives from multimodality and narrative, frame analysis, and nexus analysis. Course objectives include introduction to social semiotics and multimodality, basic techniques in analysis, and considerations of the role of theory. The target audience is graduate students, early career scholars, and advanced researchers who may have limited knowledge of multimodality and social semiotics and seek to learn about theories and analysis related to multimodality.