AERA Announces Annual Meeting Professional Development Courses—Register Now
AERA Announces Annual Meeting Professional Development Courses—Register Now
 
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January 2021

AERA has announced four professional development courses that will be held immediately following the 2021 Virtual Annual Meeting, on April 13–16. All courses run from 1:00 p.m. to 5:00 p.m. ET. Led by an expert faculty of researchers and scholars, these four-hour virtual courses are designed at various levels to reach graduate students, early career scholars, and other researchers who seek to increase their knowledge and enhance their research skills.

To maximize access to these courses for education researchers during these challenging times, AERA is charging only a modest fee of $35 each for Annual Meeting registrants who are AERA members and $55 for Annual Meeting registrants who are non-members. Professional development courses can be added to new or existing Annual Meeting registrations in the My AERA section of the AERA website. Course registration for non-Annual Meeting attendees will open the week of February 1 on the AERA website. The fee for non-meeting attendees is $55.

The courses focus on skill development in qualitative research methods, meta-analysis, multilevel modeling, and data analysis and visualization. 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 (VRLC).

George Wimberly, AERA’s director of professional development, designed and leads this series. Click the links below to jump to each course description.

PDC-01: Teaching and Learning Qualitative Research Methods Principles Through Popular Film Clips
Tuesday, April 13
Instructor: Johnny Saldana (Arizona State University)

This four-hour course provides students and instructors of qualitative research courses pedagogical strategies for using popular film clips to teach and learn selected principles and methods of inquiry. Mediated instruction has a longstanding tradition in K–12 classrooms, and the power of “edutainment” in our digital and performative culture should not be underestimated or dismissed by university professors for advanced undergraduate and graduate-level classrooms. Popular film viewing offers novelty and engagement in traditional learning settings, and holds the potential to vividly instruct as well as entertain. Popular film clips can be used to (1) introduce qualitative research topics; (2) illustrate basic principles and techniques of inquiry; (3) generate classroom discussion and reflection; (4) clarify misunderstood concepts; (5) function as referential mnemonics; and (6) teach selected content more effectively than traditional classroom pedagogy. Examples of film scenes and their topics include: Miss Evers’ Boys (research ethics); Kinsey (interviewing); and Experimenter (theory). At the conclusion of the course, participants will have (1) viewed over 20 film clips related to qualitative research methods principles; (2) participated in related learning activities (e.g., discussion, categorizing, assertion development, thematic analysis); (3) reviewed and discussed how selected learning strategies can precede and follow popular film clip viewing; (4) shared other film and media titles for recommended use with students; and (5) learned how to access related media and software for their own teaching resource development.

PDC-02: Advanced Meta-Analysis
Wednesday, April 14
Instructors: Terri Pigott (Georgia State University), Ryan Williams (American Institutes for Research), Tasha Beretvas (The University of Texas at Austin), and Wim Van Den Noortgate (Katholieke Universiteit Leuven)

This course will introduce advanced methods in meta-analysis. Topics covered include the computation of effect sizes from complex research designs; models for handling multiple effect sizes per study (dependent effect sizes) and exploring heterogeneity; power analysis in meta-analysis; the use of meta-analysis structural equation modeling (MASEM); and an introduction to single-case experimental design meta-analysis. The statistical package R will be used to conduct the statistical techniques discussed. Participants are encouraged to bring their own research in progress to the course. The activities will include lecture, hands-on exercises, and individual consultation. This course is designed to follow the course “Introduction to Systematic Review and Meta-Analysis” recorded by the instructors in prior AERA Virtual Research Learning Series (See RL-4, “Introduction to Systematic Review and Meta-Analysis” at  https://www.aera.net/Professional-Opportunities-Funding/AERA-Virtual-Research-Learning-Series2020). The target audience consists of researchers with experience in systematic review and meta-analysis who are interested in learning advanced methods for meta-analysis. Knowledge of basic descriptive statistics, systematic review, and basic meta-analysis is assumed. Students are required to bring a laptop computer.

PDC-03: Multilevel Modeling with International Large-Scale Assessment Databases Using the HLM Software Program
Thursday, April 15
Instructors: Amy Rathbun (American Institutes for Research), Francis Howard L. Huang (University of Missouri), Sakiko Ikoma (American Institutes for Research), Sabine Meinck (International Association for the Evaluation of Educational Achievement), Bitnara Jasmine Park (American Institutes for Research), and Yuan Zhang (American Institutes for Research)

This course will teach participants how to conduct multilevel modeling (MLM) with data from international large-scale assessments (ILSAs) such as TIMSS, PIRLS, and PISA. The content of the course will include an overview of the ILSAs and presentations on the design of these studies and implications for MLM analysis. Participants will learn how to specify two-level models using the HLM software program and also learn about model comparison, centering decisions and their consequences, and available resources for doing three-level models. Time will be allotted for participants to work on practice exercises, with several instructors available to mentor and answer questions. Participants should have a solid understanding of OLS regression and a basic understanding of MLM. Prior experience using a statistical software program, such as Stata, R, or SPSS, is helpful. Prior knowledge about ILSAs or prior experience using the respective databases or HLM software is not required. To participate fully in the hands-on exercises, participants should bring their own laptops with HLM software (a free student version is available).

PDC-04: Advancing Qualitative and Mixed Methods Data Collection and Analysis with Visual Displays
Friday, April 16
Instructor: Elizabeth Creamer (Virginia Polytechnic Institute and State University)

The use of visual displays that include both qualitative and quantitative data is widely accepted in mixed methods research. Led by the author of the textbook An Introduction to Fully Integrated Mixed Methods Research, this interactive course is designed to explore uses of visual displays in qualitative and mixed methods research. It expands ideas about creative uses of joint displays by exploring their use as a graphic elicitation technique to facilitate authentic data collection, including with vulnerable populations. An equal amount of time will be devoted to considering how a joint display can facilitate meaningful integration of data during analysis. A range of examples using visual methods will be presented, including photo mapping, timelining, and matrix mapping. Participants will generate ideas about the ways that a visual data display might be useful in their own project. The audience for the course includes those with both introductory and more advanced knowledge of qualitative and mixed method approaches. A variety of supplemental materials will be available to registrants online.

Early registration is encouraged. Questions about the courses should be directed to profdevel@aera.net.

 
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