PDC04: An Introduction to Hierarchical Linear Modeling for Education Researchers
Instructors: D. Betsy McCoach, University of Connecticut; Ann A. O’ Connell, The Ohio State University
Date: Friday, April 8, 8:00 a.m. – 3:45 p.m.
This course will introduce the fundamentals of hierarchical linear modeling (HLM), focusing on fundamental concepts and practical applications with very minimal emphasis on statistical theory. In addition to presenting a conceptual overview of HLM, the instructors will utilize a school-based example to demonstrate the application of HLM within an organizational framework. Participants will learn how to analyze 2-level data using HLM 7, and they will learn to interpret the results of the analyses. Instruction will consist of lecture, demonstrations of the software, and hands-on data analysis opportunities. Students should bring a laptop equipped with the free student version of HLMv7 (from www.ssicentral.com) and SPSS or another data manipulation software. The course example data will run on the student version of HLM. (Please note that there is no MAC version of the HLM software program.)
PDC16: Crafting the Story: An Introduction to Writing With Qualitative Data
Instructors: Karri A. Holley, The University of Alabama; Michael S. Harris, Southern Methodist University
Date: Saturday, April 9, 8:00 a.m. – 12:00 p.m.
In this course, participants will examine and use narrative devices inherent to the writing of qualitative research. This interactive session will be conducted in the format of a writing course. Participants will engage with transcripts from an extant research study and cast analyzed data into different report styles, using rhetorical structures common to the different styles associated with the various qualitative research designs. The goal of this course is to conceptualize writing with qualitative data as storytelling. By the end of the course, participants will be able to 1) discuss common report styles and structures in qualitative research, 2) explain the role of writer perspective and intentionality in writing, 3) describe the influence of a writer’s relationship to the intended audience, 4) define the key elements of storytelling and their relationship to qualitative research, and 5) demonstrate how these elements can be used in their own research. The course is designed for advanced graduate students and early career scholars interested in qualitative research. Participants should have a working knowledge of qualitative research, have completed at least an introductory course in the field, and have experience reading, coding, and writing from transcripts. They will be tasked with a short writing assignment before the course. Participants should bring laptops and be prepared to write and share what they have written with other participants.
PDC22: Analyzing the Civil Rights Data Collection for Education Policy Research
Instructors: Janis D. Brown, U.S. Department of Education
Date: Sunday, April 10, 8:00 a.m. – 12:00 p.m.
This course will provide graduate students, researchers, and practitioners with information on how to access and analyze the Civil Rights Data Collection (CRDC), a large-scale data set managed by the Office for Civil Rights (OCR) in the U.S. Department of Education. The CRDC is a universe collection of school districts on key education and civil rights issues in our nation’ s public schools. The data collected include student enrollment, educational programs and services, school discipline, and indicators of college and career readiness. Most data are disaggregated by race/ethnicity, sex, limited English proficiency, and disability. The course will include informational presentations, extensive demonstrations, several hands-on exercises, and group work discussions. Topics covered are: 1) an overview of the CRDC survey design; 2) demonstration of online data tools for accessing and analyzing CRDC data; and 3) sharing tricks and techniques for analyzing large-scale data sets. Participants will learn to 1) analyze CRDC data using online tools, 2) conduct statistical tests, 3) create data tables and graphs, and 4) understand how to obtain a restricted-use data license. Participants should have a general knowledge of research methods and statistics. Participants must bring their own laptop.
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The AERA Virtual Research Learning Center (VRLC) is a virtual space for students, early career and advanced scholars, practitioners, and others in the education research community to receive professional development and research capacity–building trainings.
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