2019 Methods Workshop
Presented by the Learning Performance Research Center
Additional sponsorship by Educational Psychology, Prevention Science, and Psychology
May 9-10, 2019 – 9:00 a.m. to 5:00 p.m.
About the Workshop: Mixed Methods
Mixed methods research can be defined as “research in which the investigator collects and analyzes data, integrates the findings, and draws inferences using both quantitative and qualitative approaches” (Tashakkori & Creswell, 2007, p. 4). A high-quality mixed methods research study consists of more than just the use of quantitative and qualitative strands in the same study. A defining feature of mixed methods research is that the researcher integrates the quantitative and qualitative strands. Integration occurs when an investigator intentionally combines quantitative and qualitative approaches in a study such that their combination provides a more comprehensive understanding of the topic. When and how the two strands are integrated plays an essential role in establishing the quality of the study design, and ultimately of the quality of the inferences and conclusions drawn from the study.
This two-day seminar will provide a thorough introduction to mixed methods research. We will begin by distinguishing mixed methods from mono-method and multiple-method research and the logic behind mixing quantitative and qualitative methods. Then, we will discuss integration and how researchers can integrate quantitative and qualitative strands in a study and how this can influence the validity of the inferences drawn from the findings. Specifically, we will discuss and evaluate mixed methods research designs, how integration can be achieved at different stages of the various designs, effective ways to integrate data analysis procedures, and how to represent and interpret integrated results. Further, we will discuss issues related to validity and transferability in mixed methods. The seminar will be highly interactive and numerous illustrative examples will be provided. The seminar is designed to be accessible to individuals who seek to become more familiar with mixed methods.
Presenter: Dr. Matthew T. McCrudden
Matthew T. McCrudden is an Associate Professor of Educational Psychology at Pennsylvania State University. His program of research is focused on cognitive processes that occur during reading and subsequent comprehension. Specifically, his research has investigated the effects of task (e.g., pre-reading instructions), learner (e.g., knowledge, beliefs, verbal ability), and text (e.g., visual displays, seductive details, refutational text structure) variables on the cognitive processes that students use during reading and the products of those processes (e.g., memory, transfer, written arguments). He has used a variety to methods to investigate topics in this area. He has published mixed methods research articles in the Journal of Mixed Methods Research, Journal of Educational Psychology, Contemporary Educational Psychology, Journal of Autism and Developmental Disorders, and Metacognition & Learning. He is currently an associate editor for Contemporary Educational Psychology and serves on the editorial board of five additional journals (Journal of Educational Psychology, Learning and Instruction, Educational Psychology Review, Discourse Processes, and Journal of Experimental Education). He was co-editor with Gwen Marchand and Paul Schutz for a special issue on mixed methods research in educational psychology in the journal Contemporary Educational Psychology.
Remote (videoconference): $30
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2017 – Roy Levy, Arizona State University – Foundations of Bayesian Statistical Modeling
2016 – Todd D. Little, Texas Tech University – Measurement, design, and analysis issues in longitudinal modeling with a particular focus on the longitudinal CFA model as the basis for both panel and latent growth curve modeling.
2015 – Greg Hancock, University of Maryland – Second Course in Structural Equation Modeling
2014 – Bethany Bray, Penn State University – An Introduction to Latent Class and Latent Profile Analysis
2013 – Greg Hancock, University of Maryland – A First Course in Structural Equation Modeling