Innovative Approaches to Visual Methods in Mixed-Method Research in Education

• In Event: Analysis and Meta-Analysis of Single-Case Experimental Data: Methodological Developments

Abstract

Over the past several decades, experimental single-case time-series designs have evolved in methodological sophistication and moved beyond roots in behavior analysis to other areas of psychology, education, social sciences, and health. As methods develop, the integration of qualitative and quantitative data throughout design, analysis and reporting presents unique challenges to the single-case researcher. It is now commonplace to combine visual analysis of graphed data with adjunctive quantitative analysis. Although SCD is classified as an experimental method, a rigorous single-case design (SCD) with quantitative and qualitative methods and analysis meets the definition of mixed methods research. Single-case researchers have the task of integrating qualitative and quantitative data resulting from (a) visual analysis (level, trend, variability, overlap, and immediacy within and across adjacent experimental phases, and consistency across similar experimental phases), (b) statistical analysis, and (c) findings from social validity questionnaires and interviews that provide a measure of clinical relevance of the examined intervention. Each component has relatively well-defined procedures, but limited guidance exists to inform the integration of these various forms of data throughout the study, analysis, and reporting.
The present poster defines the conceptual logic, procedures, and proposed outcomes of integrating quantitative and qualitative data in SCD with an emphasis on describing known and novel methods for improved integration of (a) visual analysis of participant outcome and treatment fidelity data, (b) quantitative effect sizes to ascertain magnitude of intervention effects, and (c) clinical relevance of the intervention in SCD and mixed methods research. Connections will be drawn between the traditional response guided approach to SCD intervention (i.e., ongoing visual analysis of data during the study to inform decisions about experimental phases) and mixed methods research with suggestions for using well-defined visual analysis methods in the planning, documentation, analysis, and report of visually represented quantitative and qualitative data in mixed methods research in education.

Authors

• Wendy Machalicek, University of Oregon

• John M. Ferron, University of South Florida

• Tom Kratochwill

• Robert H. Horner, University of Oregon

• Joel R. Levin, The University of Arizona