Issues and Improvements in the Visual Analysis of A-B Single-Case Graphs by Pre-Service Professionals

Abstract

Professionals working with individuals at risk for, or with, disabilities are required by federal legislation to select, implement, and formatively and summatively evaluate the effectiveness of evidence-based practices in typical settings. Although multiple resources related to graph construction and visual analysis are available in the literature, studies on training pre-service and in-service professionals to visually analyze data are lacking. The purpose of this study was to evaluate a multi-component visual analysis training for pre-service professionals enrolled in a behavior management course. The training explained the importance of graphing and visually analyzing data, taught participants how to visually analyze data, and included guided practice visually analyzing sample A-B graphs. Results indicated that participants were likely to display difficulties visually analyzing complex data paths and, following the training, were able to increase their accuracy of visual analysis. Limitations and implications for future research and pre-service and in-service training are discussed.

Assessing Consistency in Single-Case Alternation Designs

“…This concurs with the SCED tradition (e.g., Fahmie & Hanley, 2008;Lane & Gast, 2014;Miller, 1985;Parker et al, 2006;Parsonson & Baer, 1978) and with the fact that all methodological quality appraisal scales require visual analysis but not all require statistical analysis for evaluating effects (Heyvaert et al, 2015). In the presentation of how visual analysis is to be performed (Kratochwill et al, 2010;Lane et al, 2019;Ledford et al, 2019;Maggin et al, 2018), the focus is put on six data features. Three of these data features (level, trend, variability) can be assessed within each phase and they can also be used when comparing adjacent phases, whereas two features (overlap and immediacy of effect) refer necessarily to a comparison across adjacent phases.…”

“…Regarding the demonstration of effects, several authors coincide on the importance of visual analysis (Kratochwill et al, 2010;Lane et al, 2019;Ledford et al, 2019;Maggin et al, 2018). This concurs with the SCED tradition (e.g., Fahmie & Hanley, 2008;Lane & Gast, 2014;Miller, 1985;Parker et al, 2006;Parsonson & Baer, 1978) and with the fact that all methodological quality appraisal scales require visual analysis but not all require statistical analysis for evaluating effects (Heyvaert et al, 2015).…”

Monte Carlo Simulations to Develop Guidelines for the Use of Single-Case Designs: A Tutorial

“…To keep it simple, the report focused on the CDC method, which has been the topic of multiple studies in JABA. Should behavior analysts pursue their efforts in improving visual inspection (e.g., Ford et al, 2020;Lane et al, 2021;Wolfe et al, 2019;Wolfe & Slocum, 2015) or should they focus on developing novel methodologies (e.g., Lanovaz & Hranchuk, 2021;Manolov & Vannest, 2019)? The best approach to analyzing single-case data probably remains unknown, but it is important to rely on data to make informed decisions.…”

Defining and assessing immediacy in single-case experimental designs

“…Similar to this broader definition, several authors (Barton et al, 2019;Gage & Lewis, 2013;Haegele & Hodge, 2015;Horner & Odom, 2014;Kennedy, 2005;Spear et al, 2013) mention all three data aspects: level, trend, variability when referring to immediacy. In contrast, Lane et al (2021) only mention level and trend. Similarly, Levin et al (2021) refer to two kinds of immediate effects: an immediate abrupt effect (change in level) and an immediate gradual effect (change in trend).…”