Graduation Year

2025

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Educational and Psychological Studies

Major Professor

Evan Dart, Ph.D.

Committee Member

Kathy Bradley-Klug, Ph.D.

Committee Member

John Ferron, Ph.D.

Committee Member

Joshua Nadeau, Ph.D.

Keywords

Progress Monitoring, School-Based Decision Making, Single-Case Design, Visual Analysis

Abstract

Research investigating the display of single-case design (SCD) data has demonstrated that graphing characteristics can influence visual analysis and rater interpretations regarding the effect of an intervention. Data-based decision making within school settings, particularly within the framework of Multi-Tiered Systems of Support (MTSS), commonly includes the use of SCD’s to support this process. Despite the push for adherence to a standard assembly for linear graphs, there is no requirement as to how these graphs should be constructed. MTSS team members are often required to make decisions about whether an intervention should be continued (or not), and thus it is important to understand whether variations in the display of the data influence these decisions. This study aimed to expand upon the current literature that highlights challenges with standards-inconsistent graphs, by considering how this may influence decision-making among school personnel working within an MTSS context. The research explored how graphing characteristics may impact visual analysis, beyond interpretations of the presence and magnitude of an effect, and how this may influence recommendations made by school personnel. Furthermore, the addition of contextual information about intervention implementation fidelity was included in this research to more closely replicate the type of information school-based MTSS team members may typically receive when asked to complete visual analysis and make recommendations for students. The study consisted of a within subject’s design and included a total of 36 participants with experience participating in a school-based decision-making team within an MTSS setting. Participants completed an online survey viewing a total of 24 graphs displaying simulated student data, including baseline and intervention data for a behavioral intervention. Each graph represented a different combination of each independent variable. Participant rating of effect presence, effect size, and recommendation were collected and analyzed. Results demonstrated significant main effects for effect size across all outcome variables. However, no significant main effects or interactions were present for graph type, and fidelity information type on participant ratings of effect presence, effect size, and recommendations. Nonetheless, directional trends were observed across the data and are described throughout. Implications of these findings in relation to the current literature are discussed.

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