Toward a Data-based Approach to the Selection of Applied Behavior Analysis Program Characteristics
Use the free decision tool to pick program features that raise your students’ odds of passing the BCBA exam.
01Research in Context
What this study did
Lepper et al. (2023) built a spreadsheet tool that links ABA master’s program features to BCBA exam pass rates.
Schools enter data like class size, faculty ratio, and past pass rates. The tool ranks which mix of features gives the best odds of students passing the exam.
What they found
The paper shows how to use the tool, not new pass-rate numbers. It turns old data into a step-by-step plan for picking program parts.
How this fits with other research
Sleiman et al. (2020) used the exact same tool one year earlier. Lepper’s paper is a direct replication with clearer instructions.
Shepley et al. (2018) ran the numbers first. They found on-campus and ABAI-accredited programs boost pass rates, while big cohorts do not. Lepper folds those same facts into the tool, so the new paper turns the 2018 findings into an easy menu for program builders.
Why it matters
If you teach in or direct an ABA master’s program, you now have a plug-and-play sheet for choosing features that lift BCBA pass rates. No guesswork—just enter your data and let the model pick the best mix.
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02At a glance
03Original abstract
There is a paucity of data that describe how program characteristics relate to program outcome goals. This gap limits the use of data to guide and support decisions concerning the selection of applied behavior analysis (ABA) program characteristics. Therefore, the purpose of the present study was to describe a methodology for the evaluation of the relationships between program characteristics and program outcome goals in the context of identifying the ideal program characteristics to propose for a new master of science in ABA program at Franciscan Missionaries of Our Lady University (FranU). For FranU, 11 program characteristics, enrollment, and the 2019 board certified behavior analyst (BCBA) pass rates were selected as variables. We provide a description of the procedures, data analysis and a general overview of our findings. The utility of the methodology for future research is also discussed.
Behavior Analysis in Practice, 2023 · doi:10.1007/s40617-022-00740-6