Effects of computer‐based training on procedural modifications to standard functional analyses
One day of computer training gives graduate students the chops to modify flat-line functional analyses.
01Research in Context
What this study did
Schnell and colleagues built a one-day computer course. It teaches graduate students when to change a functional analysis that shows no clear pattern.
Students clicked through cases, chose next steps, and got instant feedback. The team tested them before, right after, and again weeks later.
What they found
Scores jumped right after the course and stayed high on new cases and follow-up tests. A single day of screen practice readied the students to tweak undifferentiated FAs.
How this fits with other research
Lloveras et al. (2022) later matched the result with remote group BST. Everyone reached mastery without computers, showing the skill can be taught live or online.
Higbee et al. (2016) used the same computer style to teach DTI instead of FA changes. Both studies saw strong gains, so the format works across tasks.
O'Grady et al. (2021) pitted computer against lecture for graph reading. Both beat no training, backing the idea that short tech lessons beat nothing at all.
Why it matters
You no longer need a full semester to prep students on FA changes. Hand them Schnell’s module, or run Lloveras’ remote BST, and they’re ready. Pick the mode that fits your site—both work.
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02At a glance
03Original abstract
Few studies have evaluated methods for training decision-making when functional analysis data are undifferentiated. The current study evaluated computer-based training to teach 20 graduate students to arrange functional analysis conditions, analyze functional analysis data, and implement procedural modifications. Participants were exposed to training materials using interactive software during a 1-day session. Following the training, mean scores on the posttest, novel cases probe, and maintenance probe increased for all participants. These results replicate previous findings during a 1-day session and include a measure of participant acceptability of the training. Recommendations for future research on computer-based training and functional analysis are discussed.
Journal of Applied Behavior Analysis, 2018 · doi:10.1002/jaba.423