Modeling Behavioral Persistence with Resurgence as Choice in Context (RaC2): A Tutorial

Laureano et al. (2023) wrote a step-by-step guide. The guide shows you how to build an Excel sheet that predicts when problem behavior will pop back up after you stop reinforcing the replacement skill.

The sheet uses the matching law. You enter how often the new skill is reinforced and how hard each response is. The sheet then graphs the expected resurgence.

The paper is a tutorial, not an experiment. It gives you the formulas and a free Excel file. Once built, the model tells you the exact session when old behavior is likely to return.

Wilson et al. (2016) showed that high effort kills resurgence in children. The RaC2 model lets you plug in that same effort value and watch the relapse line drop to zero on the graph.

Alessandri et al. (2015) proved that negatively reinforced behavior resurges in humans. RaC2 turns that finding into a calculator you can use before you start extinction.

Novak et al. (2020) showed that desirable workplace behavior can also renew. RaC2 extends the same math to any response, good or bad, once contingencies shift.

You can now preview relapse before it happens. Plug your case data into the Excel sheet, adjust reinforcement rate or response effort, and see which tweak keeps problem behavior flat. Use the curve to decide when to add extra reinforcement or increase effort, then show the graph to parents and teachers so they know what to expect.