Understanding Rule Conflict: What Happens When Learners Face Competing Expectations

When a learner hears “use your words” in therapy but finds that pointing works faster at home, they’re navigating competing rules—and their choices often reflect which rule has paid off more reliably. This study offers practical insight into why learners may appear inconsistent across settings and how clinicians can design environments that reduce confusion rather than blame.

What Is the Research Question Being Asked and Why Does It Matter?

This study asked a straightforward clinical question: when a person has two rules to follow that can’t both be right in the same moment, which one do they pick? The researchers focused on one likely factor—each rule has a different history of payoffs.

In real life, this looks like a learner hearing “use your AAC” in therapy but “just point” at home. Or “raise your hand” in class but “talk fast or you’ll miss out” on the playground.

This matters because many behavior plans rely on rules, prompts, and “remember to” statements. If two adults teach different rules, the learner may not be noncompliant. They may be making a normal choice based on what has paid off more often. Knowing this helps you design teaching so learners don’t get stuck between conflicting expectations.

The study also reminds us that rules and consequences work together. Even when a learner can repeat a rule, their moment-to-moment choices may still shift toward what has produced better results over time. For clinicians, this means we shouldn’t assume “they know the rule” equals “they will follow the rule”—especially when other rules have worked better in the past.

What Did the Researchers Do to Answer That Question?

They ran two lab experiments with college students using a computer task. Participants saw two buttons (left and right) and color cues (red or blue). Each color signaled which option would pay off, but the payoff rates differed. One context was “rich” (more frequent points for the correct option) and the other was “lean” (less frequent payoff).

In Experiment 1, participants received two clear rules up front—like “When it’s red, press left” and “When it’s blue, press right.” Training taught each rule in its own context, and participants had to follow each rule consistently to move on. After training, they completed a brief rule recall test to confirm they could state the rules correctly.

Then came the main test. Sometimes the screen showed both cues at once (the colors alternated quickly), creating a conflict where both rules felt relevant. Other times there was no cue at all. During these test phases, no points were available, so researchers could observe which choice participants preferred without new learning from reward.

In Experiment 2, they removed the given rules. Participants had to learn which side paid off in each color condition through experience alone. After training, they completed the same “both cues” and “no cue” tests. This let the researchers see whether the same choice pattern would emerge even without explicit instructions.

How You Can Use This in Your Day-to-Day Clinical Practice

Look for payoff history, not just attitude. When you see a learner pick one rule over another, check the reinforcement history first. In this study, when both cues were present, most people chose the option linked to the higher payoff rate during training. Clinically, if one setting delivers faster or more reliable reinforcement for a behavior, that rule may win when situations get messy. If a replacement behavior isn’t sticking across staff or settings, ask whether it’s actually the best-paying option in the learner’s daily life.

Do a “rule conflict” check during assessment. Ask caregivers: “What are the two different messages this learner hears about this situation?” and “Which one has worked better for them?” You can do this without blaming anyone. For example, one adult may reinforce “ask for a break,” while another ends demands only after problem behavior. The learner may not be choosing problem behavior because they want attention—they may be choosing the path that has produced the biggest, fastest change.

Pair rules with steady outcomes. In Experiment 1, participants followed rules strongly during training, even when the lean option sometimes produced no payoff. Rule-following can look strong in structured teaching with clear cues. But the test phase showed preference still leaned toward the richer reinforcement history when conflict arose. In practice, a learner may follow a rule perfectly in therapy but switch when the environment signals two different expectations. Build teaching that includes mixed cues and real-life distractions—not just clean table-time conditions.

Plan for missing cues. In both experiments, when there was no cue at all, choices were scattered and inconsistent. In daily practice, “no cue” might mean the visual schedule is missing, the teacher is new, the activity changes, or the learner is tired. If your program depends on a cue, teach a backup plan—like having the learner ask “What do I do?” or check a simple support (a card, a phone reminder, a posted routine). This supports independence without expecting the learner to guess correctly.

Be careful labeling behavior as “rule-governed.” The authors noted an important limitation: because the conflict test happened under extinction and was brief, we can’t be certain participants were truly choosing a rule versus repeating a learned pattern tied to reinforcement history. Avoid over-labeling behavior as rule-governed just because a learner can say the rule. Treat “rule talk” as one data point, and still track what actually happens when competing contingencies show up.

When caregivers disagree, rebalance the payoffs—not just the rule. If you only repeat “use your words” but problem behavior still reliably produces escape at home, the home rule is richer even if nobody says it out loud. Help the team make the replacement behavior the most efficient way to get needs met, while reducing reinforcement for the competing behavior in a respectful, safe way. That might mean faster break delivery for appropriate requests, smaller steps in demands, or better functional communication supports—not harsher consequences.

Consider your population carefully. The participants were college students in a computer task, not children with developmental disabilities, and reinforcers were points in a short session. Don’t assume the same pattern will appear for every learner or skill. Still, the core lesson holds: when two incompatible expectations compete, behavior often shifts toward the option with the better reinforcement history—especially when cues overlap or are unclear.

Make dignity part of your decision. If a learner is stuck between rules from different adults, your goal isn’t to force compliance. Your goal is to reduce confusion, increase choice and clarity, and make the most helpful behavior the easiest and safest option. Treat conflicting rules as a systems problem. Fix the reinforcement patterns across people—don’t “correct” the learner for choosing what has worked.

Works Cited

Ruiz Méndez, D. (2024). Toward a procedure to study rule-governed choice: Preliminary data. The Analysis of Verbal Behavior, 40, 280–305. https://doi.org/10.1007/s40616-024-00206-6