From CEC Today, Winter 07

Dealing with Noncompliance in the Classroom

-By Katie E. Hildebrand, Youjia Hua, and David L. Lee

As a classroom teacher, you’ve probably heard the following statement from a grumbling student, “I don’t feel like doing this!” Teachers often have to take time away from instruction or other important tasks to deal with students’ noncompliant behaviors. Here is an example of a technique you may use to deal with noncompliance in the classroom.

Let’s say you have a student in your class, Daniel, who has difficulty staying on-task. More specifically, Daniel engages in noncompliant behaviors during transitions and independent seatwork. He has a hard time adjusting back to the classroom environment after recess, and it takes him several minutes to settle down. This problem is compounded by the fact that when Daniel is given independent work to complete, he often refuses to begin or completes only the first few questions before engaging in inappropriate behaviors (e.g., wandering around the room, talking with neighbors, or staring out the window) that can disrupt other students.

Students like Daniel typically lag behind their peers academically, and it is our job to help them catch up. Unfortunately, these compliance issues can impact achievement. What starts out as a “won’t do” problem (performance deficit) soon becomes a “can’t do” problem (skill deficit). In other words, if Daniel doesn’t practice and become fluent in skills he can perform, he will have difficulty learning more challenging skills down the road. Most teachers rely on consequence-based methods to deal with compliance issues. While appropriate consequences can be effective, they must be applied after the inappropriate behavior occurs. What is needed is a way to prevent noncompliance to facilitate academic transitions.

High Probably Request Sequences
High-probability request sequences is a preventative technique that can be used to increase student compliance. For this technique, the teacher presents a series of brief (three-five seconds) preferred tasks just prior to a student’s non-preferred task. Teachers give verbal praise after the student complies with each request or task. The additional preferred (high-probability) tasks reinforce the student’s compliant response and result in his or her increased compliance with non-preferred (low probability) requests.
Let’s go back to Daniel. When Daniel is having difficulty transitioning from lunch to math class, the teacher might say, “Daniel, give me five. Give me ten. Touch your nose” (tasks with a high-probability of compliance). “Take out your math book” (task with a low-probability of compliance). The three high-probability requests increase the level of reinforcement for the entire request sequence and result in increased student compliance. Now, the lesson is over, and students begin to work independently. Daniel has difficulty staying on-task during independent seatwork. He often knows how to complete the assigned tasks (e.g., addition with regrouping problems) but remarks, “I am not doing this!” In this case, the teacher may place a series of two-three brief, preferred (high-probability) tasks just prior to each non-preferred task. For example, if 3 + 3 digit addition often resulted in student noncompliance, the teacher could add a series of 1 + 1 digit problems. It looks like this:

Getting Students Started on High Probability Request Sequences
Starting high probability request sequences is quite simple. The first step is to determine the student’s low-probability task. This is the task for which the student is typically noncompliant. Second, determine the high-probability task, a task the student prefers doing. To identify these tasks, give the student a preference assessment. Pair two tasks together for five to 10 trials and ask the student to pick and complete one. High-probability tasks are those the student selected at least 80 percent of the time. Once you have established a high-probability task, or several high-probability tasks, consider the following:

·                     Tasks should be brief and easy, so that they can be interspersed between low-probability tasks.

·                     Set the materials up ahead of time. 

·                     Ensure the low-probability task immediately (i.e., within a 10 second time period) follows the high-probability tasks. 

·                     If the student does not continue to engage in the low-probability request, determine new high-probability requests. 

·                     High-probability requests may need to be changed, as they may no longer be reinforcing for the student. 

·                     Collect data and monitor student progress. 

·                     Fade the intervention.

·                     Don’t use high-probability sequences while the student is engaging in noncompliant behaviors. Use it to prevent noncompliance.

David L. Lee is a professor at laceName w:st="on">PennsylvanialaceName> laceType w:st="on">StatelaceType> laceType w:st="on">UniversitylaceType>. Katie Hildebrand and Youjia Hua are doctoral candidates at laceName w:st="on">PennsylvanialaceName> laceType w:st="on">StatelaceType> laceType w:st="on">UniversitylaceType>. Lee and Hildebrand are members of the Pennsylvania CEC