How To: Increase Motivation in Students: High-Probability Requests

Learning Spark Blog: Jim WrightNon-compliance is a frequent source of problem classroom behavior--driven by student attempts to escape or avoid challenging academic tasks (Packenham, Shute & Reid, 2004). For instance, when transitioning between educational activities a work-avoidant student may stall in beginning the next assignment. Or, during independent assignments, that same student may run out the clock by dawdling between work items. To increase compliance and work completion, teachers should identify strategies that prevent off-task behaviors but must also continue to hold students accountable for attaining rigorous academic standards.

 

High-probability requests are one feasible classroom technique that can be effective in motivating students to engage in assigned classwork (Lee, 2006). The teacher first identifies an academic activity in which the student historically shows a low probability of completing because of non-compliance.  The teacher then embeds within that low-probability activity an introductory series of simple, brief 'high-probability' requests or tasks that this same student has an established track record of completing (Belfiore, Basile, & Lee, 2008).

 

As the student completes several embedded high-probability tasks in succession, he or she builds 'behavioral momentum' in responding that increases the likelihood that the student will apply full effort when encountering the 'main event'--the more challenging, low-probability activity. (See the table Use of High-Probability Requests to Increase Student Compliance: Examples from Research Studies for descriptions of how high-probability requests have been used successfully in school settings.)

 

Use of High-Probability Requests to Increase Student Compliance: Examples from Research Studies

Transitioning within academic tasks: Letter/word copying (Lee et al., 2004).  During independent work, two 2nd-grade students were directed to copy a letter several times from a model (a preferred, high-probability task) before being asked to copy a whole word from a model (less-preferred, low-probability task). 

 

Transitioning within academic tasks: Math computation (Lee et al., 2004). Three students with IEPs from intermediate grades were presented with flashcards containing math computation problems. The students were to read off and solve each problem, flip the card over to check the actual answer against their solution, and then advance to the next card. For the activity, the teacher first created a series of cards containing low-probability computation problems that were less-preferred because of their difficulty. Then, before each low-probability problem, the teacher inserted flashcards with three easy (more-preferred, high-probability) computation problems.

 

Transitioning between academic tasks: Independent math assignment (Wehby & Hollahan, 2000). This study focused on a middle-school student who often would not initiate independent math assignments.  The teacher compiled a list of high-probability requests related to the independent math assignment that the student would typically respond to--e.g., 'write your name on the worksheet", "pick up your pencil", "take out a sheet of paper for the assignment", "look over the first problem". At the start of the independent seatwork activity, the teacher approached the student and randomly selected and delivered 3 requests from the high-probability list. If the student ignored a request, the teacher would simply deliver another from the list until the student had successfully complied with 3 high-probability requests. Then the teacher delivered the less-preferred, low-probability request: "Begin your independent assignment."

Use of high-probability requests offers the twin advantages of motivating students while encouraging high academic standards. Students can find the experience of completing simple, high-probability tasks to be intrinsically reinforcing--which fuels the behavioral momentum that gives this strategy its power (Lee et al., 2004). At the same time, this approach offers teachers a means of holding non-compliant students to the same high academic expectations as their more cooperative classmates (Belfiore et al., 2008).

 

A potential instructional advantage of the high-probability request strategy should also be noted. Research suggests that student retention of learned material is heightened if that material is reviewed at intervals of several months or more from the initial learning (Pashler et al., 2007). If teachers are able to fold previously learned academic material (e.g., math computation facts; course vocabulary items) into high-probability requests, they can both boost student work compliance and promote retention of essential skills or knowledge.

 

Here are more detailed teacher guidelines from Lee (2006) for embedding high-probability requests to build behavioral momentum sufficient to motivate students to tackle less-preferred, low-probability academic activities:

  1. Identify incidents of non-compliant behavior. The teacher notes academic work-situations that initially have a low probability for completion because of student non-compliance (e.g., writing a journal entry; completing a worksheet with reflective questions tied to a reading assignment). The teacher also determines whether non-compliance in each situation occurs within that task or in transitioning to that task.
  2. List high-probability tasks. Next, the teacher generates a list of high-probability tasks that the student is likely to comply with. These tasks should be brief (i.e., take 5 seconds or fewer to complete) and should logically link to the low-probability activity. For example, if the low-probability event is getting the student to start the writing of a journal entry (transitioning between academic activities), easy, high-probability tasks associated with beginning the writing task might include 'organize your writing materials',  'write a title', and  'list 3 ideas for the journal entry'. If the low-probability event is having the student complete a worksheet with reflective questions tied to an assigned reading (within-task), sample high-probability tasks associated with the worksheet could include questions asking the student to 'copy the title of this reading', or 'write down one interesting vocabulary term from the first paragraph'.
  3. Create activities with embedded high-probability tasks. The teacher then reworks the low-probability work-situation to embed within it a series of high-probability tasks. If the target is to get the student to transition efficiently from one activity to another, the teacher inserts 3 high-probability requests at the start of the activity to create behavioral momentum. If the goal is to prod the student to efficiently complete an independent assignment without hesitating between items, the teacher inserts 3 high-probability requests before each challenging item on the assignment. 
  4. Introduce the activities. The teacher rolls out the activities, now retooled to include embedded high-probability tasks or requests. The teacher is careful, when presenting directives aloud to the student, to pace those directives briskly: letting no more than 10 seconds elapse between student completion of one request and teacher delivery of the next request. The teacher should also monitor the student's performance. If the student does not comply quickly with selected high-probability requests, the teacher should replace those requests on future assignments with others that elicit prompt compliance.

The guidelines offered here demonstrate how strategic use of high-probability requests can generate behavioral momentum and prevent compliance problems with individual students. However, teachers may also be able to creatively use high-probability sequences to motivate whole groups or even an entire class. For example, an instructor might decide to intersperse  3 'easy' (high-probability) items between each 'challenge' item on a math computation worksheet to be assigned to all students for independent seatwork. Or a teacher may routinely introduce in-class writing assignments by first verbally directing students to 'take out paper and pen', 'write your name on the paper', and 'copy this journal topic onto your paper'. The crucial factor in group use of high-probability sequences is that the teacher accurately identify what tasks are indeed motivating and likely to build behavioral momentum among the majority of students.

 

Identify incidents of non-compliant behavior. The teacher notes academic work-situations that initially have a low probability for completion because of student non-compliance (e.g., writing a journal entry; completing a worksheet with reflective questions tied to a reading assignment). The teacher also determines whether non-compliance in each situation occurs within that task or in transitioning to that task.

List high-probability tasks. Next, the teacher generates a list of high-probability tasks that the student is likely to comply with. These tasks should be brief (i.e., take 5 seconds or fewer to complete) and should logically link to the low-probability activity. For example, if the low-probability event is getting the student to start the writing of a journal entry (transitioning between academic activities), easy, high-probability tasks associated with beginning the writing task might include 'organize your writing materials',  'write a title', and  'list 3 ideas for the journal entry'. If the low-probability event is having the student complete a worksheet with reflective questions tied to an assigned reading (within-task), sample high-probability tasks associated with the worksheet could include questions asking the student to 'copy the title of this reading', or 'write down one interesting vocabulary term from the first paragraph'.

Create activities with embedded high-probability tasks. The teacher then reworks the low-probability work-situation to embed within it a series of high-probability tasks. If the target is to get the student to transition efficiently from one activity to another, the teacher inserts 3 high-probability requests at the start of the activity to create behavioral momentum. If the goal is to prod the student to efficiently complete an independent assignment without hesitating between items, the teacher inserts 3 high-probability requests before each challenging item on the assignment.

Introduce the activities. The teacher rolls out the activities, now retooled to include embedded high-probability tasks or requests. The teacher is careful, when presenting directives aloud to the student, to pace those directives briskly: letting no more than 10 seconds elapse between student completion of one request and teacher delivery of the next request. The teacher should also monitor the student's performance. If the student does not comply quickly with selected high-probability requests, the teacher should replace those requests on future assignments with others that elicit prompt compliance.

References

  • Belfiore, P. J., Basile, S. P., & Lee, D. L. (2008). Using a high probability command sequence to increase classroom compliance: The role of behavioral momentum. Journal of Behavioral Education, 17, 160-171.
  • Lee, D. L. (2006). Facilitating transitions between and within academic tasks: An application of behavioral momentum. Remedial and Special Education, 27, 312-317.
  • Lee, D. L., Belfiore, P. J., Scheeler, M. C., Hua, Y., & Smith, R. (2004). Behavioral momentum in academics: Using embedded high-p sequences to increase academic productivity. Psychology in the Schools, 41, 789-801.
  • Packenham, M., Shute, R., & Reid, R. (2004). A truncated functional behavioral assessment procedure for children with disruptive classroom behaviors. Education and Treatment of Children, 27(1), 9-25.
  • Pashler, H., Bain, P., Bottge, B., Graesser, A., Koedinger, K., McDaniel, M., and Metcalfe, J. (2007) Organizing instruction and study to improve student learning. Washington, DC: National Center for Education Research, Institute of Education Sciences, U.S. Department of Education. Retrieved from http://ncer.ed.gov.
  • Wehby, J. H., & Hollahan, M. S. (2000). Effects of high-probability requests on the latency to initiate academic tasks. Journal of Applied Behavior Analysis, 33, 259–262.