Elementary students with or at risk of emotional and behavioral disorders (EBD) often experience failure and frustration in mathematics. With high-quality instruction and motivation strategies, such as reinforcing engagement, self-monitoring strategies, and using the high-p strategy, we can improve student engagement and motivation to scaffold learning. — Jay Lingo
We often hear about repeated experiences of frustration and failure in the mathematics classroom, more so for students with or at risk of emotional and behavioral disorders (EBD). “In regards to mathematics performance, 92% of students with EBD had significant deficits in mathematics. These feelings of incompetence could lead to loss of motivation and engagement which are important for academic success.”
In order to address this, general and special educators can promote engagement in math with three motivation strategies: (1) reinforcement strategies (2) self-monitoring of attention (SMA), and (3) high preference strategy. These strategies combined with high-quality, effective mathematics instruction will promote student success.
(1) Reinforcement strategies
“Praise statement that identifies a specific behavior for attending to and being engaged during mathematics instruction rather than a general praise leads to forming positive learning habits.” For example, “Lucas, great job cooperating with your group while you worked to solve that fraction problem.” Praises with behavioral description convey more authenticity and sincerity which increases the reinforcement.
Another strategy is a token economy system to simultaneously work on money and/or decimal concepts. For example, “Great work finding your division error and re-working the problem. I am adding a dollar and 25 cents to your token account for persistence.” We could be strategic in the timing of using the system by delivering tokens when they take risks or are off-task during group work to redirect their attention back to the task.
Educators could also use tech tools to help us remind ourselves to praise or deliver a token on a continuous loop. For example, a tactile prompting device such as iWatch sends a vibratory cue every 3-5 mins. Remembering to frequently and consistently reinforce engagement over an extended period of time makes this strategy more effective.
(2) Self-Regulation and Self-Monitoring
“Students with or at risk of EBD find self-regulation challenging. This is because it relies heavily on cognitive capacities such as working memory, inhibition, and attention.” Teaching cognitive and metacognitive strategies to support learning and independence helps with this. For example, set a timer for every 5 or 10 minutes during mathematics instruction and circle “yes” or “no” when the timer sounds indicating whether or not the student was engaging in the previously defined attentive behavior. It is important that prior to this, baseline data is provided as well as teaching the student how to self-monitor. This process involves reviewing the target behavior, modeling examples and non-examples of the behavior, explaining when and how to record behavior using a self-monitoring checklist.
(3) The High Preference Strategy (High-p strategy)
Students could establish momentum when completing preferred tasks, and this momentum can carry over to facilitate the completion of non-preferred tasks. This strategy “greases the wheels” for students to tackle more effortful work. The high-p strategy also promotes engagement through increasing speed in task initiation and/or completion.
Try implementing these motivation strategies one at a time and see if it makes a difference for your students with EBD. Remember it’s important to keep track of data to see which strategies or combination of strategies work with each student. Even more important is working directly with the student to develop personalized goals for engagement and task completion.
Morano, S., Markelz, A. M., Randolph, K. M., Myers, A. M., & Church, N. (2021). Motivation Matters: Three Strategies to Support Motivation and Engagement in Mathematics. Intervention in School and Clinic, 1053451221994803.
Summary by: Jay Lingo - Jay believes the MARIO Framework is providing structure and common meaning to learning support programs across the globe. Backed up with current research on the best practices in inclusion and general education, we can reimagine education…together.
Researchers Stephanie Morano, Andrew M. Markelz, Kathleen M. Randolph, Anna M. Myers, and Naomi Church participated in the final version of this summary.