The Current Dilemma

Consider the current issues facing all educational professionals. First, school-wide Problem Solving Models (e.g. response to intervention (RTI) or positive behavior supports (PBS)) essentially require interventions for everyone in need. Second, educational policy (e.g. No Child Left Behind and IDEIA) mandate higher levels of accountability than have been typically demanded, resulting in the need for defensible formative outcome data to measure the effectiveness of interventions. Finally, traditional models require a great deal of time to develop recommendations about a child’s needs. For example, a comprehensive assessment orientation requires hours of assessment and report writing followed by long meetings to develop intervention plans. In addition, we have learned that regardless of the amount of upfront assessment, any interventions recommended will only be ones that are “likely to be effective”, and unfortunately not sure things. Intervention effectiveness is only known after implementation and formative assessment.  A traditional consultation orientation is designed to find an effective intervention, but is unfortunately quite time consuming as it typically requires a number of consultation sessions to guide the intervention process. The combination of these factors is a concerning mix of more cases, more accountability, and a lack of models that are built to handle a massive intervention caseload.

The Solution: “Efficiency”

The logical solution to this dilemma is “efficiency”. It is critical that we select and design interventions at Tiers 1, 2 and even 3 (in a PSM/RTI model) very quickly so that most of the time allocated is devoted to actual intervention implementation. Second, we need to collect outcome data in a highly feasible manner. Finally, it is critical to have a consistent manner of data analysis that is quick and easy for most educational professionals. Considering the needed efficiently, it is only defensible to select intervention based on the “The Reasonable Hypothesis”. In most cases, the efficient and likely effective pathway is to test the most likely hypothesis explaining the academic or behavioral problem first, and then proceed to less likely and more complex explanations. This orientation is an application of Ockham’s razor – given two competing theories (or hypotheses for the problem behavior) the simplest explanation is to be preferred. If that approach fails to improve student performance, then something progressively more time-intensive can be attempted until the probable cause of failure is identified. To go about this path, we must consider functional explanations rather than look “within” the child.

Relating academic performance/student behavior to aspects of classroom instruction that both precede and follow student performance represents a functional approach to understanding academic or behavior problems.  Functional explanations appeal to factors external to the child that have been shown experimentally to affect academic and social behavior performance, such as time for learning, feedback from the teacher, and reinforcement for correct responding. Because these factors are external to the child and subject to direct manipulation, functional explanations have the added advantage of identifying simple, practical targets for intervention programming.

The 5 Common Reasons for Academic Problems

We have decided to use the model of five common reasons why students fail academically proposed by Daly and Martens (1997). This model provides a simple and quite comprehensive approach to quickly selecting functional explanations. Those interested in an in depth explanation of this framework are directed to read the original article (A model for conducting a functional analysis of academic performance problems. School Psychology Review, 26(4), 554-575). Specifically, the five common reasons are;

  1. The academic activity is too hard (Academic Acquisition Interventions).
  2. They have not had enough help to do it (Academic Proficiency (Accuracy) Interventions).
  3. They have not spent enough time doing it (Academic Proficiency (Speed) Interventions).
  4. The student has demonstrated the skill before, but are having difficulty applying the skill in a new manner (Academic Generalization Interventions).
  5. They do not want to do it (Behavioral Fluency Interventions).

The 4 Common Reasons for Behavior Problems

In relation to behavior problems, we have decided to mirror the above approach. Specifically, children acquire, become fluent, and then generalize appropriate social behaviors.  Behavioral acquisition interventions are the parallel to the first in the academic framework.  Behavioral Fluency intervention are the parallel to the second and third in the academic framework.  Finally, generalization programming is the parallel to fourth in the academic framework.  We have also added a category for classwide strategies to support appropriate behavior. Specifically, the three common reasons are;

  1. Classwide Interventions
  2. Student has not learned the behavior (Behavioral Acquisition Interventions).
  3. The contingencies in the environment do not support the desired child behavior (Behavioral Proficiency Interventions).  This common reason can be further broken down in to cases where the student is trying to get something (often attention) or escape something (often an academic task demand)
  4. The student has not had to do the behavior that way before (Behavioral Generalization Interventions).

Using the Framework

Using this model, a teacher or problem solving team is asked to consider what they think the most likely reasons are for the academic or behavior problems. Once selected, these hypothesized reasons are then used to select interventions. If there are more than one likely reasons selected, they should be rank ordered (from most to least likely). It is important to note that the accuracy of these reasons will only be known after interventions are implemented and outcome data is selected. While it is important for the teacher/problem solving team to be logical in the problem reasons selection stage, it is not important for the team to perseverant in order to make the perfect decision. Again, it is only after the intervention is implemented that the accuracy of the original decision will be known. Considering how this framework is to be utilized, it should be very clear that intervention implementation with fidelity, collection of defensible outcome data, and accurate analysis and decision making necessary components. This framework has not been developed to aid in the selection of an intervention, and then simply hoping that it will work.