GSOE - University of California, Riverside
Efficient & Effective School-Based Problem-Solving Teams
About PST 1-2-3
PST 1-2-3 provides explicit yet flexible guidance to educators as they engage in team-based problem-solving and data-based decision-making activities to address challenges facing students, staff, classrooms, buildings, and districts within tiered service delivery models. PST 1-2-3 draws from core problem-solving components, behavioral consultation processes, and practical, real-world experiences to address frequent barriers to ineffectiveness and inefficient SB PST. PST 1-2-3 uses structured agendas, repetition and consistency, time limits, and deemphasis of prior training or experience to address barriers to success such as resistance, inconsistency, poor training, and lack of knowledge or skills relative to intervention, supports, data-collection, or problem-solving. Since initial pilot implementation in 2008, PST 1-2-3 has been refined through incorporating additional research and theory, feedback from users, and outcomes for students. The effectiveness of PST 1-2-3 is rooted in its unique features. PST 1-2-3 requires little training for most participants, it uses a consistent 3-meeting cycle, and activities are driven by simple, structured, time-bound agendas.
The primary emphasis of PST 1-2-3 is to promote collaborative problem analysis and problem-solving while downplaying the individual, expert-driven approach to intervention inherent in a diagnosis-driven medical model of service delivery. In the PST 1-2-3 process, the “expert” is the person charged with ensuring the integrity of the PST 1-2-3 process. In keeping with a collaborative, collectivist, and non-expert driven problem-solving approach, PST 1-2-3 meetings serve as organizational tools for activities to be executed following meetings. The underlying rationale for this approach is that meetings themselves (i.e., meeting with experts) do not address problems; real problem-solving or intervention efforts are the actions carried out following the meetings. To this end, a hallmark feature of PST 1-2-3 is the dedicated time, following the initial meeting spent researching possible problem solutions. This prevents teams from (overly) relying on the meeting experts to generate on-the-spot solutions to identified problems. This mechanism also serves to broaden all team members skills in identifying evidence-based interventions for a variety of problems (i.e., doing intervention research) and broadening awareness of specific evidence-based practices in generally. Guidance from the PST 1-2-3 facilitator and other team members in conducting this and other problem-solving activities allows participants to learn by doing, thus eliminating the need for exhaustive, sit-and-get training.
Supporting the consistency and repetition and decreasing the burden of training is the overall format of PST 1-2-3. PST 1-2-3 employs a three-meeting cycle to established problem-solving activities as a linear process rather than a singular event. Each meeting follows a specific agenda that results in explicit actions, roles, and responsibilities for some or all team members that will be completed. Teams work through steps, including functional problem definition, baseline data collection, intervention selection, progress monitoring, implementation fidelity checks, and data-based decision in a very structured, organized, and efficient manner. Within a problem-solving approach, to increase the likelihood of problem remediation, some problem-solving steps must occur prior to others. For example, problem identification, definition, and analysis must occur prior to identification of possible problem solutions. It is impossible to identify and select an evidence-based intervention for a problem that has not been identified. Similarly, the importance of problem identification extends to collection of baseline and progress monitoring data. It would likely be frustrating to collect baseline data using reading fluency probes only to discover later that the difficult facing the student was in the area of Math. In short, problem-solving is time bound and linear process, which requires planning, organization, forethought, and commitment for success. It is imperative that this process occur in a sequential fashion to preserve the ability of collaborators to make high-quality, informed data-based decision.
Finally, PST 1-2-3 is based on a simple, yet effective technique used by numerous professions to eliminate natural, expected human error. No matter the level of training or education, on any given day, our intelligence, or training can fail, if only momentarily. To combat this human condition, physicians, engineers, pilots, and others use checklists and repetition to increase the integrity in executing steps in processes and procedures essential to success. The PST 1-2-3 process applies a checklist-structured, consistent problem-solving model and incorporates function-based problem definition and intervention selection in addressing difficulties exhibited by students in any subject area and at any grade or support level. The model allows team members to work through the problem-solving process in an organized, structured manner incorporating through support, practice, and frequent repetition. This process allows repetition of the same processes and procedures within RTI/MTSS service delivery models across all tiers and is designed to be used to address system, building, group, or individual level problems. This consistency in process is designed to promote fluency in problem-solving PST 1-2-3 emphasizes process over problem. This is to say different problems require different solutions, not different processes (or people or experts) to identify and implement possible solutions. Within the PST 1-2-3 process, procedures do not change, only the student(s) or classroom, the identified problem, and possible solutions (evidence-based interventions) will change. The PST 1-2-3 process has been designed to adapt to such differences while maintaining consistence across executing the steps necessary for quality problem-solving and associated data-based decision making.