Data Collection and Data Based Decision Making

As the intensity of interventions increase, the amount of data collection should also increase. Data is essential in evaluating the effectiveness of Tier 2 interventions to guide decision-making during and after the course of intervention.

Data Collection

Baseline Data & Goal Setting:

Baseline data should be gathered to determine a student's current performance of a targeted skill to create an achievable goal. Ideally, at least stable 3 baseline data points should be collected to ensure a valid estimate of a student's current proficiency of a targeted skill and anticipated rate of improvement.

In addition to setting a goal, decision rules should be established to determine when a student's performance meets exit criteria. This will create an objective standard by which an interventionist will determine when a student has made sufficient progress and no longer require the Tier 2 intervention.

Progress-Monitoring Data:

Progress monitoring, ongoing data of a student's performance of the skill targeted for intervention, must also be gathered. The more data points that are collected, the more accurate this data will be in capturing a student's response to intervention.

Pre-packaged Tier 2 interventions often have built in progress-monitoring tools or they can be created by the interventionist (e.g., goal-attainment scaling, subjective units of distress, check-in check-out forms, behavior contracts, etc.)

Treatment Fidelity Data:

Data on the treatment fidelity with which interventions are implemented as designed must also be gathered in order to determine if a student's lack of response to an intervention is due to it not being accurately delivered or if it did not meet the needs of the student.

Analyzing Data:

Data should be charted and graphed to allow for a visual inspection of the student's rate of progress. A trend line should also be computed to assess whether the student will achieve the goal set at the onset of the intervention.

This can be accomplished using a web-based data management program or spreadsheets (i.e., Excel, Google Sheets, Numbers, etc.)

Data-Based Decision Making

Data should be reviewed frequently (ideally every couple of weeks) to determine if adjustments need to be made to improve the fidelity of implementation and the student's response to the intervention. Once the identified intervention period has finished, the interventionist must determine if the student's intervention should:

  • Continue (if possible) when the student is making progress but has not met their goal, OR
  • Be faded (if possible), when the student has met their goal, to ensure the student maintains their current rate of performance of the targeted skill, OR
  • Be discontinued when:
    • The student met their goal and/or the exit criteria.
    • The student did not make sufficient progress and requires more intensive support.