What are your current processes at the site or in your classroom when a planned intervention is not working? What about when it has been successful?

How do you determine who needs additional support and what kind?

So, you have collected all the data, found your desired behaviour, put in place interventions and responded to behaviour success and errors, and it’s still not working. What now?

In this place, we finally look to the Response to Intervention (RTI) model for answers.

Much like the review and reflect component of the behaviour design model, data-informed decision making is simply using the information available to determine if the desired behaviour needs additional modifications to motivation, ability/access, prompt or reward for a student to be successful.

By using data to inform these decisions instead of professional judgement, we remove the effect of cognitive and unconscious bias from the decision-making process. This is important due to the impact of the Pygmalion effect discussed earlier.

In order to have adequate data decision-making, you need to develop data rules that are, in essence, a prompt for you to perform one of the following behaviours –

Student remains in tier 1 intervention.

Student graduates to tier 2 intervention.

Student remains in tier 2 intervention.

Student returns to tier 1 intervention.

Student graduates to tier 3 intervention.

Student remains in tier 3 intervention.

Student returns to wave 2 intervention.

Having clear guidelines for each of these prompts will remove the need for both challenging conversations and professional judgement calls. Instead, we rely on data triggers to determine a student’s mobility through the tiers of interventions.

Each data trigger will be unique to each desired behaviour and the data collection tool you use.

Some examples may look like –

After a student forgets their hat 3 or more times in a week for a 3-week period.

After a student scores above 13 on the SRSS for anti-social behaviour.

After a student has more days absent than present a week.

After a student receives more than an average of 3 office referrals in a week for a term.

After a student can identify where spare hats are kept.

After a student can tell an adult their emotional state when angry 9 times out of 10.

After a student puts on sunscreen every time, the bell rings.

After a student scores below an 8 for the SRSS.

Develop a list of data triggers for your desired behaviour –

Student remains in tier 1 intervention.

Student graduates to tier 2 intervention.

Student remains in tier 2 intervention.

Student returns to tier 1 intervention.

Student graduates to tier 3 intervention.

Student remains in tier 3 intervention.

Student returns to wave 2 intervention.

Consider what the process of graduating and returning between tiers of intervention may look like at your site.

Pair this work with the skills you have developed in the behaviour design module and propose what tier 2 and 3 interventions may look like for your desired behaviour.

It’s time to put it all together.

You now have all the tools to develop a draft PBIS program, informed by behaviour theory and CPS.

Give it a try – pick three desired behaviours, apply these skills, and see how they work for you.

Good luck!

It’s all up to you now. Reflect on how your desired behaviours were implemented into your site.

What were the barriers?

Where you explicit enough?

Did you need additional support?

Do you need to seek additional skills or expertise?

Who were your champions, and who were the detractors?

Where will you go from here? Will you expand to more behaviours?