I really dig this animation that goes along with a talk by Sir Ken Robinson on changing education paradigms.
I’m really in to data based decision making. I know this term gets thrown around quite a bit, but I think it’s importance is often overlooked, especially when we get into the AAC field. Let me start with an example that involves communication, just the wrong kind.
A colleague of mine is a behavior consultant. He gets called in on some cases you wouldn’t believe. One interesting case he shared with me concerned a young student who spell curses. Without getting into the details of how this all got started, I want to focus on what happened after my colleague visited the classroom. Keep in mind that this student was probably spell cursing over 50 times a day. My colleague observed the classroom and made a few recommendations and followed up a few weeks later.
Now, here’s where the data collection piece comes in. If you are being cursed at (spelling or otherwise) 50 times a day every day and the student reduces their cursing to 40 times a day you are not going to notice the difference. However, if this occurs after implementing a new strategy for a few days, this is actually huge difference! Basically, in less than a week’s time, you were able to reduce the negative behavior by 20%. Just think of what could happen over a few weeks of implementing this and other strategies. Unfortunately, if you are like most of us, you would not have collected data on every curse word thrown at you every day, so you would not have noticed the 20% reduction, therefore causing you to believe the strategy was worthless and abandoning it.
Let’s carry this example back to the world of AAC. Many times I see an AAC device purchased or borrowed and simply sat in front of student waiting for it to magically increase communication for the student. Unfortunately, it doesn’t work this way. Strategies must be used with the student using the device just like reading strategies are used with students learning to read. So how do we know if the device is going to work? You guessed it… with data!
If you thought the example above was tough to collect data on, imagine collecting data on a student who has over 300 opportunities to respond in any given day. I’m not saying it is easy, but we have to figure out a way to collect data to determine if a device is increasing the student’s ability to independently respond when an opportunity arises. One easy way to start this process is with rubber bands. Put a bunch around your wrist and before introducing a new strategy or device, throw one of the bands in a jar every time the student independently responds. Do this for a week, then repeat after a device and/or strategy is introduced. If the jar started after the AAC was introduced has more bands, improvement has been made. Train all of those working with the student to collect data as well so you have a more accurate picture of how the device or strategy is working throughout the day.
In addition to tracking the number of independent vs. prompt dependent communication attempts, you may also consider tracking the amount of time it takes a student to respond after a prompt is given. In this case, the shorter the time the better.
As the title suggests, this short post is on the importance of collecting data. There is much more to successful AAC implementation than just collecting data however. I’ll throw out some ideas on how to make the process easier soon.