SMART Goals and PDSA

Video Transcription

Hi, everyone, and welcome to this lesson all about how to develop SMART goals and how to use PDSA for the purpose of continuous improvement. I promise you will learn what all those letters stand for. Let's get started.

I was trying to think of an example outside of school in which I personally use SMART goals, and I was having trouble. In fact, I was staring at a blank screen while working on this video when I realized the example was right before my eyes. It's creating these videos.

Before I begin each one, I have a specific goal in mind that's measured by how well I cover the material and the quality of the production. The goals I set are attainable in x amount of hours per video, for example. The goals are relevant, and I'm responsible for reaching them in an allotted amount of time. And there you have it, a real example of a SMART goal.

SMART, S-M-A-R-T, of course, is an acronym. And as you develop your goal, you'll want to use it for guidance as you ask yourself these questions. What specifically do you want to accomplish, and what actions are needed to get there?

How will you measure the attainment of the goal? Is the goal attainable? Why is this goal relevant, and who will be responsible for carrying out the actions? How long will we work on the goal, before we measure and adjust our actions, if needed?

Now let's take close look at an example of a SMART goal and dissect it in order to see if it meets all the criteria. Here's one you might see written in an elementary math class maybe in October. By June, 90% of all students will improve their math problem solving skills by at least one point as measured by the district rubric. This goal is specific in terms of the percentage of students that need to grow, however, does not identify actions that are needed to get there.

Attainment will be measured using the district rubric. The goal of 90% is attainable. The goal is relevant because math problem solving is an essential skill, and the teacher will carry it out. And it clearly states that the time period ends in June. This is certainly not a perfect SMART goal, but it represents a pretty standard one.

Next, let's move on to the implementation of a Plan Do Study Act cycle of inquiry. This is an educational phrase, so of course, it has to have an abbreviation. It's PDSA.

SMART goals are larger and include action steps. It's a good idea to break those steps up into their own short cycle action plans, and using the PDSA model is one way to do that. I've used PDSA both as a teacher and as an administrator, and I can tell you, that it's a very helpful approach to action planning around a shared problem with the goal of improving teaching and learning and to increase student achievement or even improve student behavior.

Listed here are the steps of a PDSA cycle. As we continue to encourage students to take ownership of their learning and the data. The PDSA cycle supports this notion. As it continues improvement process, it can be used by a teacher or a team that has identified an area that needs improvement based upon the data.

But why stop there? Students can also engage in individual PDSA cycles with their own identified goals. For example, here are some students and teacher-created PDSAs. Charts like these are popping up in schools everywhere.

Generally, PDSA is used in classrooms are updated weekly by the students. An example might be something like this. I want to improve my ability to solve 2-step equations with 85% accuracy on our common assessments this quarter. I will use our online tutorial program during intervention time and meet with the teacher wants a week after school for extra help. I will monitor my progress on formative assessments in my data binder daily and chart my progress weekly.

In order for schools and teams to continually improve, they need to know where they currently stand, where they are going, and how they are doing in their progress to get there. It's impossible to answer those questions without the use of data. Data is critical in the development of both SMART goals and PDSAs. The entire PDSA process is founded on the use of data.

It begins with reviewing the current or baseline data. From there, you determine data-based outcomes. Next comes establishing how the progress toward the outcome will be measured. Then, you monitor that progress data and adjust steps based upon the results. Finally, you determine if the outcome or goal is met based on the data.

None of this can be possible without both qualitative and quantitative data review. Qualitative data informs teams about how stakeholders feel about or perceive the effectiveness of the school with regards to both academic and social emotional support, as well as gives a sense of the overall culture and climate of the school. This type of data can come from surveys, anecdotes, forums, interviews, and consensus taking. It's important for this data to be reviewed regularly in order for stakeholders to see if the particular programs are helping schools toward their vision, mission, and goals.

Quantitative data as the name suggests includes information that could be quantified, for example, standardized assessments, state assessments, internal formative assessments used for instruction, as well as summative assessments. This data is important because it can be directly related to how instruction is impacting student performance, and if the school is moving toward reaching the goals established in their plans. PLC teams need to know if they are on track to meet their school improvement goals. And data review will help them determine if they need to adjust their actions.

Now let's go ahead and summarize what we covered in this lesson. We introduced SMART goals and learned what S-M-A-R-T stands for. We looked at a sample SMART goal. Next, we examined PDSA and looked at the Plan Do Study Act samples. We talked about data collection, and as part of that data collection, we looked at both qualitative and quantitative data.

Here's today's food for thought. Take a look at the many ways your district collects data and think about what the data is being used for. For more information on how to apply what you learned in this video, please view the additional resources section that accompany this presentation. The resources in this section include links useful for applications of the course material, including a brief description of each resource.

That's all for this video. Thanks so much for watching. Have a great day.