With September crossed off the calendar, most of us are now firmly into a new school year. Rules, routines and procedures have been taught and reviewed; initial data has been collected; data teams are getting into a rhythm. But what data are we looking at?
One of the teaching points I revisit frequently with teams all over is the need to collect data on our own adult practices. I rarely have anyone who questions this. But they are usually at a loss for how to do this, and even have hard time deciding what data would be meaningful to collect.
As I always say, if you have something that is already collecting data for you, don't invent something new. Here is an example of how we used a walkthrough form to collect and analyze adult practices, and how we prioritized next steps based on the aggregate data we collected.
My work with the school started as an off-shoot of ongoing work in the district, and statereporting of a performance gap between Hispanic students and their white classmates, and, more significantly, between English Language Learners and students whose first language was English.
The question the administrator had: What professional development do teachers need to better support English Language Learners in our school?
The Data Collection Tool
To collect data on teacher practices that impact second language acquisition, we used the Sheltered Instruction Observation Protocol (SIOP). This protocol assesses the components of a well-designed lesson for supporting second language acquisition, and allows for the recording of specific evidence for each component. Click on the image, below, or the link, above, to download a copy of this observation tool.
Lesson #1: You can collect school-wide data on adult practices from any form you currently use in your school.
The Data Collection Method
The above walkthrough sheet was taken to classrooms, which were observed for 10-20 minutes, each. Each classroom's activities were recorded on a separate sheet. The larger blocks allowed for recording of specific evidence, while the center block, with SIOP lesson features, was a check box: the feature was evident or not. Additional comments were recorded in the margins, as necessary.
This data collection method is not different from the way teacher walkthrough data is collected everywhere. But how to turn it into a school-wide data set, then prioritize the next steps from it?
Lesson #2: You don't necessarily need to change your data collecting techniques to begin collecting data on adult practices.
The Data Compilation
After all the walkthroughs were finished, we needed to decide where were the areas of strength of the staff, where were the high-leverage points (i.e., places where there were good practices that could be made even better, and where were there certain practices that were conspicuously absent, altogether. The idea is that it is better to build on current structures and practices, than to insert brand new ones.
(NOTE: if data were collected from 80% or more of the staff, I felt that there was enough to determine a school-wide focus. I collected data from 89% (16/18) staff members)
To determine this as an aggregate, I used a blank data collection form, and simply put check marks next to each component observed. In this way, I had a clear visual summary of practices which appeared to be in place, versus practices that were not yet begun in the school. Because of other professional development happening in the building, the administrator wanted to know if there were particular grades that need more support than others, so I color coded the checkmarks red for K-2, and green for 3-6.
Lesson #3: Resist the temptation to disaggregate the data. Your goal is to take the "temperature" of the entire school.
The Data Analysis
So, what do the checkmarks mean?
The administrator wanted to know where to best target additional coaching support. So we looked for patterns and trends across the entire school.
We set some filters for looking at the data:
We were most interested in the widespread, systemic practices (because these reflect transfer of past professional development into standard practice, and these represent areas of strength for the staff, upon which we can build their learning); practices that are part of the culture but not yet systemic (because these represent the staff's "instructional" level); and practices which are not evident in any of the classrooms (because these demonstrate potential obstacles to overcome). The broad range of practices that are not part of the school culture are not the primary focus, because they may be out of the repertoire of many of the faculty without more intensive support. They are important, but not the top priority at present.
Based on these decision rules, we discovered this set of practices for each of the above categories (see image, at left). Note that I created a handy chart for the number of tallies and the percentages that each represents of the total number of classrooms. It was just as fast for me to create this "cheat sheet" once as to enter it into a spread sheet.
I used no special paper, just a corner of the summary sheet - why make things more complicated than necessary? But I did color code the three levels. Color is helpful, and most teachers are familiar with this color scheme from SRBI.
I love a good Excel spreadsheet. You might be tempted to codify the entire data set and enter it into a spreadsheet. Here are the reasons NOT to do this:
Lesson #4: Develop decision-rules to prioritize a focus BEFORE deeply analyzing the data.
The Next Steps
Sometimes (not usually), our data tell exactly the area for focus teacher support. Other times (most times), it tells us that there are many areas of need, or scattered, seemingly disconnected areas. We can only do so much in one year, so it is up to us to identify key areas that will give us the greatest changes in practice. This often takes a little detective work and inference, and the combination of small topics into a larger, more meaningful focus.
For example, in our data set, above, guided practice showed up as a universal structure, but also as an area for targeted support, based on the ways that teachers were using guided practice to support English Language Learners. Similarly, while there were many classrooms with small group activities, there were comparatively few observed where the teacher was directly instructing the entire class. It was inferred, therefore, support in the more explicit use of the gradual release model might address all of these areas, and would be preferable to addressing each of these pieces as individual topics.
Based on the practices highlighted in yellow, above, it was determined that these would be prioritized areas of support for the teachers:
It was also decided that, since the percentages were consistently higher for the K-2 classrooms, and there was another professional development targeting those grades, the bulk of the coaching support would be delivered to grades 3-6, with occasional grade level team meetings with the other grades, or delivery of tips and materials during staff meetings.
Lesson #5: Be ready to infer underlying reasons for disparate data points, and to explore root causes for some observations.
Developing an Instructional Plan
Where to start?
There are many decision rules when picking the starting point for addressing adult data. In most ways, they are not unlike the rules you use when working with student data:
So, you see there isn't one decision rule.
In the above example, we then went back to our original data sheets to read over the specific comments for the areas we identified using our simple tally mark system. We determined that teachers were using a lot of good practices, but few of them were selected and used to directly address the needs of ELLs in their rooms. In other words, instruction was not necessarily adapted to address the unique needs of these students. In order to do that, however, teachers had to have a way of analyzing their lessons to anticipate areas where English language learning would impact accessibility of the instruction.
Consequently, the decision was made to introduce the staff to Cummin's Quadrants, a tool for analyzing the content and language demands of instruction and activities. This foundational learning would then form the basis for identifying ways to adapt and supplement materials, content and instruction, with the needs of their ELLs in mind. This one piece would then, theoretically, set teachers up for most of the other focus areas: without addressing it first, the other areas might seem disconnected from one another.
Lesson #6: Once target areas are determined, go back and read over the specific data to help construct plans to address these areas.
Because you used a data collection tool and method which are not new to you, you don't have to invent a new tool to collect data on how well the plan is working. There are two basic ways to monitor progress:
Did You See the Data Teams Steps?
As you see here, with this one example, collecting data on adult practices is not any different than collecting data on DRA performance in students. This look at adult practices is helpful for school data teams when deciding a problem of practice for a school-wide goal, for administrative teams determining goals for Professional Learning Plans for staff, and for professional development committees creating PD plans for the school year.
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