We talk quite frequently about the importance of having or analyzing data. Could you tell me some specific examples of times when you have used data to drive instruction or make a change at your school or in your county?
I think data analysis occurs at just about every job at every level. Personally, I primarily deal with advertising and finance data. The data from monetary gain/loss drives future production. In a far-reaching way, this is like planning instruction in a classroom. If it isn't profitable (like the students don't learn or don't pass the test) you probably wouldn't try that lesson or book again, right?
As an EC teacher, I use data to drive instruction on a daily basis. Thru the collection and analysis of data, I am able to pinpoint the needs of my students and where I should focus my instruciton or remediation.
As an English I teacher who prepares students for an End-of-Course test, I consider some data to be invaluable. With every practice assessment, for example, I am able to measure student growth. Online assessments are especially user-friendly because they easily provide data that allows me to see exactly which concepts are difficult for students to master. Upon analyzing the data, I can adjust my instruction to fit student needs.
That said, however, in some cases, I feel that schools are too data-driven. Regardless of how much growth a student shows over the course of a semester or year, proficiency on the End-of-Course test is seemingly what matters most to administrators. I wish that the state would use a growth model instead of a proficiency model to measure success. Why do I say that? Because, for example, an honors student can come into English I and score proficient on the EOC on day one of the course; however, a struggling student can grow significantly over the course of the year and still not be proficient on the EOC. To the state, the data shows that the struggling student has "failed," when in reality, he or she probably learned more in the course than the honors student did.
So therein lies the conundrum. Would it be possible to switch to a growth model and still make the state happy?
I do thnk we are getting there with EVAAS, but we have a long way to go. I also believe you have shown that data can be both good and bad; moreover, the state has some room to improve as well. This realy goes hand-in-hand with the No Child Left Behind discussion above
At the DOT, data is very important. We use it to determine important things like speed limits and the need for a signal light. Specifically, to determine the speed limit, we gather data about the number of driveways, the number of houses, the width of the road, and then conduct a traffic study of 100 cars to see their average speed. We use 85% of the average traffic speed and combine that data with the other factors to set a speed limit on any given road. When thinking about installing a new traffic signal light, we also have to gather data. For this, we count the number of cars which come onto the main road (during another traffic study) and also look at the number of incident responses (if any). Finally, we determine whether or not the intersection has had any fatalities. All of this combined determines the need, or lack thereof, for a signal installation.
I think data analysis occurs at just about every job at every level. Personally, I primarily deal with advertising and finance data. The data from monetary gain/loss drives future production. In a far-reaching way, this is like planning instruction in a classroom. If it isn't profitable (like the students don't learn or don't pass the test) you probably wouldn't try that lesson or book again, right?
ReplyDeleteAs an EC teacher, I use data to drive instruction on a daily basis. Thru the collection and analysis of data, I am able to pinpoint the needs of my students and where I should focus my instruciton or remediation.
ReplyDeleteAs an English I teacher who prepares students for an End-of-Course test, I consider some data to be invaluable. With every practice assessment, for example, I am able to measure student growth. Online assessments are especially user-friendly because they easily provide data that allows me to see exactly which concepts are difficult for students to master. Upon analyzing the data, I can adjust my instruction to fit student needs.
ReplyDeleteThat said, however, in some cases, I feel that schools are too data-driven. Regardless of how much growth a student shows over the course of a semester or year, proficiency on the End-of-Course test is seemingly what matters most to administrators. I wish that the state would use a growth model instead of a proficiency model to measure success. Why do I say that? Because, for example, an honors student can come into English I and score proficient on the EOC on day one of the course; however, a struggling student can grow significantly over the course of the year and still not be proficient on the EOC. To the state, the data shows that the struggling student has "failed," when in reality, he or she probably learned more in the course than the honors student did.
So therein lies the conundrum. Would it be possible to switch to a growth model and still make the state happy?
I do thnk we are getting there with EVAAS, but we have a long way to go. I also believe you have shown that data can be both good and bad; moreover, the state has some room to improve as well. This realy goes hand-in-hand with the No Child Left Behind discussion above
ReplyDeleteAt the DOT, data is very important. We use it to determine important things like speed limits and the need for a signal light. Specifically, to determine the speed limit, we gather data about the number of driveways, the number of houses, the width of the road, and then conduct a traffic study of 100 cars to see their average speed. We use 85% of the average traffic speed and combine that data with the other factors to set a speed limit on any given road.
ReplyDeleteWhen thinking about installing a new traffic signal light, we also have to gather data. For this, we count the number of cars which come onto the main road (during another traffic study) and also look at the number of incident responses (if any). Finally, we determine whether or not the intersection has had any fatalities. All of this combined determines the need, or lack thereof, for a signal installation.
Love, Dad