But if teaching is, at least in part, to prepare students for the real world, then it must be important to use data that reflects reality, or life outside the classroom. If education is supposed to mimic reality, our evaluation measures ought to be realistic, right?
What types of evaluation measure do you use in real life? For example, how do you judge how long to leave your burrito in the microwave? If it comes out burned, do you make adjustments? What other "data-driven measures" do you use, and how well do they work?
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Many times, as we learned today, teachers do not adjust their teaching methods even if they see that they are not succeeding in teaching the students. It is extremely important to adjust methodology in response to the data you receive in success if whatever you're doing does not work. In real life, no matter what it is, we naturally adjust to succeed and survive. Its seems only natural to do the same in business or teaching and to "face the facts" about bad teaching practices.
In plumbing, the work is evaluated as to how well it holds up. The water lines, for example, are plugged and filled to test their integrity. Sometimes there are leaks that have to be fixed and then retested until it is all good. This testing system works well. Even before this stage, every piece of pipe needs to be cut the right length. You can quickly tell if the pipe you are holding will not fit where it is needed. Plumbing needs to be done in the real world and thus can be used as a model for realistic evaluations
Cormac
Most data is compiled through trials. Trial and error is a method that can take a long time but is specific in its successes. In evaluating students as a teacher, results and feedback is the best and most helpful way to encounter problems. Like a science experiment, teachers adjust certain parts of their teaching to improve results. In a way, it could lead to trial and error. Finding out what works is the main goal in order to solve problems head on. These "helpful" problems test your teaching style. In everyday life, we measure our time management in everything we do. From getting to class on time to meeting with friends, we constantly measure the purpose, benefit, and necessity of our actions. We see what works and further utilize what is successful or most beneficial.
To measure your own evaluation in school, you first play around with certain studying habits. Some procrastinate and wait until the day before to study, but it ends up working for them. You have to find out by making mistakes and trying again in order to find the perfect balance. In order to find out what works in your classroom it is important to try different methods and get feedback from students until you feel comfortable on the plan that works well for you.
I personally use a lot of trial and error. For example, in brewing beer or mead I write down the different sets of data pertaining to ingredients, fermentation time, boil time, and priming. This is aided by simulation software that aids in predicting the outcome, but ultimately my own palate and anyone else who samples the end product is going to have the conclusion. Usually I will look at what worked and what did not and adjust accordingly. Sometimes it is a less data intensive process but the data collection is more about replicating positive results.
Wow, What a class tonight! A brilliant display of curriculum planning, teaching implementation and assessment. Lots of data points to track how information shared in the classroom was sinking in. At the end of the day, the teacher is responsible for keeping track of her/his students and making sure they have the oportunity to succeed. It is the teacher who must find a way to bring the material to the student in a way that they can grab hold of.
This was a good blog, I never think about data measures I use in real life! I'm always deciding when to leave for class, and checking my clock when I leave and arrive to see how quickly I walk. I think that we metacognitively evaluate ourselves all the time, but data measures are perhaps less common which might be why they seem so difficult to connect to real life in classroom settings.
-Robin van Schravendijk
I'm reminded of one of my fellow teachers, who constantly talks about how frequently he calculates his minimum speed to get to campus on time. I use data and measurement in many ways. In art-making, I constantly am in a battle to decide whether to accentuate mistakes or eliminate them completely. With students, I find it important to allow mistakes, but also to address & identify them asap.
I feel like assessment and adjustment is the name of the game. I think one of the best skills students can learn is how to fail or be wrong and use the errors they make diagnostically. If we can teach children to make mistakes and then have the perseverance and incentive to suss out where the error was in their process and correct that error for success, then we have done our jobs well.
I'm always noticing myself making corrections based on "incoming data" as I go through my days. The first thing that came to mind reading this week's question was how I've modified my bicycle route from home to the high school where I'm working. In the 1st wks, depending on when certain traffic lights would change to red, I would vary a bit here and there from my initial, rough course idea. Over time, though, I've noticed which 2 routes are solidly best among the many options tried. These include a couple hills, but always result in a faster trip than traveling the stupidly popular "wiggle" (through Lower Haight / Dubose Triangle).
I adjust the length and type of my violin practice based on how many errors I make when I play...I never really thought about that as data before, but I suppose it's true that if I never kept track of my successes (playing with few mistakes) or failures (many, or the same ones repeatedly) then I wouldn't know what or how to practice. Same goes - should have gone - for math when I was a kid. Instead I was defeated by the data, which told me I sucked. Ergo, more important is the teacher's use/follow up with the data to improve the student's performance.
The first thing that comes to mind regarding data usage "in real life" is my bicycle, and everything that goes along with it. I'm constantly making adjustments to the various features: gears, wheels, etc. not only in how the parts are put together, but how the bike is ridden on the road. Also, the best route to take and the time involved, particularly because I'm relatively new to the area and I have the opportunity to improve the route(s) I take on my daily commute, I am constantly "collecting data" and applying the information to make improvements. Popped a tire? Buy a stronger tire. Steep hill? Change gears. Too many hills? Take a different route. Late? Leave earlier. In reality our brains are essentially collecting data through our senses continuously and we are putting our acquired to use just as much even if it is as simple as putting one foot in front of the other and maintaining balance.
I do think data can create a good framework for assessment and understanding. As a teacher it is important to know how the class is progressing and where each student falls among the spectrum. Weekly assessments I think are a great way for revealing progress and understanding where the class as a whole is at and how each student might contribute to that whole. Even having a little daily type of assessment might be helpful for the teacher to know that the task(s) for the day were clear and the students took something away. (perhaps using an exit ticket) I think we learn mainly through experience and don't know that data is always the best means for assessment especially for students in knowing and having a grip of how they personally are doing/progressing in the class.
Data is important to mark progress and give feedback to the students. Education is supposed to prepare children for the real world and with appropriate assessments to ensure success. Evaluation is in real life is by how well one can perform tasks. Also trial by error is a way of measuring success of real life. Someone has to fall a few times before you can find what works and continue. The same is often true in education. It sometimes takes a few different tries of learning methods to find something that works. Collecting data in an accurate way is a way to determine if it works or not.
In theory evaluation measures should be realistic but they really aren't. Just the same as education is supposed to mimic reality but it usually doesn't.
In real life I look at my grades as an evaluation method. If I see a B that means I need to work harder and change how I am doing something. I use lots of data daily because I'm a research assistant in the psychology department. That data works well to tell us the questions we are asking.
After reading this post I thought of my daily commute up to campus. I have to consider which route will be most efficient depending on the day and time, calculate how long I think each bus ride may take, calculate time waiting for a bus, and given that I use public transportation, I have to factor in time lost due a detour, driver change, trouble maker, etc. Everyday I am working with the ever changing data required to plan my route to and from school. My daily bus struggle relates to the trials and tribulations that a teacher goes through each day. The more data I have about my bus route (GPS time, for example), the easier my planning will be. Similarly, the more data a teacher has regarding her students, the smoother his or her day will go. Collecting and evaluating data (like Todd's "Exit Ticket") will help teachers evaluate students more effectively. Ultimately, we as teachers hope to introduce students to data evaluation skills and encourage critical data analysis that can be used in daily life, like a bus ride.
Once we start our teaching careers it is safe to say that we will have a lot to learn. We will have to use the method of trial and error. Try things out and if they fail or not work as well adapt the lesson. It is rare that one lesson will be great right out the gate so constant adjusting will need to take place.
In everyday life, trial and error is probably the most common form of data collection to make progress. One example of this is pushing limits. I often times don't get enough sleep and push my studies until the last minute. So, I will stay out late and study the least amount possible. If I do well in a class, then I don't change my habits, but if my grades start to slump, I will cut back my socializing habits and put more energy into school. This method of evaluation is used in all aspects of life, and is not necessarily taught in a classroom setting, but it is used by everyone as an informal evaluation tool.
My father is always tracking data such as temperature, rainfall, etc. And, no, he's not a meteorologist . . . it just happens to be his thing. I'm less concerned with data analysis; while it is significant for identifying past trends, I feel that it can lead to a sense of stagnation in the sense that all of this normalized information is "just the way it is", as opposed to the way it ought to be. I'm more interested, obviously, in the latter.
I use trail and error. I test out a hypothesis that I believe to be true, and then test it out. If it does not work, I try a different method, and see if this works. If it doesn't, I try a different one and so on. I test out different methods until I find one that works. For school, you have to try different methods of teaching to see which one the students are responding too. Testing would be a good way to see if a student is effectively learning the material.
Yes "without data, all anyone has is an opinion" but it is important to remember how easy it is to manipulate or mislead with data.
Take for example standardized tests. One can see significant improvement in final scores if test taking skills are taught. But then do these higher scores represent any improved learning other than in a students ability to take standardized tests.
I think it is vital to mix data with subjective analysis of the data and what it may mean. In teaching we will need to continually asses how are students are learning and what that may mean about our teaching.
Sure, without data all we have is our opinion. But, to what extent should we allow data to dictate and control our opinion? For example, let's consider standardized tests. The data from theses tests indicates that students of color and socioeconomically disadvantaged students trail white students' test scores. Should we allow this data to lead us to the conclusion that white students are simply smarter than their black and latino counterparts? Surely not. However, many educators erroneously make this assumption.
Data legitimizes our opinions, but let's not forget how the interpretation and perception of that data is often subjective. As an undergrad Psych major, I became all too familiar with reading the same experiment's data to justify and support a wide variety of theories. Simply put, data is what we make of it.
In my own life, experience is paramount as an evaluation measure. Each time I leave San Jose to drive into the city, I consider every other morning I've awoke to do the same thing. If I wake up too late and am stuck in traffic, I consider all the other mornings I've left at that time and compare the experiences. Then I consider what traffic was like when I've left earlier. Using my past experiences at data, I sometimes make adjustments in my behavior. However, this measure does not always prove to be reliable.
*Jacquelene*
Sure, without data all we have is our opinion. But, to what extent should we allow data to dictate and control our opinion? For example, let's consider standardized tests. The data from theses tests indicates that students of color and socioeconomically disadvantaged students trail white students' test scores. Should we allow this data to lead us to the conclusion that white students are simply smarter than their black and latino counterparts? Surely not. However, many educators erroneously make this assumption.
Data legitimizes our opinions, but let's not forget how the interpretation and perception of that data is often subjective. As an undergrad Psych major, I became all too familiar with reading the same experiment's data to justify and support a wide variety of theories. Simply put, data is what we make of it.
In my own life, experience is paramount as an evaluation measure. Each time I leave San Jose to drive into the city, I consider every other morning I've awoke to do the same thing. If I wake up too late and am stuck in traffic, I consider all the other mornings I've left at that time and compare the experiences. Then I consider what traffic was like when I've left earlier. Using my past experiences at data, I sometimes make adjustments in my behavior. However, this measure does not always prove to be reliable.
We use many different ways to evaluate daily activities. Personally, the most I estimate data and how it will relate is through sewing. I always have to estimate if I will have enough fabric to make what I want to make, and if I will have any left over. This can relate to teaching in something as simple as estimating how many supplies you will need for an activity, will any break? Will soemone lose any and you will need extras?
As pathetic as this may sound, I observe and evaluate just about everything that happens in my everyday life. My parents don't know how else to describe me, but the word "thoughtful." Most of the time I think of this as a curse brought upon me because I'm always thinking about the way I think. It hasn't been until this semester, while taking a Teacher Ed class (Teaching for Diversity and Social Justice), that I've recognized this quality - critically consciousness - as a positive motivator and drive for my life.
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