Images of computers, robots, numbers, maybe an android, this is what comes to mind when the word ‘data’ is used. As a teacher, the flickering 16 millimeter of the mind may click through silent rows of heads bent over scantrons, diligently bubbling in their sheets, the clock ticking, soft-soled shoes administrating, envelopes ripping open, a lifetime of learning boiled down to a double digit number given on a curve. There is no mastery, there are only gradients, only differentials, only quantifiable measurements. No matter that the purpose of the test is to measure if a student will make it successfully though the first year of college. No matter that the strongest correlation to the test score is the student’s 3rd grade reading ability.
I happen to be in an ethical dilemma because of data. Specifically, the data driven instruction that is supposed to make out students smarter, faster, stronger, give them the competitive edge necessary to succeed in this capitalistic society of ours. This is partially because of the lack of relevancy in standardized testing – that is, there is little or no connection between ‘real life’ and standardized exam-taking – but is primarily because the tools we use to collect data, these standardized exams, make liars of us all.
There is no way to prepare for a norm-referenced exam, such as those given to students across this country’s high schools (eg, PSAE, ACT, PLAN, EXPLORE). The bell curve will nullify any testing clues, any Saturday morning sessions, any private tutoring. That is the JOB of the curve, to select out the cream of the crop for the limited number of college seats available. While K-12 shouts from the rooftops that all kids need to go to college, the colleges only have so much dorm space, and the professional fields only have so many salaried positions. Our data collection tool selects, and yet we use it as a way to measure our students on their way to mastery. We stand before our students and encourage, cajole, threaten, weep – trying to make them understand how the balance of their futures hangs by the outcome of these tests. Data Driven Instruction has taken away the importance of the classroom content and replaced it with a skills-based approach. As though sequencing the events is more important than actually knowing the events. Or that reading the graph is more important than retaining the information for generalization to other courses. Or that answering the equation theoretically with a calculator makes up for the inability to do multiplication quickly in one’s own head. Ironically, ACT’s homepage declares that the test is a curriculum-based test, opposing the growing trend that teaching ‘skills’ will lead to higher test scores.
Thankfully, there is a light at the end of the DDI tunnel and an end to the Dilemma of Dishonest Inspections. It too is called data. This data, however, comes from the classroom. In contrast to the images above, classroom data looks just like the classroom: attendance rosters, assignment grades, classroom participation, teacher-created tests, project rubrics, phone logs, referrals, student and parent conference notes, lesson plans and reteaching strategies, department and grade level meeting minutes, posting of grades and objectives, and walls of fame. The classroom teaches to mastery. Thus, using classroom data to measure quantifiable content-based (and skill-related) objectives, to drive the curriculum, to assess the abilities of the students and school not only leads us back to honesty, but has the potential to make the school a real learning environment rather than a test-prep machine.
The main argument against classroom assessments, from every quadrant, but primarily from the data experts, curriculum giants, and administration pertains to the reliability and validity of the classroom teacher. That is, does Mr. X’s English assessment REALLY test comparative relationships and does it do so at the 10th grade level? Does Ms. A’s math quiz ACTUALLY assess the students’ ability to sequence, or their ability to use the appropriate geometric equation? Here’s the thing, though. These questions don’t negate the teacher, not do they make obvious the need for standardized tests (norm-referenced or otherwise). In fact, what there questions do is make teachers the professional that they have worked to be. In order for teachers to be accountable for their students mastery levels, teachers have to use their own lessons and assessments to determine these mastery levels.
Does this excuse teachers from high failure rates? Or from having to provide support for high pass rates? Absolutely not. What this does do, however, is provide an opportunity for all-out honesty – take out the curve, admit the weakness at writing multiple choice questions, seek out help in creating rubrics and writing directions that are explicit and clear, find a mentor to help reteach content and spiral in skills to the next unit. What this does is create a school-wide learning community rather than a test-prep blitz.
Here we are with honest classroom data. Mountains, piles, drawers, files, books, binders, desks, computers full of data. This data drives our instruction every day and keeps us awake every night, and compels us to hunt down students when they miss our class. It’s because of data that we came into this field – to help kids learn to read, to get kids excited about math, to watch the class debate the issues. And this data is also what keeps us good teachers. To claim that Data Driven Instruction is possible from a source outside the classroom negates the very purpose of the classroom and the teacher. It obfuscates the purpose of education. It illuminates the purpose behind schooling. And as teachers, honest teachers working to solve our Dilemma of Dishonest Inspections, we shout from the rooftops that we do not school! We are here to educate. And we use honest data every day to do it.