Where is Data Driving Us?
Many of our schools these days are guided by a business school practice known as Data-Driven Decision-Making (DDDM). This approach means that we do not base decisions on whim or convenience, but rather rely on actual student achievement outcomes to guide us. The first step in this process is determining which data we actually care about. That key decision has been made for us in the public schools by the mandates of NCLB. The data that matter most are student test scores in language arts and math. Data-Driven Decision-Making means we then must make choices that will increase those scores.
The term "Data-Driven Decision-Making" has a sort of value-neutral, rational sound to it. It means we are basing our choices on facts, that we are willing to make tough choices in the interest of student achievement. That should be good news, right?
But the choices that are made actually do carry value judgments, and I am not sure that we are considering all the relevant data when we make these decisions.
A few weeks ago, a San Diego area teacher named Ellen posted the following comment to this blog. She wrote:
I can see the disparity on a daily basis, as the tight economy and the effects of NCLB with its relentless pursuit of annual "progress" narrow the scope of my students' education. Where once students had the opportunity to express themselves in art, music or organized sports, they are now forced into the straightjacket of language arts and math.
I am required to have a daily 2 1/2 hour language arts block (using a scripted program, no less) and a 1 1/2 hour math block. Science was recently added to this limited curriculum because it is now tested on the CSTs, but there are no hands-on experiments because of the time constraints and lack of equipment. Science consists of students reading from a textbook and answering multiple choice comprehension questions in a workbook.
Recently our school celebrated an increase in test scores, but teachers were castigated because the English Learner subgroup did not pass.
It appears that the program Ellen describes has, in fact, resulted in increased test scores in Language Arts and Math. Thus, according to the rules of Data-Driven Decision-Making, it should be considered a success. But Ellen's description has me wondering about the nature of the data we are relying upon, and what questions we might ask to uncover additional data.
1. The CST data we are using measures primarily language arts and math performance. What information might we be missing as a result of being driven by this narrow set of data?
2. What academic, cultural and physical activities were cut to make room for the daily regime of 150 minutes of Language Arts and 90 minutes of Math? Has this data been sought?
3. What might the impact of the elimination or reduction of hands-on science, history, art, music and PE be on the long-term success of our students? Has success in math and language arts come at the expense of future success in other subjects? Is this question being asked?
Scientists know that the data one collects depends on the questions we ask. It is possible to go a long way down the wrong path if we focus on the narrow set of questions posed by NCLB.
The underlying issues behind my questions are ones of equity. These intensive language arts and math programs are motivated by concerns about inequitable outcomes for the mostly Latino and African American students attending the affected schools. But there are also equity concerns raised by the time taken that must come at the expense of other subject areas. It is the higher-performing schools that have more time for science, history, art, etc. because they are not obliged to spend 90 minutes a day on math and two and a half hours a day on language arts.
This raises a bigger question about Data-Driven Decision-Making in general. This term is used in a way that implies an objective, value-neutral focus on results. In fact, the data is so limited that the decisions one makes are constrained within a narrow range of options. The data gathered carries a set of values that have been determined, in this case by priorities set by NCLB.
Another business school term is "opportunity cost." There is no free lunch. If our school communities wish to make student achievement on math and language arts our highest priority - over science, history, art, PE, and music, then at the very least we need to be aware of what we are giving up in the bargain. I have a problem with policymakers and school leaders making this decision without acknowledging that there are in fact choices being made, and that there are tradeoffs, and that these are decisions that have values embedded within them. I have a problem when we do not even measure the impact these choices are making in other areas, and then we act as if our decisions are driven by pure data.
What do you think? What data is missing from the decisions being made at our schools?