Stephen Lane is a high school teacher with 10 years’ experience at a suburban high school outside of Boston, MA. He teaches history and economics and also coaches cross-country and track & field.
We are living in an age of the quants. In the social sciences, sports, and of course education, the number-crunchers rule. Information that can’t be reduced to a numerical essence is suspect, whether the subject is basketball or economics. In education, quantifiable data can be useful, but the current infatuation with numbers betrays muddled thinking, misallocates teaching resources, and rewards behavior we probably don’t want to see rewarded in teaching.
Now that I’m done preaching to the choir, I’d like to think about how to reverse this trend. Railing against the misapplication of numbers (in particular, standardized test results, and misguided comparisons of American students to their foreign counterparts) is important, but we also ought marshal the tools of the quants themselves – data – to support a more nuanced look at student achievement and quality teaching.
My aunt, a former school committee chair (don’t hold it against her), and uncle, a retired principal, both avow they knew good teaching after 5 minutes of classroom observation. A former student of mine, whom we’ll call Hermione (the brightest witch of her age), is an ed consultant on value-added models (again, don’t judge). She feels confident their models can measure a teacher’s impact – given 10 years of data in relatively unchanging circumstances. Neither a 5-minute observation nor 10 years of data seem like reasonable metrics, nor do they address the conditions underlying the performance.
Quants assume that teachers work primarily in a vacuum – that a teacher’s success or failure is primarily the product of individual ability, effort, or lack thereof. My experience differs. My growth as a teacher is primarily due to the culture within my department, and the guidance and example of my colleagues. I am not unusual: Interviews conducted with active and retired teachers in our district with at least 20 years of experience overwhelmingly identified fellow teachers as the primary influence on teachers’ development and improvement.
In a paper on compensation methods in manufacturing, economists Susan Helper, Morris Kleiner, and Yingchun Wang noted that incentivizing certain individual outcomes (e.g., production rate) tends to crowd out other worker activities, such as process and quality improvement, which require greater teamwork.[i]
Professor Helper was kind enough to respond to an email about her work, and noted:
“Individual incentive pay is … problematic when individual contributions to performance are hard to measure… this is especially the case when good performance is hard to define and/or has many competing objectives as is often the case in a lot of modern activities, teaching included. In these cases, group incentives, or even NO incentive (hourly pay) is better than individual incentives, because otherwise it’s hard to get individuals to engage in hard-to-measure activity (mentoring co-workers…), if the reward is for an easy to measure task that may be less important…”
Standardized test results are an easy measure of student achievement and teacher performance. But the trade-offs are unfortunate. Teachers are people too; people respond to incentives. If standardized tests are used to measure performance, teachers will respond accordingly: More test prep, less collegial collaboration. Over-quantification not only assumes teaching in a vacuum, it makes it more likely.
Further, teachers will set up incentives for students so that test prep will crowd out activities which hone hard-to-measure skills such as problem solving, creativity, decision-making, and teamwork. Over-quantification not only assumes that success is about attaining a certain score, it increases the likelihood that attainment of that score will be the only success.
Again, not a new argument. But I’d like to repackage the argument in the language of the quants. Can hard data make a case for the nuanced view of teacher and student success? Can it shape a message that breaks through the noise, reverses current trends, and changes the discussion? Let me ask several questions:
1 – What kinds of teamwork are significant and measurable in the teaching profession? Can we measure the degree to which teachers collaborate positively in a school?
2 – Is it possible to draw correlations between degree of teacher collaboration and student achievement? How exactly does teacher teamwork improve student performance?
3 – How to measure student achievement on hard-to-measure activities?
Producing data that helps teachers, policymakers, and the public understand what constitutes good teaching and real student achievement is a start towards knocking down the edifice the quants have built. Their numbers are simple because they ignore complexity. If we can’t make the complexity understandable, the quants’ simplistic view of education will reign unchallenged.
Granted, larger sociopolitical trends are at work, but trends are trends. They reverse. The tide will turn eventually, but we can do more to help the process along. What kind of data can be gathered? And how can we shape it into a more compelling message?
[i] Helper, Kleiner, Wang, Analyzing Compensation Methods in Manufacturing: Piece Rates, Time Rates, or Gain-Sharing. 2010, NBER Working Paper Series