The data on measuring big goals

This is the second written response to the TFA pre-institute work (response 1). The focus is on the importance of setting big goals.

Research demonstrates that leaders who set exceptional expectations for their teams can get exceptional results. TFA’s own data bears this out for teachers who set lofty goals for their students. But new teachers will lack an important component of the argument that their students can meet these big goals: evidence that that teacher’s students have successfully hit high expectations before.

Addressing a new class of chemistry students on the first day of school, Paul Holloman says in the video for this exercise: “If you don’t care about making an A, there’s the door. Hit it. Get gone now. Because I don’t want to have you in my class if you’re not willing to work and make an A.”

His tone, as he admits, is blunt. He is stern and even intimidating as explains his expectations for hard work and attendance. “There’s nobody in here who can’t make an A,” he says. At first glance, this might sound like an ambitious but brutal pep talk. But for an observer, what makes his expectations talk absolutely convincing is the data he has to back it up from his previous three years in the classroom.

Over those three years, his class average has been a 93, he tells the new students. He points to a chart on the wall by the door displaying the test scores from the previous semester’s end of course exam. “This is my job,” he says in an after-class interview, “It’s serious business.” To demonstrate his commitment to his job, he tells the class that he is regularly available to help them, even answering question for athletes during halftime at basketball and soccer games.

Taken altogether: the firm classroom rules, the willingness to be available for many hours of outside-the-class help, and the record, written right there on the wall, of producing some of the highest student achievement in the state of North Carolina, all make the goal of a class A average on the final exams seem both sufficiently ambitious but also feasible.

Goals this specific have not driven most of my professional work. Somewhat by necessity, they have been more abstract and my colleagues and I have not tracked them with quantifiable metrics. For instance, Science Progress, the magazine of progressive science and technology policy I work for currently, set out to draw a clear connection between science and the progressive values of pragmatism, justice, and equality. The project began with the understanding that 1) no such publication existed in this specific space, 2) there were influential conservative journals generating a significant amount of discussion around issues of science and public policy, and 3) at the time of the launch, in 2007, a conservative presidential administration had severely damaged the relationship between science and policymaking by attacking science that did not support favored policy outcomes.

Three years later, the magazine enjoys the respect of colleagues and contributors, has generated good responses to certain pieces of content, and has generally seen steady attention as measured by website traffic and email list metrics. But while we may have a big goal that is fairly easy to state—to influence public policy by connecting science and progressive values—our ways of measuring whether or not we have hit that goal have remained qualitative and imprecise.

Considering where the project is now alongside the readings on the importance of setting big goals, two facts stand out. First, setting goals and working hard did make the first two years of the project a success: my colleagues and I worked hard, often outside normal hours, to ensure the success of the magazine and the larger political goals it represented. In that regard, I see the clear benefits of setting lofty goals to aim for and the utility of not setting a prescribed path to get there. We experimented with a variety of topics and types of content and attracted more of the same as a result. Likewise, students in my future classroom will see big, ambitious goals before them, and we will experiment with the best instructional tools to help them learn and reach those expectations.

But second, I see clearly now that part of the problem with our plans for Science Progress lie in the fact that we have articulated few measurable goals for checking our progress toward the lofty expectations we set. What’s heartening to learn is that there are proven ways of creating quantitative milemarkers for abstract goals. As Steven Farr explains in Teaching As Leadership, the Cleveland Orchestra set out to define its success as something highly abstract and subjective-sounding: “artistic excellent.” To measure their progress towards that goal, they crafted proxy indicators, including the number of standing ovations, the number of pieces they could play perfectly, invitations to prestigious festivals, ticket demand, requests from composers to debut new works with the orchestra, and other groups that imitated their style.

The point being that even for something as abstract as achieving “artistic excellent,” setting measurable indicators was not only possible, but facilitated getting a large group of people to move towards the same big goal. While I won’t be able to walk into my classroom this fall with three years of data, like Mr. Holloman, to back up my claim that I can motivate a group of students to work together with similar ambition, I will understand the method and know that it is possible.