The trouble is that while some 70.1 percent of new high school graduates started college last fall, many people already enrolled in community colleges don’t finish. Leonhardt reports:

Less than a third of all students who enroll in community colleges with the intention of getting a two-year degree — a degree leading to jobs in nursing, auto repair, preschool education — ever do so at any college, statistics suggest.

On top of that, data on students in community college is apparently scarce. A CAP colleague explains that the federal student loan and Pell grant structure is designed to get students enrolled, but does little to track them on their way to a degree or credential.

While that’s unfortunate, it’s not surprising. Lack of data is a consistent problem in many corners of the education system. Another CAP report demonstrates the problems that arise from the fact that most high schools only pay attention to how many of their students move on to college, not how well prepared they were to make the transition. Fortunately, there are success stories of schools that have recalibrated their learning goals to ensure that students aren’t just exposed to college preparation work, but that they actually learn how to do it.

Now TFA is all about capturing as much student tracking data as possible, within the context of a given year. That’s no small order, but the year is the scope of your work as a teacher. What if, as a teacher, you kept track of this information from year to year, and were able to follow your student through the school system to see how they were doing in the subject you taught? And what if the district also kept data on college enrollment, and those systems synchronized with college data. What if, years down the road, you knew what role you and other teachers played in shaping that student’s education?

Complicated, sure, but it’s just text in a database.

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.

Take this report that my humble employer, the Center for American Progress, and College Summit released last week. The authors explain that while many public high schools have a rigorous college preparation curriculum that includes Advanced Placement classes and the like, smart successful students often make it to their first year of college and find themselves totally adrift, unprepared for the academic expectations of higher ed. High schools, despite their best intentions, often don’t know whether or not they’re preparing students for success in college because they don’t keep track of how those students perform in their “13th” year. Simply put, they don’t measure the outcome of their work. It’s a matter of counting.

Now, building a data system that follows students from secondary school to potentially far-flung colleges is not trivial, but the principle—take note of what you do, measure, and make adjustments to better meet your goals—is one of those simple ideas that made for a lot of successful projects over the past decade.

The business community is generally out ahead on this whole counting and measuring thing, but it’s also worth noting that much of the exponential growth of web-based and social media technologies over the past 10 years is due, fundamentally, to the ability to use computers to measure what people are doing and craft tools and products that fit people’s needs. Google does this, incrementally, billions of times day. Similar story for most everything else you clicked on around the Internet today. But in a whole variety of other fields, counting has been around for decades, and its impact has snowballed in the face of cheap, fast computing, and the basic acceptance that if you want to understand a problem, you need data.

Atul Gwande’s Better offers a terrific tour of how measurement has improved various corners of medicine since the middle of the 20th century. Hospitals have beaten back onslaughts of drug-resistant bacteria by persuading everyone to wash his or her hands and counting the results. The introduction of the Apgar score, which enumerates on a 0-10 scale the health of newborn infants upon delivery, lead to a dramatic upswing the in the quality of care for infants and dramatic upswing in survival rates, which are now about 8 times better than they were in the 1930s. And the 90 percent survival rates for U.S. combat troops wounded in Iraq and Afghanistan is due in large part to the fact that military physicians diligently record copious information on injuries, treatments, and outcomes—so they can constantly find ways to improve on their success.

The next big step in education and in medicine is to take what we’ve counted, standardize the information, and compare it. That means national testing and data standards for education and interoperable electronic health records for medicine. Fortunately, there’s federal money for both of those projects: $4.35 billion for schools and $19 billion health information technology.