K-12 Education

Constitution For Effective School Governance

Our guest author today is Kenneth Frank, professor in Measurement and Quantitative Methods at the Department of Counseling, Educational Psychology and Special Education at Michigan State University.

Maybe it’s because I grew up in Michigan, but when I think of how to improve schools, I think about the “Magic Johnson effect." During his time at Michigan State, Earvin “Magic” Johnson scored an average of 17 points per game. Good, but many others have had higher averages. Yet, I would want Magic Johnson on my team because he made everyone around him better. Similarly, the best teachers may be those that make everyone around them better.  This way of thinking is not currently the focus of many current educational reforms, which draw on individual competition and market metaphors.

So how can we leverage the Magic Johnson effect to make schools better? We have to think of ways that teachers can work together. This might be in terms of co-teaching, sharing materials, or taking the time to engage one another in honest professional dialogues. There is considerable evidence that teachers who can draw on the expertise of colleagues are better able to implement new practices. There is also evidence that when there is an atmosphere of trust teachers can engage in honest dialogues that can improve teaching practices and student achievement (e.g., Bryk and Schneider, 2002).

Is Teaching More Like Baseball Or Basketball?

** Republished here in the Washington Post

Earlier this year, a paper by Roderick I. Swaab and colleagues received considerable media attention (e.g., see here, here, and here). The research questioned the widely shared belief that bringing together the most talented individuals always produces the best result. The authors looked at various types of sports (e.g., player characteristics and behavior, team performance etc.), and were able to demonstrate that there is such thing as “too much talent," and that having too many superstars can hurt overall team performance, at least when the sport requires cooperation among team members.

My immediate questions after reading the paper were: Do these findings generalize outside the world of sports and, if so, what might be the implications for education? To my surprise, I did not find much commentary or analysis addressing them. I am sure not everybody saw the paper, but I also wonder if this absence might have something to do with how teaching is generally viewed: More like baseball (i.e., a more individualistic team sport) than, say, like basketball. But in our social side of education reform series, we have been discussing a wealth of compelling research suggesting that teaching is not individualistic at all, and that schools thrive on trusting relationships and cooperation, rather than competition and individual prowess.

So, if teaching is indeed more like basketball than like baseball, what are the implications of this study for strategies and policies aimed at identifying, developing and supporting teaching quality?

Rethinking The Use Of Simple Achievement Gap Measures In School Accountability Systems

So-called achievement gaps – the differences in average test performance among student subgroups, usually defined in terms of ethnicity or income –  are important measures. They demonstrate persistent inequality of educational outcomes and economic opportunities between different members of our society.

So long as these gaps remain, it means that historically lower-performing subgroups (e.g., low-income students or ethnic minorities) are less likely to gain access to higher education, good jobs, and political voice. We should monitor these gaps; try to identify all the factors that affect them, for good and for ill; and endeavor to narrow them using every appropriate policy lever – both inside and outside of the educational system.

Achievement gaps have also, however, taken on a very different role over the past 10 or so years. The sizes of gaps, and extent of “gap closing," are routinely used by reporters and advocates to judge the performance of schools, school districts, and states. In addition, gaps and gap trends are employed directly in formal accountability systems (e.g., states’ school grading systems), in which they are conceptualized as performance measures.

Although simple measures of the magnitude of or changes in achievement gaps are potentially very useful in several different contexts, they are poor gauges of school performance, and shouldn’t be the basis for high-stakes rewards and punishments in any accountability system.

Multiple Measures And Singular Conclusions In A Twin City

A few weeks ago, the Minneapolis Star Tribune published teacher evaluation results for the district’s public school teachers in 2013-14. This decision generated a fair amount of controversy, but it’s worth noting that the Tribune, unlike the Los Angeles Times and New York City newspapers a few years ago, did not publish scores for individual teachers, only totals by school.

The data once again provide an opportunity to take a look at how results vary by student characteristics. This was indeed the focus of the Tribune’s story, which included the following headline: “Minneapolis’ worst teachers are in the poorest schools, data show." These types of conclusions, which simply take the results of new evaluations at face value, have characterized the discussion since the first new systems came online. Though understandable, they are also frustrating and a potential impediment to the policy process. At this early point, “the city’s teachers with the lowest evaluation ratings” is not the same thing as “the city’s worst teachers." Actually, as discussed in a previous post, the systematic variation in evaluation results by student characteristics, which the Tribune uses to draw conclusions about the distribution of the city’s “worst teachers," could just as easily be viewed as one of the many ways that one might assess the properties and even the validity of those results.

So, while there are no clear-cut "right" or "wrong" answers here, let’s take a quick look at the data and what they might tell us.

Librarians, Libraries, Serendipity And Passion

Our guest author today is Connie Williams, a National Board Certified Teacher librarian at Petaluma High School in Petaluma, CA, past president of the California School Library Association, and co-developer of the librarian and teacher 2.0 classroom tutorials.

Down the road from where I live, on the first-of-the month, a group of vintage car owners gather for a “cars and coffee” meet up. The cars that show up with their drivers cover many years and obsessions. Drivers park, open up the car hoods and take a few steps back and begin talking with other car owners and visitors who happen by. These are people who are interested in the way cars work, their history, and they all have stories to share.

How do they know so much about their cars? They work on them – gaining insight by hands-on practice and consultations with experts. If they’re wealthy enough, they pay someone else to do the work, yet they don’t just hand over their cars to them. They read about them, participate in on-line groups, ask for guidance, and they drive them. Most often, when they drive them, someone stops and asks questions about their cars and they teach what they know to others. 

This is an example of the kind of learning we would hope for, for all our students – a passion that is ignited and turns into knowledge that is grown, developed, and shared. In this sense, it is inquiry – asking questions and taking the required steps to answer them – that is at the heart of learning.

The Bewildering Arguments Underlying Florida's Fight Over ELL Test Scores

The State of Florida is currently engaged in a policy tussle of sorts with the U.S. Department of Education (USED) over Florida’s accountability system. To make a long story short, last spring, Florida passed a law saying that the test scores of English language learners (ELLs) would only count toward schools’ accountability grades (and teacher evaluations) once the ELL students had been in the system for at least two years. This runs up against federal law, which requires that ELLs’ scores be counted after only one year, and USED has indicated that it’s not willing to budge on this requirement. In response, Florida is considering legal action.

This conflict might seem incredibly inane (unless you’re in one of the affected schools, of course). Beneath the surface, though, this is actually kind of an amazing story.

Put simply, Florida’s argument against USED's policy of counting ELL scores after just one year is a perfect example of the reason why most of the state's core accountability measures (not to mention those of NCLB as a whole) are so inappropriate: Because they judge schools’ performance based largely on where their students’ scores end up without paying any attention to where they start out.

The Equity Projection

A new Mathematica report examines the test-based impact of The Equity Project (TEP), a New York City charter school serving grades 5-8. TEP opened up for the 2009-10 school year, receiving national attention mostly due to one unusual policy: They paid teachers $125,000 per year, regardless of experience and education, in addition to annual bonuses (up to $25,000) for returning teachers. TEP largely makes up for these unusually high salary costs by minimizing the number of administrators and maintaining larger class sizes.

As is typical of Mathematica, the TEP analysis is thorough and well-done. The school's students' performance is compared to that of similar peers with a comparable probability of enrolling in TEP, as identified with propensity scores. In general, the study’s results were quite positive. Although there were statistically discernible negative impacts of attendance for TEP’s first cohort of students during their first two years, the cumulative estimated test-based impact was significant, positive and educationally meaningful after three and four years of attendance. As always, the estimated effect was stronger in math than in reading (estimated effect sizes for the former were very large in magnitude). The Mathematica researchers also present analyses on student attrition, which did not appear to bias the estimates substantially, and they also show that their primary results are robust when using alternative specifications (e.g., different matching techniques, score transformations, etc.).

Now we get to the tricky questions about these results: What caused them and what can be learned as a result? That’s the big issue with charter analyses in general (and with research on many other interventions): One can almost never separate the “why” from the “what” with any degree of confidence. And TEP, with its "flagship policy" of high teacher salaries, which might appeal to all "sides" in the education policy debate, provides an interesting example in this respect.