one shovel

“When you only have one guy with a shovel, you can’t build a dike to hold back the sea.”

Orson Scott Card

Ever been to the beach and tried to build a sand castle when the tide was coming in? Futile effort. Particularly if it is a solo effort. Perhaps if the whole family was engaged in building a berm you might have a chance, but the victory will be short-lived. The incoming tide will eventually overwhelm your efforts or a rogue wave will obliterate your work. If you are the only one in your system with a vested interest in building an effective school data team, then your ability to tend to the data in a manner that will influence instruction will eventually be overwhelmed by other administrative responsibilities. Given the need to share tasks, the operational paradigm of Distributed Leadership is essential for the success of school data teams.

Distributive Leadership is more of a cultural construct then it is a set of protocols. Distributed Leadership is not about assigning a task to another person, it is a cultural phenomenon. And be aware, the distributive leadership required for data teams is a new paradigm for many districts, so therefore it will be considered as either an intrusion or as an innovation. It is an intrusion if there is no sense of ownership and it occupies time that teachers would otherwise spend on “getting their work done”. It is a welcome innovation if it is an efficient and effective process that guides instructional practices and decisions about students.

Decisions about students include using student performance data to determine which interventions are necessary and what form of differentiation is required. Changes to instructional practices include using student performance outcomes to help determine pacing, the targeting of specific standards, and in identifying the best instructional practices.

Richard Elmore’s (2000) article, Building a New Structure for School Leadership, states that there is a need to focus on instruction, but administrators who focus on instruction are rare. He states that leaders need to harness organizational coherence and that Distributed Leadership allows various competencies to emerge and coalesce. However, Elmore finds that while changes do occur, improvements are rare.

Andrew Hargreaves (2005) work studying educational reform during the last three decades with high school teachers in New York and Ontario concludes that sustainable educational leadership requires distributing leadership. However, he finds that Distributed Leadership will be hindered by the prevailing culture of teacher autonomy. Hargreaves (2001) asserts that occupations have their own “emotional geography” (p. 4) and that teachers are reluctant to acknowledge that other teachers may be more effective. Unfortunately this interferes with one of the goals of looking at disaggregated data; which is to identify best performance/best practices that exist within a school. The hope is that you can discover a strategy or practice that has success, meaning that one teacher will have more success on any given topic when compared to others. This is one reason why the practice of data teams must be considered in context to the school culture and climate.

Assuming that you can weave the Distributed Leadership into the culture of the school, what does it look like in practice? The literature on distributed leadership is unclear as to what form it takes and how it impacts school leadership (Harris, 2004). Harris states that we need proof for what constitutes effective practice or otherwise we are just contributing to multiple theories and constructs which may prove misleading. Fortunately, a 4-year long case study of the use of data teams in five urban school districts in Rhode Island helps in articulating effective practices (LaChat & Smith, 2005). Also, in a Q-and-A session titled, Making Data Teams Work, Douglass Reeves names school systems in Elkhart Indiana, Norfolk Virginia, and Fort Bend Texas as examples of districts with good practices.

The initial findings of the study by Lachat and Smith from five high-poverty, low-performing, urban high schools demonstrate that there are four main factors influencing the effectiveness of school data teams: 1) the quality and timeliness of the data, 2) the ability of the technology and data-warehousing system to provide disaggregated data, 3) utilizing a clear set of questions to collaboratively look at the data, and 4) the role of school climate, culture, and leadership has on the willingness of the teachers to engage in the process. The authors of the study state that the schools had varying degrees of success in implementing data teams. This initial study does not offer student performance data to support the work, but they do cite anecdotal examples of progress being made due to consideration of data.

So what is the function of your school-wide data team? Do they shepherd the work produced in the instructional data teams? Are they a clearing house, funneling results and data to the pertinent parties? Do they serve as cheerleaders for the process, acting as culture builders? Take a tip from Mark Parker, Nike’s designer and CEO, who commented after attending a session of Nike’s think tank for innovation, where new ideas for shoe designs are vetted: “Edit and amplify. I’m trying to amplify the innovation agenda further, and short-list the things that will make the biggest difference. That’s an art and a science” (McGirt, 2010, p. 69). So for schools, the science part may be the disaggregation, dissemination, and dissection of the data; and the artistry is the culture building.

Edit and amplify.

Have your school-level data team discuss the key data points for your school and have them share in the work of building the data-driven decision process. But, if you are reluctant to give up your shovel and feel that if you alone worked with enough focus and determination you could get the job accomplished, then let me remind you of the legend of John Henry. John Henry was a miner that single-handily tried to outperform a steam-driven drill. The good news is that he completes the task, the bad news is that he then collapses and expires. Don’t let data be the death of you, don't let the volume of data inundate you; distribute the load by creating the culture that will embrace the data analysis process in order to improve the teachers’ instructional practices.

Make a good day,

Tod

PS. Card, O. S. (1999). Ender’s Shadow. New York: Tom Doherty Associates Book. Quotation from page 364.

PSS. Elmore, R. F. (2000). Building a new structure for school leadership. Retrieved from the Albert Shanker Institute website http://www.ashankerinst.org/downloads/building.pdf

PSSS. Hargreaves, A, (2001). Emotional geographies of teaching. Teachers College Record, 103(6), 1056-1080.

PSSSS. Hargreaves, A. (2005). Editorial statement. The Educational Forum, 69(2), 101-110.

PSSSSS. LaChat, M. & Smith, S. (2005). Practices that support data use in urban high schools. Journal of Education for Students Placed at Risk, 10(3), 333-349, Lawrence Erlbaum Associates, Inc.

PSSSSSS. McGirt, Ellen (2010, September). Artist. Athlete. CEO. Fast Company, 148. 66-114. Retrievable at http://www.fastcompany.com/magazine/148/artist-athlete-ceo.html

PSSSSSSS. Reeves Q & A: Making Data Teams Work, retrieved from http://blogs.edweek.org/edweek/District_Dossier/data/