Reading this week:
Halverson, R.; Grigg, J.; Prichett, R.; Thomas, C. (2007). The New Instructional Leadership: Creating Data-Driven Instructional Systems in School. Journal of School Leadership. 17: 159-193.
Thorn, C.A. (2001, November 19). Knowledge Management for Educational Information Systems: What Is the State of the Field?. Education Policy Analysis Archives. 9(47). Retrieved September 5, 2007 from http://epaa.asu.edu/epaa/v9n47/.
Unit of analysis. That seemed to be the thing that kept popping out at me this week. This was stated directly by Thorn (2001) that if the student is the unit of interest, then the data gathered should be attributes about the student. Student Information Systems, however, tend to be designed to produce reports for district-level analysis, not for the classroom. Halverson et al. (2007) found a mismatch or inoperability of data in the district’s high-tech data storage as opposed to the local collection and storage of low-tech data. The logical goal of the proposed data-driven instructional system is thus to link the results of summative data with formative information systems that teachers can use to improve instruction. The goal of practical measurement, as proposed by Yeager et al. (2013) is that “educators need data closely linked to specific work processes and change ideas being introduced in a particular context” (p.12).
In the past, I have associated data-driven decision making as context-blind work whose sole purpose was to improve standardized test scores. The readings this week as well as the networked improvement communities (Bryk et al., 2010) from a few weeks ago has given me a different perspective on what it means to use data to inform instruction, design, and communities. Continue reading “Reaction 11: Data-Driven Instructional Systems”