Strong agents and weak systems: University support for school level improvement
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Abstract
This study examined individual and school level factors that advance and suppress the traits of high performing schools. Based on action plans and reflective journals of 28 school level practitioners in 14 schools across 10 school districts, researchers tracked the progress of each practitioner from participation in a university-based school improvement institute through the initial 5 months of action plan implementation at the school site. This study also presents a conceptual model for a strong system, based on an extensive literature review. Findings are as follows: (1) Internal, school-level change agents who are knowledgeable and skillful with the traits of strong systems were able to make significant inroads within weak systems. (2) School and district level leadership knowledgeable and skillful with the traits of strong systems were crucial to the sustainability of improvement efforts. (3) The effectiveness of change agents in initiating improvement did not necessarily align with positional power, confirming prior complexity research findings that posit non-linearity of change. (4) Effective change agents focused in their work with colleagues on the cultivation of intellectual dispositions and complex skills. Such activity stands in contrast to much contemporary Professional Learning Community (PLC) work (so called) that focuses on “training” teachers in scripted procedures and suggests that much contemporary PLC work needs to be redirected from the learning of procedural skills to the cultivation of intellectual dispositions and complex skills. University colleges of education, whose signature traditions include inquiry, analysis, and reflection, are well-positioned to support such work.
Keywords
Complex adaptive systems Complexity research Professional learning community School improvement School reform University partnershipsNotes
Acknowledgments
The authors are grateful to the Graduate School of Education at the University of Massachusetts Lowell for a Paquin-Adams Grant Award which supported this research. We are also grateful to Stuart P. Robertson whose expertise with QSR NVIVO Software assisted the authors in the design and use of our NVIVO shell.
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