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Scaling Up Through Networked Improvement (SUNI) 

Supporting leaders in postsecondary institutions to scale up evidence-based innovations, such as math pathways, through coaching on organizational change practices.

Despite evidence of the effectiveness of some reform efforts in postsecondary education, innovations developed and evaluated at small scale are challenging to scale widely. In order to realize the broader impacts of evidence-based interventions, such as math pathways, knowledge is needed about how institutions can adopt, implement, and scale reform.  

Purpose

The goal of the Scaling Up Through Networked Improvement (SUNI) project is to test and refine a practical theory of scaling postsecondary math pathways reforms centered around building institutional leadership capacity. In particular, the project examines the practices of institutional leaders in supporting or hindering those efforts when they are supported by leadership coaching for organizational change.

Audiences Served

SUNI provides coaching for postsecondary leaders focused on planning and leading organizational change.

Project Activities

Postsecondary leaders receive coaching as they implement math pathways reform effectively, sustainably, and at scale. Outputs, such as a toolkit about organizational change practices, will benefit leaders engaged in innovation and reform efforts. 

The project includes two studies: 

  • a quantitative outcomes study to understand relationships among student achievements, faculty and classroom characteristics, and college-level factors 
  • comparative case studies of institutional leadership teams that explore processes and practices to implement math pathways at scale 

Project Director

Ann Edwards

Ann R. Edwards

Ann R. Edwards is Senior Director of Mathematics Education. She is a nationally recognized leader in mathematics education with over 30 years of experience in research and development in mathematics learning, instructional practice, teacher learning, curriculum development, and policy.

Funder

This project is funded in full by the National Science Foundation through award number 1820830. 

Project Duration

7 years (9/1/2017–8/31/2024) 

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