Program Design Network (PDN)


The purpose of the UCEA Program Design Network (PDN) is to support collaborative engagement by education leadership faculty in leadership preparation design, redesign, and improvement efforts and aligns with UCEA’s commitment to continuous improvement.

The UCEA PDN is organized for UCEA faculty to work in cross-institutional teams in a facilitated program design networked improvement communities (PD-NICs) listed below:

PD-NIC: Candidate Selection and Recruitment

Facilitator: Casey Cobb (University of Connecticut)

Knowledge Worker: Wesley Henry (University of Washington)

University Programs:

            Florida Atlantic University

            Iowa State University

            Michigan State University

            Portland State University

            University of Iowa

            University of Texas

PD-NIC: Curriculum, Instruction, and Coherence

Facilitator: David Eddy-Spicer (University of Virginia)

Knowledge Worker: Amy Reynolds (University of Virginia/UCEA)

University Programs:

            Fordham University

            Loyola Marymount University

            Oklahoma State University

            University at Buffalo

            University of Georgia

PD-NIC: Mentorship and Coaching

Facilitator: Richard Gonzales (University of Connecticut) and Mónica Byrne-Jimenez (Hofstra University)

Knowledge Worker: Gopal Midha (University of Virginia/UCEA)

University Program:

            Auburn University

            Northern Illinois University

            St. Louis University

            University of Illinois-Chicago

            University of Virginia

PD-NIC: Powerful Learning Experience with a Focus on Equity

Facilitator: Mariela Rodríguez (University of Texas at San Antonio)

Knowledge Worker: Catherine Robert (University of Texas at San Antonio)

University Programs:

            George Mason University

            Penn State University

            University of Houston

            University of Wisconsin-Milwaukee

            Washington State University

PD-NIC: Preparation Partnerships

Facilitator: Karen Sanzo (Old Dominion University)

Knowledge Worker: Bryan VanGronigen (University of Virginia/UCEA)

University Programs:

            Florida State University

            New York University

            The Ohio State University

            Sam Houston State University

            University of Utah

Roles (UCEA, Facilitators, Knowledge Workers, Faculty)

  • PDN Faculty Team Participants: The role of faculty participants is to lead their program in design, redesign, or improvement efforts. Participating programs identify at least two faculty members that consistently engage in the PD-NIC.  
  • Facilitators: A facilitator serves as an external liaison between the PD-NIC and UCEA. The facilitator is also an organizer of PD-NIC meetings.
  • Knowledge Workers: The role of UCEA Knowledge Worker during the PDN is to document the PD-NIC improvement work.
  • UCEA: The role of UCEA during the PDN is to build the core capacity for improvement work, identify and make available resources for enhancing improvement work on the Networking Tool (online platform), and chart the progress of the PD-NICs.

Improvement Science: Based on a framework devised by the Carnegie Foundation for launching a viable networked improvement community, PD-NICs will begin their work with the following domains of activity:

  1. Conducting a program self-assessment that clearly identifies program strengths and weakness, particularly around the PD-NIC focal area.
  2. Identifying an improved future state with clear unambiguous and measureable goals;
  3. Learning the philosophy and practices of Design Thinking and Improvement Science.
  4. Developing a theory of improvement that specifies high-leverage drivers hypothesized to help make progress toward a clear, unambiguous, and measurable aim;
  5. Using improvement research methods that specify a concrete approach to disciplined experimentation through iterative testing of new routines and practices related to the high-leverage drivers; and
  6. Building a measurement and analytic infrastructure that enables the network to formatively track progress and learn from efforts to experiment with process improvements. (Russell, 2016, p. 3)