Education Case Studies: Introduction | MinSIM | College Decision Making | High School Quality

Exploring Issues of Quality in a Vermont High School

Problem Statement:  In 2000, a local school board and the senior members of its administration engaged us to: 

• facilitate a deeper understanding of the long-term implications of the community’s continuing financial and demographic changes on the board’s capacity to manage this school “system,” and subsequently
• develop a system dynamics model (Computer Simulation) to assist the board in its decision-making. 

The starting point for the process began with a broadly framed question:  How can the school board and the administration maintain the high overall quality of its regional high school/technical center and its strong reputation in the community while recognizing financial pressures?

Approach: We implicitly drew upon the structure of our Ladder of Engagement to:

• Engage the board and administrators in sharing their respective concerns and KNOWLEDGE of the “problem,” its behaviors, and their root causes;
• Organize and integrate that knowledge into an UNDERSTANDING of the feedbacks through which key components of the system (students, teachers, and budgets) interact to generate those behaviors; and finally
• Through simulations of the school, identify and evaluate strategies to allow the board and administration to guide and INFLUENCE future developments in a desirable direction.

KNOWLEDGE

What do we know about the “behavior(s)” of the system?

We focused on two issues here:

• The starting point focused on developing agreement among board members and the administration around a common “problem” statement.  A variety of “mental models” were exposed at the table indicating major differences in people’s perceptions both in the financial challenges confronting the school district as well as the factor(s) that defined the school’s reputation and standing in the community. Through these conversations the group agreed to focus on school “quality” and to settle on a small set of measures to define that “quality.”
• With appropriate (and necessary) prompting on our part, the group agreed that a reasonable measure of quality revolved around two key indicators:  class size and class variety (in terms of the numbers of available options for student electives).  This focused the group’s attention, as illustrated in the map below, on the dynamic interplay between changing student numbers (based on changing matriculation, graduation, and/or early departures) and the school’s ability to provide enough classes or “sections’ to maintain both its traditional diversity of electives and its relatively small class size.

UNDERSTANDING

What “drives” the behavior of the system?

What developed from these conversations was a computer simulation, incorporating five dynamic “stocks” or elements within the system that influenced overall “quality.”   The interactions of these elements can be illustrated in the map presented below:

Changes in either student FTE numbers (A) or course sections (B) would reduce the “current school quality index” (a) (we assumed that changes that led to an enhanced quality index would not be as problematic).  A reduction in “current school quality index” or any board decision to increase its “desired school quality index” (b) would generate a “quality gap” (c).  Responding to this “gap” would involve funding (d) to enhance the numbers of faculty (and the classrooms to house them) (1), thereby adjusting the number of available “sections” and eliminating the “gap.”

The capacity to effect such necessary changes, however, requires “discretionary funds available to address need” (d).  These funds, in turn, are dependent upon the balance of “Budget $$” available (C) and the school’s current “Expenses” (D).  Any change in faculty size and/or classroom infrastructure would also become institutionalized and subsequently impact “Current Expenses” (D).  The challenge, then, of making appropriate “quality” decisions that are also financially sustainable, involves balancing the dynamics within (and between) each of the five areas.

INFLUENCE

Can this understanding be used to generate better policies to manage the system?

The final computer model was developed as a “flight simulator” to provide members of the school board and administration the means to explore a variety of “what if” scenarios, ranging from managing budgets (involving, for instance, changing hiring practices and/or salary/benefit scales) to contemplating implications of future enrollment changes on overall “quality” issues.  It is gratifying to us that, two years after the model was developed, the district financial administrator continues to update the model’s data each year and use it, often at the board’s request and with the board’s involvement, to contemplate the long term systemic implications of current developments and/or decisions.