Does high-stakes accountability and increased centralization limit or threaten capacity for organizational learning in schools?
High-stakes accountability is a growing movement based on assumptions of measurement and standardization as successful drivers of school reform. With increased testing requirements and the introduction of common core standards, macro-level mandates are coming down to schools with little consideration of how these changes play out at the level of individual behavior. The general consensus is that top-down control necessarily leads to changes at the micro level. Without models for considering emergent behavior, school systems are held to weak and untested assumptions about individual behavior that will purportedly lead to desired systemic results.
Schools are social entities founded on interdependent relationships, and trust acts on both engagement and motivational levels to instigate and sustain buy-in for change. This represents an opportunity for combinations of agent-based and network modeling. The organizational learning theory of school reform considers school culture, climate, and professional learning communities as a framework for how certain schools are able to spread new practices and individual pockets of knowledge across a building. Underlying tension between politics, efficiency, and sensitivity exist in the management of organizational learning , particularly as schools increase in size and as new accountability reforms remove local capacity and flexibility by adding restrictions. These models begin looking at the idea of individual control from the teacher point of view.
I developed two models. The network for my initial base model was developed off interview data from a school site, while the abstract extension of the base model allows for varying formations based on underlying network structure.
The main variables and interactions for my model are as follows:
AGENTS: Teachers, Administrator(s)
Teacher-restricted: teacher to administrator ratio of global control
Degree-skeptical: # interactions needed before new idea adoption
Knowledge: amount of new idea absorbed
Trustingness: # links per individual
Administrator and teacher agents move randomly at a certain fraction of time steps based on the degree teacher-restricted. Agents only absorb knowledge from agents they have a trust link with. Agents absorb a certain amount of knowledge with each interaction based on degree-skeptical. Agents become believers once they have fully absorbed an idea. They can then begin influencing others.
To begin, select the size of your model school and the individual staff preferences
The underlying structure can be administrator centered, or not.
As agents learn a new a new idea, they turn green. My model was in part inspired by infection models of the spread of disease throughout a population.
The main results I got from this model included a large number of exponential and long tail curves suggesting that, at high numbers of staff, learning nearly always slows down for the final agents regardless of network/teacher-restrict value.
A surprising finding included the discovery that, across all network types and varying numbers of total staff and all other variables, degree teacher-restricted led to longer absorption of an idea. But full teacher restriction did NOT yield the highest time steps to completion.
My future extensions for this model include variations with staff turnover, multiple competing ideas, and growing network dimensions.