Our Starting Points

As we think and write about the Legible University, we currently work from three main propositions. Two are about the nature of the University, and one is about the scope and generality of our discussion. Several other implications follow from them. These all need more exploration and elaboration, and will be the focus of many posts.

  1. The University is a complex system.
  2. The University is a built environment.
  3. We’ll stick to speaking about “the University”.

 


Big Proposition #1: The University is a complex system.

A unified, consensus definition of ‘complex system’ does not yet exist, and our working concept of it will take many posts to become completely clear. A quick look at the two words will get us started though.

System

The Merriam-Webster Dictionary generally defines ‘system’ as “a regularly interacting or interdependent group of items forming a unified whole.”

More technical approaches to define ‘system’ exist but they vary by context and problem domain. Definitions are often much more precise for physical/natural systems than for social systems. Rather than direct definitions, most approaches indirectly define ‘system’ by inventorying their characteristics.

The key characteristics of a system that we are most interested in are their interdependent structures, ill-defined boundaries, behaviours that trigger changes to other parts of the system or loop back on themselves.

Complexity

Complexity doesn’t have a unified, consensus definition either. Definitions of complexity often depend on a particular definition of a system, and vary depending on the discipline making the definition. The definitions typically relate to some manner of describing the large number of interactions and kinds of relationships between the elements.

Weaver (1948) distinguished between disorganized complexity and organized complexity:

Disorganized complexity: A result of a system having a very large number of interacting parts, like the molecules in a container of gas. The behaviour of the individual parts may be seen as random, but the behaviour of the whole system may be understood using probability and statistics.

Organized complexity: The non-random, or correlated, interaction between the parts of a system. Via that interaction, the system manifests properties that are neither manifested in the individual parts, nor directly dictated by the individual parts. These are often called ’emergent properties’.

Organized complexity, with its emergent properties, is the more intriguing type for us, though disorganized complexity also plays a role.

These are some implications of viewing the University as a complex system:

Wicked Problem characteristics apply to understanding the University.

We will have much more to say about this one.

Social Mess characteristics apply to understanding the University.

We will have much more to say about this one too.

There are multiple ways of parsing the University.

Given the complexity of the University, each way of parsing it produces an approximation or a partial view of the University. There is a lot of uncertainty, approximation, and invisibility within any view of the University. It does not mean that all ways are equal, however. Some are more official than others, some are more accurate than others (by the same specific measures), and the two things don’t always correlate.

Following this through to action, there are differences between the official ways of seeing and designing the University versus how people actually navigate the University.

The University may be viewed from multiple “neighbourhoods” (or spheres): things are simultaneously operating in different ways, for different reasons, to accomplish different goals, in different parts of the University. This creates frames: some phenomenon might be caused by something happening within a different sphere, and if that sphere is not within one’s view, then it may be difficult or impossible to understand that phenomenon.

Multiple scales operate simultaneously: a Faculty office may be treating a particular problem in a much different way than a department within the faculty is treating it, and an individual may be approaching it in yet another way. This also creates frames: some phenomenon might be caused by something happening at a different level, and if that scale is not within one’s view, then it may be difficult or impossible to understand that phenomenon.

Adequately understanding a particular phenomenon within the University usually requires many fragmented views through different lenses. Each lens implicitly defines what you can see, and what you can’t, and it’s good to understand those limits when using the lens.

There is great benefit to using metaphors of other complex systems to get new insights into the University.

Complex systems have similar patterns and behaviours, so concepts that are clearly seen and understood in one system can often help us uncover elements of another system.

Some metaphors we’re going to work with, in roughly decreasing order of our familiarity:

  • urban / cities
  • exploration, navigation, mapping, cartography
  • ecology
  • economy
  • human health
  • magic and ritual
  • We’re sure we’ll add others to this list…

Uncertainty, ambiguity and incompleteness are inherent, and impossible to avoid.

To address this challenge, we have to use multiple lenses, but these only take us so far. At that point we tend to fill in the blanks based on our own past experience and knowledge. One thing we often observe, in ourselves and others, is that it’s easy to fall off the edges of your expertise without knowing it, closing down possibilities and contradictions before we really know what we’re dealing with.

 


Big Proposition #2: The University is a built environment.

The physical aspect is important, but is only one manifestation of the University’s built environment. A university’s built environment involves numerous intersecting, overlapping, and sometimes discrete dimensions:  social, political, virtual, intellectual, epistemological, aspirational and economic, for example.

It also suggests that the theory and methods from several practices typical of working with built environments can be carefully adapted and applied:

 


Big Proposition #3: We’ll stick to speaking about “the University”.

We make it a point to not use “higher education”, “post-secondary institutions”, or “learning institutions”. This may seem exclusionary to people in colleges, secondary schools, and other learning institutions. It is not intended to be exclusionary, nor because we believe these ideas don’t apply to other learning institutions.

We do this because we don’t know how far our metaphors, ideas, and conclusions may be applied. The ideas we present here are developed by our experience and by what informs us, which is universities. We assume that these ideas are generalizable to some degree, but are not completely generalizable to all learning institutions everywhere, and we don’t know where those limits are. So, we stick to the institutions we know. We expect that will keep us busy enough.

 

We often use stories about universities as examples to carry the discussion. Universities like Midsize U, Research U, Small Undergrad U, and Top X U. None of these are our institution, or any other specific institution. They are aggregates of all the different experiences we’ve heard through our readings and our conversations with other people. They simply try to capture typical institutional characteristics that help carry the story we are telling. If we’ve done it well, we hope you’ll see things you recognize from your own experiences.


References

Weaver, W. 1948. Science and complexity. American Scientist, 36(4):536-544.