Models and theories that support interactive professionalism

Theories of action

In 1974, Argyris and Schön published Theory in Practice: Increasing Professional Effectiveness, the first of a series of books that were to become deeply influential through the insights they provided into individual and organisational learning. In this first book, they argue that people’s behaviour is guided by and can be explained by their “theories of action”. They theorise that people can learn better by making explicit, understanding, and critically evaluating the components of their theories of action in relationship to a particular problem of practice. This idea underpins many of the communication and relationship practices advocated for professional learning today.

Argyris and Schön (1974) describe two types of theories of action. An individual’s theories of action consist of their “espoused theories” – what they believe they would do in a certain situation – and their “theories-in-use” – what they actually do. This is an important understanding: people’s actions are often governed by theories-in-use of which they are unaware and that differ from the values and beliefs to which they aspire.

Theories of action that are derived from people’s descriptions of how they act, or have acted in the past, and from the explanations they give for such actions are called espoused theories. Theories of action that are derived from firsthand observations are called theories-in-use. Because people are not always aware of what causes their actions, the theories that people claim to be using and the theories that are actually determining their behavior may not be the same.

Robinson and Lai, 2006, page 26

There are three elements to a theory of action:

• Governing variables: Those variables that people try to keep within an acceptable range. They include the values, assumptions, theories, beliefs, concepts, rules, attitudes, routines, policies, practices, norms, or skills that underlie people’s actions. Any action is likely to impact upon a number of such variables, and so any situation can trigger a trade-off among governing variables as those involved try to keep within their personal boundaries.
• Action strategies: The actions people take to keep their governing variables within the acceptable range.
• Consequences : What happens as a result of an action. These can be both intended (often expressed as goals or objectives) and unintended.

The following example illustrates how this works:

A person may have a governing variable of suppressing conflict, and one of being competent. In any given situation she will design action strategies to keep both these governing variables within acceptable limits. For instance, in a conflict situation she might avoid the discussion of the conflict situation and say as little as possible. This avoidance may (she hopes) suppress the conflict, yet allow her to appear competent because she at least hasn’t said anything wrong. This strategy will have various consequences both for her and the others involved. An intended consequence might be that the other parties will eventually give up the discussion, thereby successfully suppressing the conflict. As she has said little, she may feel she has not left herself open to being seen as incompetent. An unintended consequence might be that she thinks the situation has been left unresolved and therefore likely to recur, and feels dissatisfied.

Anderson, 1994

Argyris and Schön (1974) perceive learning as the formation or modification of a theory-in-use. That is, learning involves the resolution of dilemmas that result from a conflict between some elements of a theory-in-use: governing variables, action strategies, or consequences. The basic dilemma is between a person’s desire to be effective and their desire to keep their theory-in-use and the behavioural world they have created constant. In the example above, the learner has kept her behavioural world constant by maintaining her sense of competence and avoiding conflict but may be left with the unintended consequence that the situation is fundamentally unresolved.

Argyris and Schön (1974) distinguish between two kinds of learning:

• single-loop learning, which requires the learner to reflect on his or her action strategies and adopt new strategies that will be more effective in achieving their governing variables
• double-loop learning, which requires the learner to change his or her governing variables through deeper reflection on the assumptions that underpin them.

Argyris and Schön (1978) develop the metaphor of a thermostat to compare the two processes.

When the error detected and corrected permits the organization to carry on its present policies or achieve its present objectives, then that error-and-correction process is single-loop learning. Single-loop learning is like a thermostat that learns when it is too hot or too cold and turns the heat on or off. The thermostat can perform this task because it can receive information (the temperature of the room) and take corrective action. Double-loop learning occurs when the error is detected and corrected in ways that involve the modification of an organization’s underlying norms, policies and objectives.

pages 2-3

In double-loop learning, the people in the room might decide to question whether they have set the thermostat to the right temperature or even whether they have chosen the right source of heat! Referring again to the example above, double-loop learning might occur if the learner questioned the value of suppressing conflict or the need to always appear competent.

Double-loop learning does not supersede single-loop learning. Single-loop learning enables us to avoid continuing investment in the highly predictable activities that make up the bulk of our lives; but the theory-builder becomes a prisoner of his programs if he allows them to continue unexamined indefinitely. Double-loop learning changes the governing variables (the “settings”) of one’s programs and causes ripples of change to fan out over one’s whole system of theories-in-use.

Argyris and Schön, 1974, page 19

This process can be represented as follows:

Figure 4: Single- and double-loop learning

Figure 4 text version

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