The Transformations Club Second Meeting

Meeting Overview

For anyone Interested in the Club

Lonny introduced the guide2expertise Matrix using the travel domain. It provides an unprecedented organization of any domain of expertise, identifying the steps of transformative learning (TL) between phases of any goal within any domain. We organize our notes by phase of connection with the club (see Beginning). Several members introduced dilemmas (the first step of TL) and told how they resolved them without thinking explicitly about the steps of TL (see Exploring). That raised the question of what value knowing the steps might have. Discussion of another member’s dilemma showed how explicitly knowing the steps could stimulate the discovery of new approaches. We affirmed that explicit knowing was not necessary but could help. This “Yes...and” approach is well known to improvisational actors (see Sustaining). A recently published analysis of governmental discussions of sustainable development showed how deliberately using a model of learning could help to prevent stalled learning (see Mastering). An innovation used AI to show how the rich variety of types of learning applies to the steps of transformative learning. This demonstrated how labeling a practice that someone is learning is a sustainable solution to the problems of exploring how to label a person’s “learning style” (see Inspiring)

Beginning

Contents of this webpage

During our founding meeting our notes were organized according to reader interest. The same will be true for this week. Note that the language and issues are more complex for the more advanced audiences. Readers can use ctrl-click on an underlined term to jump to a section.

Phases of connection with the club:

Beginning: attended at least one meeting.

Exploring: intending to come to the next meeting.

Sustaining: feel committed to keeping the Club going.

Mastering: want to make or respond to a contribution on a particular topic.

Inspiring: have a discovery or an idea for improving the club, site, and their domain of expertise

Exploring

Dilemma Stories

At the Founding Meeting (see guide2expertise.org/tc1), I used my dilemma about getting mad at my computer to describe the steps of transformative learning, which actually worked. Beginning 70 years ago, for the next 25 years, I touched typed on a mechanical typewriter with 44 keys. I’m now, for the first time, deliberately learning to suppress my 44-key habits in order to be a better typist on keyboards with over 100 keys. Deliberate transformative learning revealed the root of my frustration and led to a sustainable solution.

At this meeting, Mike told a story about a dilemma that he solved without thinking about the steps of transformative learning. It involved a particularly difficult piano accompaniment for a choir he performed with. Instead of sticking to the sheet music, he rewrote the accompaniment especially to remove note repetitions that are easy to accomplish by singers using different syllables, but very hard to repeat using the same keys. He found the re-write very satisfying. Duke added that such modifications are common and that he had used them even when performing classical pieces with a symphony. Judy added a description of creating a complex new knitting pattern that similarly was accomplished without thinking about the transformative learning steps. Clearly, transformative learning happens without people deliberately thinking about the steps of transformative learning.

Sustaining

“Yes…and,” the improv actors’ approach of affirming and adding to a story.

This second meeting demonstrated the power of the well-known, improvisational drama “Yes…and“ approach, documented in Keith Sawyer’s book, Group Genius. Respond to a co-actor’s offering with affirmation plus something new. If there’s only affirmation, only something new, only silence, or only opposition, the moment fails. In short, the only way for a collaborative, improvisational moment to succeed, is to affirm and add to a previous contributor’s offering. The story below shows how “Yes…and” characterized this second meeting remarkably well.

The dilemma stories brought up the question of whether to use intuitive or transformative learning concepts to solve such dilemmas. I don’t remember our coming to a conclusion about this question, but here, it is worthwhile noting that all three stories mentioned the DEEP steps of transformative learning. They discerned a Dilemma, Examined it to find a solution, Enabled themselves to implement the solution, and Performed it. The steps were used whether deliberately (like David) or intuitively (like the other members).

I noted that the solution we came up with to my computer anger worked well. I’m much more ready to re-place my fingers when I see gibberish on the screen and to get up and leave when something interrupts my current project. I haven’t sworn once (previously several times per session), but I did use an exclamation once.

Duke followed up with his dilemma about getting mad at himself when he hits a ball into the net when playing tennis. That discussion gave new insights into the question of using the DEEP steps or just solving problems intuitively. Like me, he had not been able to solve the dilemma for years, though he had tried several approaches.

Sandy added to the discussion by introducing a new dilemma that she had solved decades earlier for herself and for those she taught. When learning a second language, we often fail to segment the sounds meaningfully. She helped new learners listen better by having them separate a phrase that always sounded like gibberish to them in a new place. Just breaking the words differently could produce a new insight into their meaning.

Based on Sandy’s concept, I suggested that Duke try to learn a meaningless gesture in response to hitting a ball into the net. He liked our suggestion. The steps below work for the transformation of any mode of practice for any goal to the next phase for that goal. The lettered concepts in the two E steps (numbered 2 and 3) are components of Transformative Learning described by Mezirow in his foundational book, Transformative dimensions of adult learning. A study of 500 counseling sessions found that the four steps occurred at different times over the course of therapy but the lettered components appeared in the same sessions.

Transformative Learning DEEP Steps and Components:

1.    Discern a dilemma

2.    Examine it:

a.     Reflect,

b.     Identify one’s own role in creating it,

c.      Discuss it with a friend, and

d.     Identify the next mode of practice to resolve it

3.    Enable performance:

a.     Plan when to rehearse,

b.     Rehearse,

c.      Get feedback from someone with experience in the new mode

4.     Perform: enact the new mode of practice in public.

Mastering

Intuition vs. DEEP steps and a “Yes…and” approach to errors.

Yesterday morning I finally found an answer to the question of using intuition vs. DEEP steps. The answer came from an article in Science magazine (my breakfast reading) called “A theory of change approach to enhance the post-2030 sustainable development agenda.” People may think that historical change has little to do with individual change, but my students and I showed in a 1999 publication that the mathematical succession model (described at https://www.guide2expertise.org/inspire) applies without any modification in the formula in both cases. Historical development obeys the same law as individual development.

The solution in the Science article was a model that detailed transformative learning in the international deliberations that included the current phase, all four DEEP steps with all their components, and the master and inspiring phases that would follow. They argued that if you have a clearly articulated theory of change, it is easier to spot potential failures and bottlenecks. If you just act intuitively, you are more likely to miss those chances. That conclusion applies to the value of knowing the DEEP steps as well as it does to the international deliberations.

Putting this conclusion together with the “Yes…and” approach presents us with yet another new dilemma. We identify many dilemmas through the errors we make, but pointing out errors discourages discussion. So, I asked AI this morning, how can we reconcile identifying an error with improvisational drama’s “Yes…and” approach. Is there a “No…and” approach that just requires a lot more time to process than is available on the stage? But that would contradict the notion that development is very similar across scales from conversation, to individual experience, to history.

CoPilot responded that improvisational drama has workable answers to how to respond to an error in a “Yes…and” way. It gave three techniques that with practice each of us could identify not only in our favorite TV shows, but also in much fiction writing.

The following techniques for responding to errors with a “Yes…and” approach emphasized treating the error as a gift to the scene. The examples posit that someone has just called you “left brained.”

1.     Incorporate it as a surprising contribution: The ex of one of my twin daughters believed that since their hair swirled in opposite directions, their brains must do so as well. So, to see if they were both ready to go out to do an errand he would ask, “Do we have the whole brain yet?” Of course, now that they are living 650 miles apart, they are each forced to use their whole brain all the time.

2.     Accept it as a new reality: “Darn. That hemispherectomy must have left me with no memory of the operation.” And then wave your left arm erratically as you might if you had lost your right brain control of that arm.

3.     Justify the error: “Aha! I make a lot of jokes to my wife every day. Now, I know why she laughs at me.”

And such answers even create a new dilemma. When watching TV or live drama, should we relax and let the laugh come out or pay attention to the technique that evoked it? In words framed within our discussion above, is it more fun to respond to dilemmas intuitively and bear the increased likelihood of bottlenecks and stalls, or should we go ahead and learn to identify the techniques?

In studying for the next section, CoPilot reminded me that practices acquired by high level learning approaches become “pushed down” (presumably to less complex and more primitive processes), or as neurologists say, “automated.” Intuition as CoPilot defined it below, simply involves high level practices that have been pushed down. Rehearsal of new learning results in automated learning. Automated learning is relaxing. If we use the improv pro’s ideas often enough, we will automate them enough to relax at the same time.

Inspiring

When we use 20 types of learning to push down through 5 levels of the brain.

Knowing that there are twenty types of learning embedded in at least five different levels of complexity in our brains helps people get past the tendency to label others and replace it with thinking about the complexity of what we ask or expect of each other. Transformative learning is the most complex form that has been identified because it includes all the others at various times depending on the phases, goals, and domains involved.

The following list was generated by my AI sources: CoPilot for the list, and the ordering was the same for it, Gemini, and ChatGPT. Explanations from CoPilot are in regular type and answers to follow-up evolutionary questions were posed to all three AI systems. Hypotheses about the use of each of the five levels of learning are in italics.

1. Associative (Automatic)

These processes require the least "top-down" metabolic energy. These structures are present in the brains of reptiles and birds, but the various types of associative learning have been demonstrated in invertebrates.

Discerning a dilemma for any phase results from a problem with automatic learning of the phase. The rehearsal process of enabling involves making new practices automatic.

  1. Classical Conditioning: Simple stimulus-response remapping.

  2. Implicit Learning: Unconscious pattern acquisition (the "how" without the "why").

  3. Statistical / Probabilistic Learning: The brain’s background tallying of environmental frequency.

  4. Intuition (Automated Learning): Once-complex skills that have been "shoveled" down into the basal ganglia for rapid, effortless execution.

  1. Operant Conditioning: Requires voluntary action and the evaluation of consequences (dopamine/striatum).

2. Social learning

AI sorted social learning with the operant and situated learning, but no species has been shown to imitate that is more primitive than fish.

Examining involves discussing a dilemma with a friend and enabling involves getting feedback from someone familiar with a desired new mode of practice.

  1. Observational / Social Learning: Requires the brain to translate visual input into potential personal action.

  2. Imitation / Memetic Learning: More specific than observation; requires high-fidelity mirror neuron activity to replicate a "unit" of culture or movement.

  3. Situated Learning: Learning tied to physical context; requires the hippocampus to index knowledge to a specific environment. This term comes from the “community of practice” literature of cultural psychology and the three AI systems placed it inappropriately as associative learning. It is the social learning that is restricted to the sustaining and higher phases and only found in dolphins and humans.

3. Constructive (Relational)

Here, the brain begins to organize information into abstract mental structures. The Prefrontal Cortex (PFC) starts taking the lead in organizing the data provided by the hippocampus and sensory cortices.

Constructive learning is the primary type of learning for enabling the exploratory phase of any goal.

  1. Cognitive Learning: General mental acquisition and categorization of facts.

  2. Schema-Based Learning: Fitting new data into existing mental "folders" (medial PFC/Hippocampus integration).

  3. Exploratory Learning: Proactive hypothesis testing; uses the brain's "seeking" system to drive motor and cognitive engagement.

  4. Constructivist Learning: The brain actively "builds" meaning by synthesizing new stimuli with old memories.

4. Strategic (Systemic)

This level requires "High-Level Synthesis"—the ability to see connections across different domains and manage complex, non-linear variables. Strategic learning makes possible the examining step of transformative learning.

To solve a dilemma with a current practice we identify a new phase using strategic learning. We enable practices that we use to sustain, master, or inspire goals using strategic learning.

  1. Inquiry-Based Learning: Driven by questioning; requires high-level executive function to filter and pursue relevant data.

  2. Connectivist Learning: Navigating and maintaining a network of external information nodes (people, databases, AI).

  3. Insight Learning: The "Aha!" moment. Requires the brain to suddenly restructure a problem; involves a specific burst of high-frequency (gamma) activity in the right temporal lobe.

  4. Creative / Generative Learning: The most complex "output" learning; requires the Default Mode Network (imagination) to collaborate with the Executive Control Network (structure).

5. Higher Order (Recursive)

This is the peak of neural complexity. It is "Learning about Learning." It requires the brain to turn its focus inward and modify its own operating system.

Reflective learning is an essential part of examining a dilemma, metacognitive and deliberate practice are essential to enabling.

  1. Reflective Learning: Intentional analysis of past experiences; uses the "Self-Referential" circuits of the brain.

  2. Metacognitive Learning: Monitoring and regulating one’s own cognitive performance. This involves the Frontopolar Cortex, the most recently evolved part of the human brain.

  3. Deliberate Practice: The most metabolically "expensive" form of learning. It requires total prefrontal cortex focus to suppress habits and physically thicken the myelin (insulation) on specific neural pathways.

  4. Transformational Learning: The ultimate complexity. It involves "unlearning" deeply held neural schemas and rebuilding an entirely new worldview, effectively "rewiring" the brain’s foundational logic.

This analysis shows that every learner uses multiple levels of learning and often uses multiple levels simultaneously during the performance of the same mode of practice. Learning to label practices and the learning types required to perform them is a sustainable solution to the problems created when we explore ways of labeling people. It also gives a deeper meaning to the idea of learning being “pushed down” as it becomes automated. We enable transformative learning by using strategic learning and we examine it using constructive and social learning. Ultimately, we recognize our dilemmas through associative learning.