Learning About Learning (LAL)

Working with learning as a practice

Learning About Learning (LAL) partners with organisations, networks, and initiatives that are already trying to learn — yet want to understand how learning itself is working.

Rather than arriving with new frameworks or methods, LAL accompanies people as they examine learning as a living practice: how it is initiated, shaped, constrained, taken up, resisted, or lost over time.

LAL draws on LUCA, but its emphasis is on helping participants inquire into learning in real time — asking why it is unfolding the way it is, what forces are organising it, and what becomes possible when those dynamics are surfaced.

It starts from a simple premise: learning only improves when we understand what it is, what shapes it, and what that suggests we do differently.

First- and second-order learning

In this work, a simple distinction is sometimes useful.

First-order learning refers to learning about programmes, contexts, or practice — what is happening, what is changing, what might work differently.

Second-order learning refers to learning about how that learning is being organised — how expectations are formed, how evidence is interpreted, how decisions are shaped, and how learning accumulates or breaks down over time.

Learning About Learning focuses primarily on this second-order dimension, not as an alternative to substantive learning, but as a way of strengthening the conditions under which first-order learning can matter.

The distinction is pragmatic rather than theoretical. Both forms are ongoing and interdependent.

What LAL works on

LAL does not start from the question “What should we learn?”

It starts from questions like:

  • How is learning currently taking place?
  • Where does it feel fragile, stuck, or rushed?
  • What pressures are shaping what can be learned?
  • What gets stabilised too quickly — and what never stabilises at all?

In practice, this means working with:

  • learning cycles that stall or close prematurely
  • learning pathways that constrain future options
  • learning landscapes that shape what is possible before inquiry begins

Often, the most useful shift is not better answers, but greater awareness of how learning itself is being organised.

How LAL works in practice

LAL work is always situated. There is no standard sequence.

That said, it often involves combinations of the following.

Surfacing how learning is currently happening

This may involve:

  • reflective conversations
  • timeline or pathway work
  • tracing how key decisions were reached
  • examining how evidence travelled — or didn’t

The aim is not diagnosis or evaluation, but legibility:
making learning processes visible enough to be questioned.

Working with live learning situations

Rather than extracting lessons from the past, LAL often works with:

  • ongoing programmes
  • unfolding decisions
  • active tensions

This can include:

  • sitting inside meetings or workshops
  • slowing down moments of decision pressure
  • helping groups notice when learning is being forced into closure

Learning is treated as something to be worked with, not captured.

Experimenting with learning practices

Where useful, LAL supports small, reversible adjustments, such as:

  • changing how questions are framed
  • altering the timing of reflection
  • holding multiple interpretations open longer
  • creating space for provisional claims

These are not “best practices”.
They are context-sensitive experiments in learning under ambiguity.

Attending to power and politics of knowledge

LAL explicitly attends to:

  • whose evidence carries weight
  • whose uncertainty is tolerated
  • where learning becomes politically sensitive
  • how accountability pressures shape what can be said

This is not treated as an external constraint, but as part of the learning system itself.

Ignoring these dynamics often explains why learning fails to travel.

What LAL deliberately avoids

LAL is not designed to:

  • optimise learning outputs
  • standardise learning processes
  • accelerate convergence
  • produce definitive conclusions

In many contexts, the most valuable contribution is restraint:

  • slowing learning down rather than speeding it up
  • keeping questions open longer
  • resisting premature coherence

This is not a refusal to act.
It is an effort to act without foreclosing learning too early.

How LUCA supports LAL

LUCA provides a shared orientation for LAL work:

  • Landscape helps identify which conditions are shaping learning now
  • Cycles help notice where learning is stalling, breaking, or closing
  • Pathways help understand how learning accumulates and constrains the future

These ideas are used as thinking aids, not as explanations to be adopted.

Participants do not need to “learn LUCA” for LAL to work.

What LAL tends to produce

LAL does not promise clear answers or universal solutions.

What it often produces instead:

  • greater clarity about where learning is getting stuck
  • shared language for naming learning tensions
  • more deliberate choices about how and when to learn
  • increased capacity to stay with ambiguity without paralysis

Over time, this can change not just what is learned, but how learning itself is approached.

Where LAL fits

LAL sits between:

  • abstract frameworks and everyday practice
  • evaluation and action
  • learning intentions and learning realities

It is most useful where:

  • complexity is unavoidable
  • stakes are real
  • and learning cannot be fully planned in advance