Learn Like a Human, Not a Computer
Designing learning that works with biology, not against it.
The Problem
Traditional models of learning, in schools and workplaces, treat brains as information processors. Deliver clear content, manage cognitive load, test retention.
But this computational model misunderstands how learning actually happens.
The brain isn't a computer. It's a biological prediction machine optimising for survival and wellbeing. What we learn and remember is what we care about—not what we're told to learn.
The Three Tiers of Learning
Most learning systems optimise for one of three levels:
Compliance (important, but rarely leads to learning)
Forced engagement with prescribed content.
Complete the module. Pass the test. Check the box.
Result: Brittle learning that fades quickly.
Performance Support (learning happens slowly if at all)
Just-in-time guidance that solves immediate problems.
Job aids. Quick reference. AI assistants.
Result: Efficient task completion with limited memory consolidation.
Development
Affectively engaged transformation that integrates into identity.
Building adaptive capacity. Transferable understanding.
Result: Lasting growth that enables novel applications.
Compliance meets a need for safety, standards, regulation. Performance support meets a need for efficiency. Development creates adaptiveness and resilience needed for thriving organisations and society.
Brains Are Prediction Machines
The brain does not archive information like a computer hard drive. It is a biological organ with a prime directive: survival via homeostasis.
What does this mean?
Learning is not information transfer. Learning is the process by which the brain updates its predictions about what matters for wellbeing.We remember what we care about.We care about what predicts our survival, social belonging, and identity.
The Affective Architecture of Cognition
Memory is Reconstructive, Not Reproductive
Conventional models view memory as a "recording device." Biological reality is that we don't retrieve files; we reconstruct experiences based on what mattered to us when they happened.
What gets remembered?
The brain is incredibly selective. It filters out most of daily life to save energy, consolidating only what the salience network tags as relevant to our wellbeing—what predicts survival, social belonging, and identity.
This "unreliability" is actually a feature, not a bug. The brain doesn't waste resources archiving irrelevant information. Instead, it builds an ever-evolving predictive model of what matters. We decide what matters based on two axes: arousal (low - high) and valence (negative - positive).
The Circumplex Model of Affect
OPTIMAL LEARNING = ENGAGED (High arousal + positive valence)
(Unpleasant)POSITIVE
(Pleasant)
AROUSALLOW
AROUSAL
Attention Is Not Enough
Attention for true learning operates like a seesaw across three brain networks. The pivot is Salience (what matters), which leads the toggling between Executive Control (focused work) and Default Mode (reflection, meaning-making). The key is balance.
The Network Dynamics
Salience Network (SN)
The pivot. Detects what matters emotionally and biologically. Triggers the switch between networks.
Low salience leads to weak learning, quickly forgotten.
Executive Control (ECN)
The "Task Positive" mode. Focused attention, problem solving, and analytical processing.
Excessive focus can lead to anxiety, burnout, inhibits meaning-making, sense of purpose and identity.
Default Mode (DMN)
The "Reflective" mode. Meaning making, identity formation, and connecting new info to the self.
Excessive reflection can lead to rumination, inaction, even depression.
"What you have emotion about is what you're thinking about, and what you're thinking about you might be able to learn about."
Narrative & Identity
Human beings are narrative creatures. We don't experience life as disconnected data; we organise it into stories.
Narratives enable the Default Mode Network to simulate possibilities and consolidate learning during rest. This is how information becomes part of our identity.
- Stories provide structural coherence for memory.
- Social narratives shape who we believe we can become.Without narrative, learning feels like disconnected facts. With narrative, learning becomes part of who we are.
Universal Design Principles
How do we translate biology into practice? These six principles apply across classrooms, organisations, and leadership development.
Start With What People Care About
We only learn what matters to us. Connect content to existing cares.
Begin learning design by exploring why anyone might care about this content.
Positive Interoception
Stress blocks consolidation. Safety enables learning.
Reduce unnecessary threat. Foster belonging and physiological regulation.
Moderate Arousal
Too boring = ignored. Too scary = survival mode.
Create resources which meet existing cares or experiences which trigger genuine curiosity or create eustress: meaningful challenge with support.
Toggle The Seesaw
Alternate between focus and reflection.
Build explicit reflection periods into every learning sequence.
Embed in Narrative
Stories provide the structure for memory and identity.
Ask: What story provides context for this learning? Who are the characters?
Foster Autonomy
Agency deepens engagement. Compliance is brittle.
Provide meaningful choices and respect learners' own goals.
The biological mechanism
We learn to regulate our body's energy budget (allostasis). When new information helps us predict what's coming and how to respond, the brain invests in consolidating it. When information doesn't help us predict or regulate, the brain efficiently discards it.
In other words: We only learn what's worth the metabolic investment.
Want to go deeper?
Access the foundational white paper for a deep dive into the 3 pillars, the learning seesaw mechanics, and detailed applications of the universal design principles.
White PaperApplications Across Contexts
Education
Nurture environments of safety. Develop curriculum and teaching which supports tipping the seesaw back and forth - connecting daily experiences to emerging values and identity. Create assessment which honours agency, purpose and capability.
Workplace L&D
Embed learning in realistic scenarios. Address authentic performance challenges rather than abstract compliance. Leverage social learning communities.
Leadership
Leaders must make sense of complexity and strategy through affective architecture - how emotions shape actions, how proposed change activates engagement or threat, how to use the seesaw to make better decisions, how narratives create cohesion, how purpose shapes identity.
AI-Human Collaboration
AI lacks affect and cannot "care." Understanding this biological distinction helps us allocate tasks appropriately: use AI for information processing while preserving human judgement, meaning-making, and ethical decision-making across education, workplace, and family contexts.
For Families
Parents face unprecedented challenges navigating AI during their children's most critical years of brain development. Like all technology, AI can be harmful or helpful. When we understand human development, especially during adolescence, we can use AI safely and effectively while embracing the benefits.
For Workplaces
Organisations implementing AI in workplace learning face a critical distinction: performance optimisation versus developmental learning. I focus on biological realities - what remains distinctively human, what AI cannot do, and how to implement AI in ways that enhance rather than undermine genuine capability building and adaptive capacity.
Building Learning Systems
That Work With Biology
Connecting affective neuroscience to classroom practice, workplace strategy, and leadership development.
Mike Goves
After 20 years in teaching and school leadership, I kept witnessing the gap between how we're told learning works and what actually happens, regardless of attainment and performance. It turns out the same problems persist in business. That gap led me to better understand human development.
With a Master's in Cognitive Science, as a graduate of the Oxford AI Programme, and 5Di accreditation, I bridge research and practice, informed by pioneering researchers such as USC's CANDLE lab in the US, to reveal how learning in schools and workplaces can align with human development.
I'm driven by a core belief: people deserve genuine, meaningful opportunities to develop and flourish. Adolescence is a particularly sensitive period where experiences literally build the brain networks that shape lifelong wellbeing and learning capacity.
I serve as a national judge for the Teaching Awards, sit on steering groups centred on equitable and holistic education, and was awarded Top Overseas Teacher by Singapore's Ministry of Education.
My Mission
To champion learning environments which are based in human development and flourishing, challenging computational models of learning that treat the brain as a data processor and learning as information transfer. To establish affective Foundations framework as the foundational science for learning and development.
The Affective Foundations framework is built upon the converging evidence from affective neuroscience, developmental psychology, and biological systems theory.
Translating Biology to Practice
Four domains drive application of theory through research, workshops and resources.
Affective Education
From information transmission to developmental identity
Move beyond transmitting content to students by prioritising development as the purpose of education.
Design Features
- Environments of safety and non-violent communication
- Planning and teaching using the seesaw model
- Strategies for building salience and relevance
- Assessment approaches that honour agency and identity
Affective Workplace L&D
From Content Delivery to Performance
Move beyond completion metrics to performance change. Design workplace learning that respects the brain's homeostatic drive while enabling deep skill acquisition.
Design Features
- Performance-based design
- Social learning systems
- Just-in-time support
- Culture of psychological safety
Affective Leadership
Creating Conditions for Collective Learning
Leaders navigate complexity through affective foundations - understanding how emotions shape action, how change is personal, and how to make better decisions under uncertainty.
Design Features
- Using the seesaw model for strategic decision-making
- Emotional intelligence in systems change
- Managing resistance through affective understanding
- Using narrative to create organisational cohesion
Affective AI-Human Collaboration
Understanding the Human Advantage
AI lacks affect and cannot 'care.' Learn to leverage AI for information processing while preserving human judgement, meaning-making, and ethical decision-making across education, family, and workplace contexts.
Design Features
- Clear comparison between human and AI cognition
- Framework for task allocation (what AI should and shouldn't do)
- Safe and ethical AI integration strategies
- Developmentally appropriate AI use in education
- Practical tools for immediate implementation
Research Partnerships
Help Shape These Workshops
I'm seeking education partners to co-develop and pilot affective learning frameworks and workshops. If your school is interested in exploring developmental thinking and collaborative implementation research, let's work together.
- Diagnostic assessment of current developmental practices
- Co-design of affective-first interventions
- Implementation support and iteration
- Shared learning and documentation of impact
Ideal partners: Schools committed to transformative education, willing to experiment thoughtfully.
Work With Me
Ready to support schools and businesses implementing affective approaches to learning and development.
Consultation & Advisory
I work with schools and organisations on:
- Affective-first pedagogy and classroom practice
- Leadership coaching using triple network frameworks
- AI implementation that honours human development
- Assessment and curriculum design
Get in touch to explore what we can do together. It depends on your culture and aims—or maybe you just want to discuss opportunities.
Speaking Engagements
Keynotes and workshops for conferences, schools, and organisations on:
- Affective neuroscience in practice and the seesaw model
- Why computational models fail adolescent development
- Triple network leadership and decision-making under uncertainty
- AI-human collaboration: What remains distinctively biological
Start with the Foundation
Let's Work Together
Partner to build biologically grounded learning systems.
Speaking Engagements
Keynotes and workshops on:
- Affective neuroscience in practice and the seesaw model [education focused]
- How to improve performance but why sustaining development is better [business focused]
- Affective leadership and leading change [all organisations]
- AI-human collaboration [all organisations]
Education Research Partnerships
Collaborative research on:
- Education during adolescent development (10-24 yrs)
- Curriculum design connecting to student concerns
- Authentic assessment
- Affective-first pedagogy implementation
- Learning environment design for network coordination
Consulting
- Development-focused teaching and learning
- Assessment innovation
- Human-centred learning design
- Human vs AI cognition and capabilities
- Task allocation frameworks
- Developmentally appropriate AI use
- Safe and ethical use