Taking a Walk In Quinn's Mind

How do we design learning that prepares learners for real-world performance by aligning practice, automatic responses, and assessments with the decisions and actions they’ll need to make on the job?.

How the learning loop moves from perceiving information in the environment through attention, working memory, and long-term memory to observable action.

How meaningful feedback refines declarative knowledge, develops learners’ evaluative judgment, and enables self-correcting practice without continued dependence on external guidance. It also explores why automation alone doesn’t guarantee expertise.

How feedback refines the learner’s declarative knowledge until they can evaluate their own performance and self-correct without depending on an external expert. It explores how instructional design can gradually transfer evaluative judgment from the teacher to the learner.

How declarative knowledge provides the standard for feedback, helping learners identify gaps between their actual and desired performance. It explores how instructional design must connect practice with feedback to develop correct, reliable procedural skills.

How episodic experiences become prior knowledge that can shape expectations and why varied practice and multiple scenarios are necessary to prevent learners from overgeneralising an experience.

The relationship between knowing and doing specifically, how declarative knowledge can scaffold early performance, while deliberate practice and feedback are what develop procedural skill and eventual automation.

The difference between knowing something and being able to do something, while exploring how practice develops procedural skills.

How our existing concepts, experiences, and event patterns shape what we understand and remember and how they can also mislead us through Overgeneralisation in learning design,

An introduction to the difference between declarative (“I know”) and procedural (“I can”) knowledge,

The gap between having knowledge stored in long-term memory and being able to retrieve and use it in real performance. The core question is: Are we designing learning to store or make knowledge usable

Why the format of an assessment changes the kind of retrieval learners practise. The central question is: Are we asking learners to recognise an answer, or generate it from memory?, Does it match ?.

The relationship between storing knowledge and being able to retrieve and apply it when needed. The tension between engaging learning and accessible learning.

How new information becomes connected to existing knowledge instead of remaining an isolated fact. It explores elaboration as a “dot connection” process where prior knowledge becomes the foundation...

What chunking actually means beyond simply grouping information together. It explores how sensemaking, meaningful relationships, and learners’ prior knowledge can transform separate pieces of info...

How attention moves information from the sensory store into working memory, and why working memory’s limited capacity matters for learning experience design.

The difference between removing distractions and actively directing attention. It explores how integrated labels, attention-guiding pointers, and sequencing can reduce unnecessary searching.

When to introduce the noise, stress, and complexity of real-world performance. It explores a progression: simplify → master → gradually replicate the performance environment.

This works the tension between volitional and non-volitional attention: learners can deliberately focus, but salient cues can still pull their attention away.

The difference between automatic sensory registration and the time-dependent nature of what enters through each sense. It explores why sight can provide a rapid snapshot while audio...

The distinction between sensory gates (where information enters) and channels (how different types of information are represented and processed).

Why perceived information can disappear from the sensory store so quickly, and how attentional guidance helps learners select what matters before it fades.

Introducing the sensory store as a high-capacity but extremely temporary inbox for incoming sensory information. It also explores why vision and audition receive particular attention.

How redundant cues can make visual information accessible when colour perception is limited. The core idea is that adding text, symbols, shapes, patterns, or other cues preserves the meaning ...

How redundant pathways can prevent a sensory limitation from becoming a learning barrier. It focuses on carrying the same meaning through captions, transcripts, or visual cues when...

The progression from “Can the learner perceive the information?” to “What if that sensory pathway isn’t accessible to them?” It turns Quinn Seeds 1 and 2 into a simple design lens...

The idea that perceivable information is not necessarily accessible information. It asks how instructional designers can create multiple pathways to the same meaning...

The idea that accessibility is more than making information perceivable; it is about providing another path when a learner cannot use a particular sensory pathway.

The difference between making learning feel immersive and reproducing the sensory information that competent performance actually requires.

How to move from sensory immersion to sensory fidelity using the sensory channels that competent performance actually requires rather than adding senses simply to make learning feel realistic.

How sensation and action form a continuous feedback loop between the learner and their environment. It’s refining the S.A.A.S. mental model from simply explaining information flow to...

When a sensory channel is actually worth designing around moving from “Can I use this sense?” to “Does this sense reliably serve the learning objective?”.

How audio can move beyond narration and decoration to deliberately train auditory skills especially in high-stakes environments where learners must detect, filter, and respond to competing sounds.

How can sound can move beyond narration and alerts to become part of realistic learning experiences especially by simulating the sounds learners may need to recognize in high-stakes environments.

This note is working out how the way our visual system detects motion, contrast, colour, and detail should shape the way instructional designers use visuals and animation.

This short note is working out why vision receives so much of the brain’s processing capacity, and what that means for instructional designers when deciding what learners see and process.

This short note is working out why detectability comes before perception, processing, memory, and application and why that makes it a foundational consideration when designing learning experiences.

discussing the tension between moving slowly enough to truly understand what you learn and moving quickly enough to feel like you’re making progress and why documenting, applying, reflecting...

How sensory input, attention, action, and the environment form a continuous learning loop and how that loop can be understood as a simple mental model: Stimulus → Attention → Action → Stimulus.

How sensory input, attention, action, and the environment form a continuous learning loop and how that loop can be understood as a simple mental model: Stimulus → Attention → Action → Stimulus.

How different senses capture information in different sensory stores, and why what we see, hear, smell, feel, or taste initially remains represented in the same form in which we perceived

How information from the outside world enters the learning system through our senses, and why understanding sensory processing matters...

Transform a complex neuroscience idea into something familiar enough to understand, remember, and explain using an office analogy make the concept accessible to other instructional designers.

Working out how to turn an abstract explanation of neural connections into a familiar mental model using an office analogy.

Working out whether we’ve been thinking about the performance–well-being relationship backwards: does performance create well-being, or does well-being create the conditions for better performance?

Today i learnt about the connection between happiness, psychological needs, and performance, and whether our usual way of thinking about performance is missing something important.

How instructional designers can establish the value of their expertise alongside SMEs by recognizing that expertise in content and expertise in how people learn are different.

Here i put down my understanding of the neural infrastructure underneath learning, focusing on the cognitive processes designers can actually design for

If you're curious about how information becomes lasting knowledge and what that means for an instructional designer’s job beyond simply presenting information.

Hop on this one with me to know whether “learning by doing” can become an excuse for inadequate formal preparation, especially when mistakes carry real costs.

Join me as i explore how evidence should guide instructional design decisions instead of hype, and what kinds of game-based activities might actually produce meaningful transfer...

I’m working out how to actively learn from Quinn’s book. Not just read it, by reframing, reflecting, translating ideas into design decisions, and documenting how my thinking changes along the way.

Understanding how an Instructional Designer can stay current with learning science without becoming a researcher.

This note is working out how learning science—especially cognitive load theory can improve the design of learning experiences, using integrated diagram labels as a practical example.

This note is working out whether I can responsibly keep using old instructional-design foundations and evidence when the science behind learning keeps evolving.

I could do it. But I couldn’t explain why it worked.

I’m working out how to move from “it worked before” to “I can explain why I designed it this way.”

How my journey all started on linkedin on the 20th of July 2026 around 01:15:35 AM