# Kyle Slinn
> An exploration of evidence-informed educational psychology for health care professionals.
Public Ghost content for AI and LLM tooling. This file includes a bounded export of public pages first, then recent public posts.
Append `.md` to any post or page URL to get the content in Markdown (for example, `/example-post.md`).
## Pages
### About Me
URL: https://www.kyleslinn.ca/about-me/
Last updated: 2026-08-13T13:09:43.000Z
Hello! I'm Kyle. I'm a project manager and instructional design consultant based in Ottawa, Canada. I specialize in creating evidenced-based learning experiences for health care students and professionals.

You can view my [resume here](https://drive.proton.me/urls/E93G73QGZ0?ref=kyleslinn.ca#tDSKhbYLs9kp).

I started this website/newsletter because I became frustrated with the plethora of misinformation on educational psychology and instructional design strategies being circulated in the health care space. Health care workers are expected to provide competent, evidenced-based care to their patients, but that same high-quality bar isn't applied to health care training and professional development. 

Part of the problem is a lack of critical skepticism. Too often, ideas and practices are treated as universally valid simply because they’ve been around a long time or are widely accepted. As a result, we set health care workers up for failure and burnout, and potentially put patients at risk.

This website and newsletter is my small attempt to try and fix the industry. Connect with me on social media if you want to say 'hi' or use the contact form below if you're interested in having me do some consulting for you.

Your email: Your message: Send
### Tools
URL: https://www.kyleslinn.ca/tools/
Last updated: 2026-08-13T16:06:21.000Z
Over the years I've created a number of tools that may be beneficial to you.

- [**Learning plan generator**](https://learning-plans.kyleslinn.ca/?ref=kyleslinn.ca): A simple static website that let's you build visually appealing learning plans quickly.
## Posts
### How Memory Works
URL: https://www.kyleslinn.ca/how-memory-works/
Last updated: 2026-05-14T13:14:55.000Z
Have you ever sat through a documentary that you thought was really interesting, and then found yourself struggling to explain what you learned after the fact? Or think back to when you last started a new job. There was almost certainly a time in those first few days of orientation when you were exhausted, and just couldn't absorb any more information. Neither of those outcomes is a "you" problem. This is a well-established challenge related to how our brains remember (or don't remember!) information. The good news: If we can better understand how memory works, we can make smarter instructional design decisions that actually help information stick.

In 1968, psychologists Richard Atkinson and Richard Shiffrin proposed what is now called the multi-store model of memory (also known as the Atkinson–Shiffrin model). It describes memory not as a single location where information lives, but as a flow through three distinct stages: sensory memory, short-term memory, and long-term memory. Each form of memory has different characteristics: how much information is held, how long the information is held for, and what happens to information that's deemed irrelevant. Over the years, further research has refined the details within this model (most importantly, our understanding of short-term memory), but the core ideas hold up well and remain foundational to how we think about learning and instruction.

## Three types of memory

![](https://www.kyleslinn.ca/content/images/2026/05/1.png)

**Sensory memory** is the first memory "bucket" that manages new incoming information. Every sight, sound, taste, smell, and touch is briefly held in a separate temporary bucket for each sense. To demonstrate, as you're sitting right now, you're probably not consciously thinking about how your chair feels, or about the whirring sound of the fan beside you, or of the headlights of the car passing by outside. Your sensory memory is most likely filtering all this distracting information out. The sensory memory has a huge capacity, but can only hold on to information, and it only holds on to those little bits of information for a really short period of time. If a learner's attention doesn't focus on (i.e., attend to) a piece of information at this stage, that information is quickly discarded.

**Short-term memory** is next up. It receives what attention selects and passes on from sensory memory. This stage is a multi-component *working memory* system. Rather than a single container, working memory has three components: 

- a phonological loop that handles verbal and auditory information (note: "phonological" refers to the sounds of language)
- a visuospatial sketchpad that handles visual and spatial information, and
- a central executive that coordinates information from the other two.

This matters because it means learners aren't processing verbal and visual information through the same channel. They have some capacity to handle both types of information simultaneously, if the material is designed with that in mind, but there's going to be some information loss. We'll cover this idea in more detail in the next post.

What working memory cannot do is hold a lot of information at once. *Its capacity is severely limited*, and information held here without actively thinking about it (i.e., rehearsal) fades within seconds. Working memory can easily become overwhelmed with too much information, which we'll discuss in detail soon. Rehearsal — which includes actively thinking about information, repeating it, recalling it, or applying it to new situations — improves our ability to store and retrieve information from long-term memory. So, the longer a learner thinks about new information at the short-term memory stage, the more likely they'll remember it in the future.

**Long-term memory** stores information long term. As far as we know, it has unlimited capacity, and information can be stored indefinitely, as long as we occasionally access it. Information stored here is indexed by meaning, so it's connected to what we already know, rather than by its unique characteristics. For example, a nurse doesn't store the word 'tachycardia' based on the way it sounds. Instead, she stores it as part of a broader network of meaning: elevated heart rate, possible causes, clinical significance, and what to do about it. Atkinson and Shiffrin proposed that rehearsal is the primary mechanism for transferring information from short-term storage into long-term memory, but also noted that connecting new material to existing knowledge (via schemas) in long-term memory produces stronger encoding than repetition alone. 

## Where schemas come in

As you'll recall [from my last post](https://www.kyleslinn.ca/what-is-schema-theory/), schemas are the organized knowledge structures we store in long-term memory. A well-developed schema in long-term memory guides what sensory memory pays attention to. Schemas provide organized frameworks which increase the capacity of working memory via chunking (i.e., grouping related items into a single meaningful unit). And having that schema in place accelerates how quickly new, related information gets stored in long-term memory because there is already a label in place to easily "stick" the new information to.

To illustrate: an experienced nurse who is entering a room to help with a code blue resuscitation isn't processing each individual alarm, each medical order, and each visual cue as separate items competing for space in working memory. She has a well-developed *resuscitation schema* that chunks all the elements of that environment into recognizable patterns, freeing her working memory to focus on unusual symptoms or urgent tasks. In contrast, a novice nurse wouldn't have established that schema yet, so a lot of sensory information is given attention and competes for the same limited workspace in the working memory. The novice nurse will get overwhelmed quite quickly and might not be able to engage in higher level thinking.

This highlights why it's so important we build accurate, well-organized schemas in learners' long-term memory. It's not just a best practice in order to ensure effective recall of information. It can directly impact a learner's performance in an intense situation where quick thinking is required.

## Cognitive load theory

John Sweller developed cognitive load theory (CLT) in the 1980s, building on what was then understood about the limits of working memory (Sweller, 1988). Cognitive load theory proposes that the total demand placed on working memory at any given moment comes from two sources.

![](https://www.kyleslinn.ca/content/images/2026/05/2.png)

*Intrinsic load* is the inherent complexity of the material itself. More complex information has a higher intrinsic load. For example, explaining ventricular septal defects carries a higher intrinsic load for a first-year nursing student than it would for a pediatric cardiologist. You can't eliminate intrinsic load, but you can manage it by sequencing content carefully and building foundational schemas before introducing more complex topics.

*Extraneous load* is the demand created by how material is presented rather than what it contains. Poorly organized slides, redundant text, irrelevant images, and noisy environments all add extraneous load without adding any learning value. Young et al. (2014) note in their guide on cognitive load theory and medical education that extraneous load is the primary target for instructional design improvements, and that even small reductions in extraneous load can meaningfully improve knowledge transfer.

![](https://www.kyleslinn.ca/content/images/2026/05/ChatGPT-Image-Apr-23--2026--01_28_08-PM.png)

**A fictional nasogastric tube insertion policy, one with tons of information that may not be relevant to a new employee learning the procedure for the first time. There is also no visual context provided, forcing the learner have to imagine what this text describes. Generally, I would recommended not using policies or procedure documents that look like this when initially teaching a clinical skill.*

Now, you may have encountered older descriptions of cognitive load theory that include a third type, germane load, defined as the cognitive effort dedicated to building schemas. Sweller himself has since reconceptualized germane load as a function of whatever working memory capacity remains after intrinsic and extraneous load are accounted for, rather than an independent source of load (Orru & Longo, 2019). In other words, free (or leftover) working memory capacity and germane load are effectively the same thing, and we don't need to have germane load as a separate concept. **This means the goal of good instructional design is straightforward: keep intrinsic load manageable and strip out extraneous load wherever you can.**

That "new hire" feeling from your orientation should make more sense now. In most cases, your working memory wasn't failing you, you were in cognitive overload due to unfamiliar terminology, information-dense slides, and overall too much new content at once. That left little capacity for the kind of deep processing that moves information into long-term memory.

## Takeaways

The multi-store model and cognitive load theory together offer a clear set of implications for educators.

- **Audit your sessions for extraneous load.** Go through your training materials and ask what is adding cognitive demand without adding learning value. Redundant text on slides, unexplained jargon, and information presented faster than it can be processed are all targets for removal.
- **Sequence content to build schemas, not just cover material.** Introduce foundational concepts before complex ones. Learners who have a schema to attach new information to will encode it faster and retain it longer than learners who are encountering everything at once.
- **Use both verbal and visual channels deliberately.** Because working memory has separate subsystems for verbal and visual information, presenting complementary information in both formats in serial (rather than duplicating the same content across both formats at the same time) increases effective capacity without overloading either channel.
- **Space rehearsal over time.** A single workshop asks working memory to do too much heavy lifting in too little time. Breaking content up across shorter sessions with retrieval practice in between gives long-term memory a chance to consolidate between exposures (Vagha et al., 2025). If you can spread orientation across several weeks and mix in real practice on the floor, learners will retain considerably more than if everything is front-loaded at the start.
- **Treat novice and expert learners differently.** An experienced learner with existing schemas can handle more complexity. Experienced learners also don't benefit from long explanations on things they already know - this will just adds extraneous load for them. A novice, on the other hand, needs very simple the instructional content so their working memory isn't oversaturated.

Each of these takeaways is grounded in research on multimedia learning theory, which we'll explore in the next post.

---

## References

Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), *The psychology of learning and motivation* (Vol. 2, pp. 89–195). Academic Press.

Orru, G., & Longo, L. (2019). The evolution of cognitive load theory and the measurement of its intrinsic, extraneous and germane loads: A review. In L. Longo & M. C. Leva (Eds.), *Human mental workload: Models and applications* (Communications in Computer and Information Science, Vol. 1012, pp. 23–48). Springer. https://doi.org/10.1007/978-3-030-14273-5\_3

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. *Cognitive Science*, *12*(2), 257–285\. https://doi.org/10.1207/s15516709cog1202\_4

Vagha, K., Choudhari, S. G., Taksande, A., Tembhurne, S., Vagha, J., & Vagha, S. (2025). Implementation of a spaced-repetition approach to enhance undergraduate learning and engagement in paediatrics. *Frontiers in Medicine*, *12*, 1601614\. https://doi.org/10.3389/fmed.2025.1601614

Young, J. Q., Van Merrienboer, J. J. G., Durning, S., & Ten Cate, O. (2014). Cognitive load theory: Implications for medical education: AMEE Guide No. 86\. *Medical Teacher*, *36*(5), 371–384\. https://doi.org/10.3109/0142159X.2014.889290
### What is schema theory?
URL: https://www.kyleslinn.ca/what-is-schema-theory/
Last updated: 2026-04-02T12:38:26.000Z
I want to start this post with a fictitious case study. 

Imagine that Maeve is a newly graduated nurse a few shifts into her first job in a pediatric emergency department. A 4-year-old arrives with noisy breathing, fever, and visible respiratory distress. Maeve starts her assessment and quickly thinks, “This sounds like croup.” She begins setting up the first-line interventions for the patient: nebulized dexamethasone and cool mist.

Maeve's mentor, a nurse with 10 years of experience, checks in on the patient and notices a few things Maeve missed. The child is in a tripod position (sitting upright and leaning forward), drooling, and can't breathe when they lie down on their back. Their voice sounds muffled, and their fever is 40 °C (104 °F). The mentor recognizes these symptoms don’t fit a typical case of croup, and wonders if the patient might instead have epiglottitis, a more serious condition with a very different treatment plan.

This vignette is a great example of the learning theory called *schema theory* and shows how it can impact clinical performance. 

Schemas are mental frameworks that help us organize disparate pieces of information into a meaningful whole. The theory suggests that instead of remembering dozens of separate details, our brains chunk bits of information into a single idea, concept, or construct that we can more easily recognize and act on. Schemas are how we know how to act in restaurants we've never been in before - either we walk up to the counter and order or wait to be handed a menu and seated. Because we have schemas in mind for how fast-food and slow(er) dining restaurants function, we understand how to behave given our established mental schemas from other restaurants that we've built over time. 

Essentially, you can think of a schema like a cluster of interconnected nodes that pull together observations and experiences that we've collected and remembered over time. Each node is a bit of information, such as a symptom, a risk factor, or an action treatment option for a specific condition. Some nodes may only have a single connection to them, whereas others may have many interconnections with other nodes. The more connections a node has, the easier it is to retrieve that bit of information when you need to think about it.

In our story, Maeve has a developing schema for croup - it's quite common, so she's saw it often during her training and has more experiences and observations to draw on - but her schema for epiglottitis is poorly developed. She may remember from lectures in school that epiglottitis is rare and a serious respiratory illness that can present in pediatric patients, but she doesn't really know how it presents and what symptoms it shares with other respiratory conditions.

To illustrate, Maeve’s schemas for croup and epiglottitis might look like this:

![A visual diagram showing the interlinking nodes of Maeve's croup and epiglottitis schemas.](https://www.kyleslinn.ca/content/images/2026/03/1.png)

Her preceptor, on the other hand, has much more refined schemas for both of these conditions, thanks to her years of experience.

![A visual diagram showing the interlinking nodes of Maeve's precetor's croup and epiglottitis schemas.](https://www.kyleslinn.ca/content/images/2026/03/2.png)

You can see the difference, not just in the node count, but also how interconnected each node is to the others within the schema.

# Assimilation and accommodation

[Piaget's famous theory of cognitive development](https://en.wikipedia.org/wiki/Piaget%27s%5Ftheory%5Fof%5Fcognitive%5Fdevelopment?ref=kyleslinn.ca) integrates well with schema theory. When someone learns something new (or has a novel experience), one of three things can happen:

- **Assimilation:** The person fits the new information into an existing schema. Assimilation requires less mental work from learners because they are connecting new nodes to existing nodes. In essence they are just modifying their understanding of an existing concept they know by appending the new information - kind of like tacking it on at the end of a list. So, to use our earlier example, Maeve could incorrectly assimilate epiglottitis as a form of “severe croup,” one that has the same treatment plan as croup. (Please note that this would be incorrect given the example!)
- **Accommodation:** The person builds a new schema (or substantially reshapes an old one). Accommodation requires more mental effort than assimilation does because it's much harder to create a new mental model of something that isn't well anchored in existing schemas. In essence, we have to build a whole new mental model based solely on this single piece of new information, or this one observation or experience, with only a few tentative nodes from other, related schemas to help ground the new schema. To use our earlier example again, Maeve could learn that epiglottitis is a distinctly separate condition, but some of its symptoms overlap with other upper respiratory conditions, including croup.
- **No change:** The person rejects the new information and doesn’t update their existing schema at all. In the case of our example, this would result in Maeve incorrectly refusing to believe that epiglotitis exists at all.

So that's what schemas are, how we form them, and how they might or might not change given new information or experiences.

# **Building better schemas**

Knowing all of this, are there strategies that can help us build better schemas and build them more quickly? Yes. Overall, from the schema theory lens, when teaching something new to learners, our goals should be to:

1. Activate what learners already know related to the new information
2. Make relationships between similar ideas explicit (instead of hoping learners infer them), and
3. Get learners to retrieve and use these schemas repeatedly over time.

Here are some ways we can achieve these objectives in practice. I'll continue using the example of croup to help illustrate these points:

- **Do frequent, quick retrieval.** Initiate a teachable moment and give yourself 5 to 10 minutes of review with the learner. You could ask the learner questions like, “What are your red flags for respiratory distress in kids?” and have them connect these to as many illnesses as they can remember. Then, you could watch a couple of short videos on YouTube of patients with respiratory distress and ask learners to name the key symptoms they see.
- **Group similar conditions together.**  
When teaching upper respiratory diseases to learners for the first time, teach croup alongside what it’s confused with in real life: bronchiolitis, asthma, foreign body aspiration, epiglottitis, pneumonia, and so on. Then, ask your learner to compare and contrast the conditions, like “What would signal to you that your patient has croup and isn't instead in the middle of an asthma attack?” Fun fact: This is why most of the textbooks on diagnosis are organized by symptoms, and not by organ system. They are trying to build strong schemas!
- **Use case variation.** When running case-based scenarios with learners, present sets of cases that differ on one key clinical feature, and have learners reflect on how that single difference changes the patient's care plan. For example, one at a time, vary the patient's age, onset (gradual vs. sudden), severity of fever, overall hydration and appetite, and the severity of the patient's work of breathing, and ask how the diagnosis and treatment would shift based on each single-variable change.
- **Avoid ambiguity.** When discussing teaching or reviewing clinical conditions, use descriptors that the learner can explicitly observe. It's most important to avoid using vague descriptions, like “the patient looks toxic,” or “they look bad,” or “they're working hard.” Instead, be specific and direct with your observations: the patient might be exhibiting retractions, nasal flaring, head bobbing, grunting, stridor at rest, cyanosis, or decreased responsiveness. We want to tie these concrete observable symptoms to the learner's newly forming schema. Vague terms make learners have to work unnecessarily harder to link these symptoms together in their schema, and they're more likely to make errors as a result.
- **Highlight your decision making pathways.** When working with patients, say your clinical reasoning out loud. This will help the learner connect the treatment to their existing schema directly, rather than making inferences based on what the teacher is doing (which, again, could lead to faulty schemas and errors in the future). For example, “Stridor at rest plus retractions makes me worry about significant upper airway obstruction. I'm concerned, I think we need to call for more support now.”
- **Have learners build concept maps or flowcharts.** Encourage learners to create a visual map of their schemas by building mind maps or flow charts. The act of creating this map will force them to think deeply about how each concept relates to each other and to clarify any misunderstandings in their existing schemas. Have them revisit their mind map every now and again to help them recall these connections, especially if they haven't seen that patient type or clinical presentation for a while.

![Image of a concept map about a concept map.](https://www.kyleslinn.ca/content/images/2026/03/Concept_Map_About_Concept_Maps.jpg)

This is a concept map about concept maps!

# Key takeaways

So, in summary:

- Schemas are a web of interconnected ideas that help us organize information into meaningful mental frameworks.
- The more interconnected these ideas are, the stronger we remember them and the easier it is to remember them.
- It's good teaching practice to make the relationships between ideas within a schema or between schemas explicit and give learners repeated chances to retrieve and apply the right schema.

## References

- Concept map image. Author: Dvitalo12 [License: CC-BY-SA](https://commons.wikimedia.org/wiki/File:Concept%5FMap%5FAbout%5FConcept%5FMaps.jpg?ref=kyleslinn.ca)
### The Learning Pyramid Is Built on Sand
URL: https://www.kyleslinn.ca/the-learning-pyramid-is-built-on-sand/
Last updated: 2026-03-03T13:25:38.000Z
I know I promised I’d dig into adult learning theory in my next post, but as I started writing it, I realized I need to lay a bit more groundwork first, specifically around information processing theory (which I have yet to write about). So to tide you over in the meantime, here’s a quick post discussing a different learning myth you’ve probably come across. I present to you: the Learning Pyramid.

![A diagram of the learning pyramid.](https://www.kyleslinn.ca/content/images/2026/02/1-3.png)

The lore of the Learning Pyramid is founded on the idea that we retain information in predictable percentages depending on *how* we learn it. “Passive” methods like reading or listening supposedly lead to low retention, while “active” methods like discussion, practice, or teaching others supposedly lead to much higher retention.

It’s appealing because it feels intuitive. I *also* feel like I remember things better when I explain them to someone else.

But once we start looking at this pyramid and its claims with a critical eye, it quickly becomes apparent that none of it holds up to scrutiny. Letrud (2012) [lays out a helpful critique](https://www.researchgate.net/publication/285798853%5FA%5Frebuttal%5Fof%5FNTL%5FInstitute's%5Flearning%5Fpyramid?ref=kyleslinn.ca), and I have thrown in a few thoughts as well.

# The Issues

1. **Teaching others is paradoxical.** The “teaching others” category creates a bit of a paradox. In order to teach something well, you have to have learned it yourself first, right? And presumably you learned it through one (or more) of those supposedly “inferior” methods, like reading, listening, or watching. So how can we claim that teaching others is the *best* way to learn, if it depends entirely on the teacher having already learned the material through some other method?
2. **Statistics aren't that clean.** As David Didau [rightly points out](https://daviddidau.substack.com/p/the-costs-of-believing-in-bullshit), the average retention rates associated with the Learning Pyramid are clean multiples of five. Real-world data is never that tidy. So either the numbers are completely made up, or they’ve been rounded so heavily that they’re no longer accurate.
3. **The categories overlap.** The tier categories are so loosely defined that they blur into each other. For example, let's consider a video, which most intuitively fits into the "audio-visual" category. But a video might include narration (basically a lecture - described as an "inferior" method of learning), on-screen text (which requires reading - another "inferior" method), and demonstrations (the next tier up from audio-visual) — all wrapped into one. So which category is this video supposed to fall into? It’s never really clear how these learning activities are being defined, or where one ends and another begins.
4. **How in the world do you design research to test this theory?** Let’s imagine we’re the researchers trying to test the propositions of the Learning Pyramid. How on earth would we even design a study to isolate learning experiences into these neat little categories? Take “demonstration,” for example. How would we make sure participants learned *only* through a demonstration, without reading anything, without hearing an explanation, without discussing it with anyone afterward? In the real world, these activities almost always overlap. Also, how would we isolate the independent variable and control for all the inevitable confounding variables when the categories themselves are so loosely defined? It starts to feel practically impossible. But for this pyramid to exist, someone must have done it, so let's look at the methods they used!

Now, there have been plenty of spin-offs of this pyramid over the years, but the most popular version, the one most people are referring to when they say “the Learning Pyramid” comes from the NTL Institute. Theirs is the version represented in my illustration above.

If you reach out to them (as many curious researchers have, including [Booth, 2011](https://alastore.ala.org/content/reflective-teaching-effective-learning-instructional-literacy-library-educators?ref=kyleslinn.ca); [Lalley & Miller, 2007](https://eric.ed.gov/?id=EJ790160&ref=kyleslinn.ca); [Letrud, 2012](https://www.researchgate.net/publication/285798853%5FA%5Frebuttal%5Fof%5FNTL%5FInstitute's%5Flearning%5Fpyramid?ref=kyleslinn.ca)), you’ll typically get a response that looks something like this:

> "Thanks for your interest in NTL Institute. We are happy to respond to your inquiry about The Learning Pyramid. It was developed and used by NTL Institute at our Bethel, Maine campus in the early sixties when we were still a part of the National Education Association's Adult Education Division. 

> While we believe it to be accurate, we no longer have- nor can we find the original research that supports the numbers. We get many inquiries every month about this- and many, many people have searched for the original research and have come up empty handed. 

> We know that in 1954 a similar pyramid with slightly different numbers appeared on p. 43 of a book called Audio-Visual Methods in Teaching, published by the Edgar Dale Dryden Press in New York however the Learning Pyramid as such seems to have been modified and remains attributed to NTL Institute."

So they claim that they once had research supporting their claims, but they lost it. It was at this point while I was doing my research on this topic where my brain did this:

![](https://www.kyleslinn.ca/content/images/2026/02/chair-throw.gif)

So is this whole thing just completely made up? Well… sort of.

# The Origins of the Pyramid

[Letrud and Hernes (2018)](https://doi.org/10.1080/2331186X.2018.1518638?ref=kyleslinn.ca) do an excellent job of tracing the origins of the Learning Pyramid and untangling where it actually came from. I'll quickly summarize what they found.

The core idea that people remember only a little of what they read or hear but much more of what they say, or do appears to date back at least to the 1850s. These were rhetorical or common-sense claims, not backed by any research. In 1967, D.G. Treichler popularized the percentages of average retention rates and implied these numbers were backed by research but never provided any sources as proof. Later, these retention rates were fused with a misinterpretation of Edgar Dale’s (1954) Cone of Experience, creating the modern learning pyramid graphic that stands before you today. Letrud and Hernes conclude that the Learning Pyramid is a quasi-scientific myth that has survived for over 160 years, but has never been backed by empirical research.

So at the very least, we can say with a fair bit of confidence that the NTL Institute’s claim — that their Learning Pyramid is grounded in original research — is probably not true.

# The Pyramid Isn't Aligned with Widely Accepted Learning Theories

The Learning Pyramid assumes that how you take in information — by reading or hearing — is the main thing that determines how much you’ll remember. Modern cognitive psychology rejects this view. In the well-known Atkinson–Shiffrin (1968) model of memory, what really determines retention isn’t the format of the input. Instead, other factors are far more influential like attention, how deeply you process the information, whether it makes sense to you, and how well it connects to what you already know.

Long-term memory doesn’t choose what information to store based on how it came in (whether you “heard” it or “saw” it). Information is stored based on meaning and how it connects to other ideas. The Learning Pyramid’s focus on ranking formats ignores decades of research showing that retention actually depends on factors like prior knowledge, depth of processing, the kind of rehearsal you do, context, and retrieval practice. In short, the Learning Pyramid treats learning like a simple input-output system, while modern memory science sees learning as active, constructive, and highly dependent on context.

[David Didau ](https://daviddidau.substack.com/p/the-costs-of-believing-in-bullshit)points out that the real danger here isn’t just that the numbers are wrong. It’s that the Learning Pyramid quietly pushes a flawed theory of learning, one that prioritizes visible performance over genuine understanding. If we believe discussion automatically leads to retention, we may prioritize having learners talk about concepts before they actually understand the material. If we treat “teaching others” as the fast track to mastery, we risk asking students to explain ideas they don’t yet understand themselves. And this could end up short-changing learners in the long run.

# References

Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), *The psychology of learning and motivation* (Vol. 2, pp. 89–195). Academic Press.
### Pourquoi les mythes inoffensifs en éducation ne le sont pas du tout
URL: https://www.kyleslinn.ca/french/test-post/
Last updated: 2026-02-14T01:52:32.000Z
*Cet article a été initialement rédigé en anglais et traduit par intelligence artificielle. Les liens vers des sources externes ne sont disponibles que dans les articles en anglais.*

Dans le dernier article, nous avons discuté du fait que la théorie des styles d'apprentissage ne repose pas sur des preuves très solides. Mais vous vous dites peut-être : « D'accord, mais est-ce vraiment important ? Même si ce n'est pas prouvé, quel mal y a-t-il à croire que c'est valide ou à laisser les autres y croire ? »

Pour moi, cette conversation est essentielle, car je suis convaincu que le fait de s'accrocher à des théories non fondées (comme les styles d'apprentissage) et de les perpétuer cause un réel préjudice aux apprenants. Dans cet article, j'aimerais partager pourquoi.

### Nous travaillons avec des ressources limitées

Chaque environnement éducatif — qu'il s'agisse d'une école privée, d'une université publique, d'un programme de formation hospitalier ou d'un département de formation en entreprise — a ses limites. On finit toujours par manquer de temps, de personnel, de budget, et même d'attention et de motivation de la part des apprenants. Alors, lorsque les ressources sont limitées, devrions-nous investir dans des stratégies d'enseignement dont nous savons qu'elles fonctionnent ou dans celles dont nous savons qu'elles ne fonctionnent pas ?

La réponse semble évidente, non ? Bien sûr, nous devrions choisir ce qui fonctionne ! Mais ce n'est pas toujours ce qui se passe. Parfois, les décideurs choisissent sciemment l'option inefficace.

Prenons l'exemple de l'arrêt du tabac basé uniquement sur l'abstinence stricte. Cette approche pousse les patients à arrêter totalement la nicotine, souvent de manière brutale. Pourtant, la plupart des gens n'y parviennent pas, et cette stratégie peut causer du tort en décourageant les tentatives futures d'arrêt. À l'inverse, les approches de réduction des méfaits, comme la réduction graduelle ou le passage à des alternatives moins nocives, ont souvent de bien meilleurs résultats à long terme. Malgré ces preuves, certaines directives cliniques continuent de demander aux prestataires de soins d'enseigner uniquement les méthodes basées sur l'abstinence.

Ainsi, lorsque nous enseignons des stratégies inefficaces, nous ne faisons pas que gaspiller des ressources : nous les retirons activement des stratégies qui aident réellement les apprenants à réussir. Et ce faisant, nous portons directement préjudice aux personnes que nous sommes censés aider.

### Les équipes de direction ne sont pas toujours au fait des réalités pédagogiques

Lorsque nous laissons traîner des théories éducatives non fondées et qu'elles continuent d'être perçues comme égales à celles fondées sur des preuves, nous créons un véritable problème pour les décideurs. Les administrateurs d'hôpitaux, les dirigeants d'universités ou les fonctionnaires ne sont souvent pas des experts en sciences de l'apprentissage ou en psychologie de l'éducation. Ils peuvent se fier à ce qu'ils ont entendu dire ou à ce qui semble crédible et, par conséquent, allouer des ressources à des stratégies qui ne fonctionnent pas réellement.

Ils peuvent se tourner vers nous, les experts pédagogiques de nos organisations, pour demander conseil. Si nous leur disons de suivre des stratégies qui ne sont pas étayées par des preuves, non seulement nous gaspillons ces ressources limitées, mais nous risquons de perdre leur confiance lorsque la formation ne produira pas les résultats escomptés. Et une fois que vous perdez votre crédibilité auprès de la direction, il devient beaucoup plus difficile de défendre ce qui fonctionne réellement par la suite. Car plus tard, vous devrez nager à contre-courant, en contrant un discours public qui soutient le mythe que vous essayez de dissiper. Il faudra beaucoup plus de confiance pour obtenir le feu vert pour une stratégie d'enseignement fondée sur des preuves mais moins connue, et cette confiance risque de faire défaut après l'expérience de formation précédente (échouée).

### Les apprenants perdent confiance en eux

Un autre risque auquel nous sommes confrontés en enseignant des stratégies éducatives inefficaces est de faire perdre aux apprenants confiance en leurs capacités. Tout d'abord, nous savons que la motivation et le sentiment d'efficacité personnelle (auto-efficacité) d'un apprenant sont étroitement liés à son expérience de réussite. En d'autres termes, ils sont motivés lorsqu'ils peuvent constater leurs progrès, et leur conviction qu'ils peuvent réussir à apprendre encore plus à l'avenir s'améliore également. Si nous utilisons des stratégies d'enseignement inefficaces, nous programmons l'échec des apprenants, qui risquent alors de perdre à la fois leur motivation à continuer d'apprendre et leur conviction qu'ils peuvent réussir la tâche donnée.

La perte de confiance et de motivation sont également des risques majeurs liés au mythe des styles d'apprentissage. Lorsque les apprenants croient que les styles d'apprentissage sont réels et fondés sur des preuves, et qu'ils rencontrent ensuite du matériel qui ne correspond pas à leur prétendu « style », ils peuvent supposer qu'ils ne réussiront pas parce que le matériel d'apprentissage n'adhère pas à leurs préférences. En conséquence, ils peuvent ne pas essayer de s'engager avec le matériel dès le départ et renoncer complètement à cette opportunité d'apprentissage, même si elle aurait pu (et aurait probablement) été précieuse.

Dans les deux cas, une motivation et une auto-efficacité réduites peuvent façonner les décisions futures d'un apprenant. Les apprenants peuvent investir moins d'efforts dans de nouveaux apprentissages, éviter les opportunités de développement professionnel ou décider de ne pas poursuivre d'études supérieures ou de rôles de direction. Ces choix peuvent contribuer à une moins bonne performance au travail ou à une stagnation de carrière, ce qui peut à son tour renforcer les croyances négatives sur leurs capacités. Au fil du temps, ce cycle peut éroder la confiance en soi de l'apprenant, son potentiel de revenus, ainsi que sa satisfaction professionnelle et personnelle.

Ce qui commence comme une croyance apparemment inoffensive sur les styles d'apprentissage a finalement le potentiel de restreindre les opportunités actuelles et futures d'un apprenant.

### Confiance du public et réputation

Ces effets ne se limitent pas aux salles de classe. Ils peuvent affecter la façon dont les institutions sont perçues de l'extérieur par les apprenants, les dirigeants et le public.

Les établissements d'enseignement, en particulier les écoles, les universités et les organismes de santé, ne se contentent pas de dispenser des formations. Ils font des promesses implicites. Lorsqu'ils éduquent des apprenants, ils s'engagent à les soutenir avec un enseignement efficace, justifiable et qui vaut leur temps. Lorsque ces programmes sont construits sur des théories bancales, cette promesse est rompue.

Imaginez que la presse découvre qu'une institution a investi massivement dans une approche éducative que la communauté de la recherche remet en question, ou rejette carrément, depuis des décennies. Peu importe que l'équipe pédagogique ait eu connaissance ou non des pratiques fondées sur des preuves. S'ils ne le savaient pas, l'institution paraît mal informée ou incompétente. S'ils le savaient, cela donne l'impression que les résultats des apprenants n'étaient pas une priorité. Dans les deux cas, la crédibilité institutionnelle en prend un coup, car nous savons tous que les contribuables réagissent vivement lorsqu'ils pensent que leur argent est gaspillé ou mal dépensé.

Vous pourriez supposer que le public ne se souciera pas de quelque chose d'aussi technique que la conception pédagogique (instructional design). Mais l'histoire suggère le contraire. Les débats sur la méthode globale et l'approche équilibrée de la lecture, l'enseignement des mathématiques par la découverte, les tests standardisés et l'utilisation des écrans en classe sont tous des exemples qui montrent que le public se soucie profondément de la manière dont l'apprentissage se déroule, surtout lorsque les résultats sont médiocres.

Avec le temps, des décisions maladroites en matière d'enseignement érodent la confiance dans la capacité de l'institution à prendre des décisions saines et fondées sur des preuves concernant l'apprentissage.

### Nous risquons de sous-évaluer l'expertise pédagogique

Une raison peu discutée pour laquelle des théories non fondées comme les styles d'apprentissage persistent est que l'éducation elle-même est souvent traitée comme une « compétence douce » (soft skill), quelque chose que n'importe qui peut faire s'il connaît assez bien le contenu.

Vous avez probablement entendu le dicton : « Ceux qui ne savent pas faire, enseignent. » Cela reflète une incompréhension commune : que l'expertise dans un sujet se traduit automatiquement par une expertise dans l'enseignement de ce sujet.

En réalité, concevoir des expériences d'apprentissage efficaces nécessite une connaissance approfondie de la théorie éducative, des sciences cognitives et de la conception de l'évaluation, ainsi que des années d'expérience pratique. Ce sont des compétences spécialisées, au même titre que l'expertise clinique, technique ou juridique. C'est pourquoi le programme de *Sesame Street* (1, rue Sésame) a toujours été créé en étroite collaboration avec des spécialistes formés en éducation de la petite enfance — les créateurs voulaient un produit efficace pour enseigner, ils ont donc investi dans ceux qui avaient une connaissance approfondie des sciences de l'apprentissage.

Lorsque les institutions acceptent des théories apparemment intuitives mais non fondées, elles sapent involontairement cette expertise, et les professionnels de l'éducation deviennent des exécutants plutôt que des experts en la matière et des conseillers. Je l'ai vu de mes propres yeux. Lorsque l'expertise pédagogique est dévalorisée, les décisions concernant la conception des programmes sont dictées par des préférences personnelles, des anecdotes et l'intuition, plutôt que par ce qui améliore réellement l'apprentissage.

Lorsque les professionnels de l'éducation ne sont pas habilités à insister sur des pratiques fondées sur des preuves, les résultats des apprenants en souffrent, et cela peut renforcer la croyance que l'éducation est une affaire de devinettes plutôt qu'une discipline fondée sur la recherche. Les théories non fondées ne font pas que gaspiller des ressources — elles rendent plus difficile pour les professionnels de l'éducation de faire le travail pour lequel ils ont été formés et de démontrer la valeur de ce travail.

### Ce qu'il faut retenir

Alors, que devrions-nous faire de tout cela ?

Premièrement, nous devons traiter les décisions éducatives avec la même gravité que les décisions cliniques, politiques ou opérationnelles. Lorsque le temps, l'argent et l'effort des apprenants sont limités — et ils le sont toujours —, l'utilisation de stratégies qui « semblent justes » mais qui ne sont pas étayées par des preuves peut avoir des conséquences réelles pour les apprenants, les institutions et la confiance du public.

Deuxièmement, parlez à vos professionnels de l'éducation tôt et souvent. Demandez quelles théories et quels cadres façonnent vos programmes de formation et pourquoi. De nombreux concepteurs pédagogiques, spécialistes de l'apprentissage et responsables du développement professionnel sont déjà conscients des limites des idées pseudo-scientifiques populaires comme les styles d'apprentissage, mais peuvent manquer d'autorité ou de soutien institutionnel pour les contester. Ils ont besoin du soutien de la direction, surtout si un changement organisationnel est nécessaire pour mettre à jour les méthodes de formation existantes.

Troisièmement, auditez les programmes existants avec un œil critique. Les théories non fondées persistent souvent non pas parce que quelqu'un les a choisies activement, mais parce que les programmes sont transmis, réutilisés et modifiés sans jamais être réévalués et reconstruits de fond en comble. Identifier et supprimer les pratiques à faible valeur libère des ressources pour investir dans des stratégies qui améliorent réellement l'apprentissage.

Enfin, rappelez-vous que l'éducation fondée sur des preuves ne consiste pas à courir après les tendances ou la perfection. C'est une question d'honnêteté intellectuelle — être prêt à abandonner des idées lorsque les preuves ne les soutiennent pas, même si elles sont familières ou intuitivement séduisantes. Cet état d'esprit protège les apprenants, renforce les institutions et conforte l'éducation en tant que discipline professionnelle qu'elle est véritablement.

Si vous avez aimé cette discussion et souhaitez en lire plus, David Didau a publié sa propre opinion à ce sujet alors que je terminais mon article. David est un auteur prolifique sur les meilleures pratiques éducatives fondées sur des preuves en matière d'alphabétisation pour la maternelle à la 12e année (K-12).

Dans la prochaine infolettre, nous ferons une analyse approfondie d'un autre concept qui est devenu un peu un phénomène pop — les « principes d'apprentissage des adultes » — et ce que les preuves disent réellement sur la façon dont les adultes apprennent le mieux.
### Why Harmless Myths in Education Aren’t Harmless at All
URL: https://www.kyleslinn.ca/why-harmless-myths-in-education-arent/
Last updated: 2026-05-13T21:20:43.000Z
Last post, we discussed how learning styles theory doesn’t actually have much evidence supporting it. But you might be thinking, “Okay, but does this really matter? Like, even if it’s not proven, what’s the harm in believing it’s valid or letting others believe it’s valid?”

To me, this conversation is an important one, because I believe that hanging on to and perpetuating unsupported theories (like learning styles) is actually causing real harm to learners. In this post, I’d like to share why.

# We’re Working with Limited Resources

Every educational setting—whether it’s a private school, a public university, a hospital training program, or a corporate learning department—has limits. You eventually run out of time, staff, budget, and even your learners’ attention and motivation. So when resources are tight, should we invest in teaching strategies we know work or ones we know don’t work?

Sounds like an obvious answer, right? Of course we should choose what works! But this doesn’t always happen. Sometimes decision-makers knowingly choose the ineffective option anyway.

Take abstinence-only smoking cessation as an example. This approach pushes patients to quit nicotine entirely, often abruptly. [Yet most people don’t succeed](https://www.youtube.com/watch?v=vicVQXC1Z6U&ref=kyleslinn.ca), and the strategy can cause harm by discouraging future attempts to quit. In contrast, harm-reduction approaches, like gradual reduction or switching to less harmful alternatives, often have much better long-term outcomes. Despite this evidence, [some clinical guidelines continue ](https://www.youtube.com/watch?v=vicVQXC1Z6U&ref=kyleslinn.ca)to tell healthcare providers to teach abstinence-only methods to patients.

So, when we teach ineffective strategies, we’re not just wasting resources, **we’re actively taking them away** from strategies that actually help learners succeed. And in the process, we’re directly harming the people we’re supposed to be helping.

# Leadership Teams Don’t Have Their Finger on the Pulse

When we let unsupported educational theories hang around and continue to be perceived as equal to evidence-based ones, we create a real problem for decision-makers. Hospital administrators, university leaders, or government officials are often not experts in learning science and educational psychology. They may rely on what they’ve heard or what seems credible, and as a result, allocate resources to strategies that don’t actually work.

They might turn to us, the educational experts in our organizations, and ask for advice. If we tell them to follow strategies that aren’t backed by evidence, not only are we wasting those limited resources, but we risk losing their trust when the training doesn’t produce the desired results. And once you lose credibility with leadership, it becomes much harder to advocate for what actually works later on down the road. Because later, you’ll be swimming upstream, countering public discourse that supports the myth you’re trying to dispel. It will take a lot more trust to get them to green-light the evidence-based but less well-known teaching strategy, and that trust may now be in short supply after the previous (failed) training experience.

# Learners Lose Their Confidence

Another risk we face by teaching ineffective educational strategies is causing learners to lose confidence in their abilities. First, we know that a learner’s motivation and self-efficacy are closely related to their experience of being successful. In other words, they are motivated when they can see their improvements, and their belief that they can be successful at learning even more in the future improves, as well. If we use ineffective teaching strategies, we’re setting learners up to fail, and in turn they may lose both their motivation to keep learning and their belief that they can succeed at the given task.

Loss of confidence and motivation are big risks of the learning styles myth, too. When learners believe that learning styles are real and evidence-based, and then they encounter material that doesn’t match their supposed “style,” they might assume they won’t be successful because the learning material does not adhere to their preferences. As a result, they may not try to engage with the material in the first place and completely forgo this learning opportunity, even though it could have (and probably would have) been valuable.

In both cases, [reduced motivation and self-efficacy can shape a learner’s future decisions](https://www.sciencedirect.com/science/article/abs/pii/S0001879108000973?ref=kyleslinn.ca). Learners may invest less effort in new learning, avoid professional development opportunities, or decide not to pursue graduate education or leadership roles. These choices can contribute to poorer job performance or career stagnation, which in turn can reinforce negative beliefs about their abilities. Over time, this cycle can erode the learner’s self-confidence, earning potential, and career and life satisfaction.

What begins as a seemingly harmless belief about learning styles ultimately has the potential to narrow a learner’s current and future opportunities.

# Public Trust and Reputation

These effects don’t stay contained within classrooms either. They can affect how institutions are perceived externally, by learners, leaders, and the public.

Educational institutions, especially schools, universities, and health care organizations, don’t just deliver training. They make implicit promises. When they educate learners, they are committing to supporting them with instruction that is effective, defensible, and worth their time. When those programs are built on shaky theories, that promise is broken.

Imagine the press discovering that an institution has invested heavily in an educational approach that the research community has been questioning, or outright rejecting, for decades. It doesn’t matter whether the education team knew of the evidence-based practices or not. If they didn’t know, the institution looks uninformed or incompetent. If they did know, it looks like learner outcomes weren’t a priority. Either way, institutional credibility takes a hit because we all know that tax-payers have big feelings when they think their money is being wasted or poorly spent.

Now, you might assume the public won’t care about something as technical as instructional design. But history suggests otherwise. Debates over [whole reading](https://ottawacitizen.com/news/local-news/ontario-schools-need-sweeping-changes-to-help-children-learn-to-read-ontario-human-rights-commission?ref=kyleslinn.ca) and [balanced literacy](https://www.thestar.com/news/gta/ontario-kindergarten-changes/article%5Fdc4ee6cc-0b7b-4cb7-9bc8-eb1400afd473.html?ref=kyleslinn.ca),[ inquiry-based math instruction](https://www.ctvnews.ca/canada/article/why-canadian-students-are-falling-behind-in-math-and-what-experts-say-needs-to-change/?ref=kyleslinn.ca), [standardized testing](https://www.cbc.ca/player/play/video/9.6915699?ref=kyleslinn.ca), and the [use of screens in the classroom](https://www.cbc.ca/news/canada/sudbury/technology-electronic-screens-teaching-elementary-health-harm-1.7261086?ref=kyleslinn.ca) are all examples that show the public cares deeply about *how* learning happens, especially when learning outcomes are poor.

Over time, fumbling decisions about teaching erodes trust in the institution’s ability to make sound, evidence-based decisions about learning.

# We Can Undervalue Educational Expertise

One underdiscussed reason why unsupported theories like learning styles persist is that education itself is often treated as a “soft” skill, something anyone can do if they know the content well enough.

You’ve probably heard the saying, *“Those who can’t do, teach.”* It reflects a common misunderstanding: that expertise in a subject automatically translates into expertise in teaching that subject.

In reality, designing effective learning experiences requires deep knowledge of educational theory, cognitive science, and assessment design, along with years of practical experience. These are specialized skills, no different from clinical, engineering, or legal expertise. This is why the Sesame Street curriculum has always been created in close collaboration with [trained early education specialists](https://sesameworkshop.org/about-us/press-room/turn-everyday-moments-learning-adventures-sesame-streets-ready-school/?ref=kyleslinn.ca)—the creators wanted a product that was effective at teaching, so they invested in those who have deep background knowledge on learning science.

When institutions accept seemingly intuitive but unsupported theories, they unintentionally undermine that expertise, and educational professionals become implementers rather than subject-matter experts and advisors. I’ve seen this firsthand. When educational expertise is discounted, decisions about curriculum design get driven by personal preference, anecdotes, and intuition, rather than by what actually improves learning.

When education professionals aren’t empowered to insist on evidence-based practices, learner outcomes suffer, and it can reinforce the belief that education is guesswork rather than a research-driven discipline. Unsupported theories don’t just waste resources—they make it harder for educational professionals to do the work they were trained to do and to demonstrate the value of that work.

# Takeaways

So what should we do with all of this?

First, we need to treat educational decisions with the same gravity we bring to clinical, policy, or operational decisions. When time, money, and learner effort are limited—and they always are—using strategies that *feel* right but aren’t supported by evidence can have real consequences for learners, institutions, and public trust.

Second, talk to your education professionals early and often. Ask what theories and frameworks are shaping your training programs and why. Many instructional designers, learning specialists, and professional development leaders are already aware of the limitations of popular pseudoscientific ideas like learning styles, but may lack the authority or institutional backing to challenge them. They need leadership support, especially if organizational change is needed to update the existing training methods.

Third, audit existing programs with a critical eye. Unsupported theories often persist not because anyone actively chose them, but because curricula get handed down, reused, and modified without ever being reassessed and rebuilt from the ground up. Identifying and removing low-value practices frees up resources to invest in strategies that actually improve learning.

Finally, remember that evidence-based education isn’t about chasing trends or perfection. It’s about intellectual honesty—being willing to let go of ideas when the evidence doesn’t support them, even if they’re familiar or intuitively appealing. That mindset protects learners, strengthens institutions, and reinforces education as the professional discipline it truly is.

If you liked this discussion and want to read more, David Didau [posted his own take](https://daviddidau.substack.com/p/the-costs-of-believing-in-bullshit?r=9hr5a) on this as I was finishing up my post. David is a prolific writer about evidenced-based educational best practices in literacy for K-12.

In the next newsletter, we’ll do a deep dive on another concept that’s become a bit of a pop phenomenon —“adult learning principles”—and what the evidence actually says about how adults learn best.
### 教育における無害な神話がなぜ全く無害ではないのか
URL: https://www.kyleslinn.ca/japanese/jiao-yu-niokeruwu-hai-nashen-hua-ganazequan-kuwu-hai-dehanainoka/
Last updated: 2026-02-14T18:32:21.000Z
この記事は元々英語で書かれ、人工知能を用いて翻訳されました。外部ソースへのリンクは、記事の英語版でのみ利用可能です。

前回の投稿では、「学習スタイル（Learning Styles）」説には、実はそれを裏付ける根拠があまりないという話をしました。しかし、皆さんはこう思っているかもしれません。「わかった、でもそれって本当に重要なこと？ たとえ証明されていなくても、それが有効だと信じたり、他人にそう信じさせたりすることに何か実害があるの？」と。

私にとって、これは非常に重要な議論です。なぜなら、根拠のない理論（学習スタイルのようなもの）にしがみつき、それを広め続けることは、**学習者に対して実害を及ぼしている**と信じているからです。今回の投稿では、その理由をお話ししたいと思います。

## 私たちが持つリソースは限られている

私立学校であれ、公立大学であれ、病院の研修プログラムや企業の学習開発部門であれ、あらゆる教育の現場には限界があります。時間、スタッフ、予算、そして学習者の集中力やモチベーションさえも、いつかは尽きてしまうものです。リソースが逼迫しているとき、私たちは「効果があるとわかっている戦略」と「効果がないとわかっている戦略」、どちらに投資すべきでしょうか？

答えは明白ですよね？ もちろん、効果があるものを選ぶべきです！ しかし、現実は必ずしもそうではありません。意思決定者が、効果がないと知りながらあえて非効率な選択肢を選ぶことさえあります。

例えば、「完全禁煙（禁欲）」のみを指導するアプローチを考えてみましょう。この方法は患者に対し、ニコチンを完全に、多くの場合は急激に絶つことを強います。しかし、ほとんどの人は成功せず、失敗体験が将来の禁煙への意欲を削ぐという害をもたらすことさえあります。対照的に、徐々に減らしたり、害の少ない代替手段に切り替えたりする「ハーム・リダクション（害の低減）」アプローチの方が、長期的にははるかに良い結果をもたらすことが多いのです。こうした証拠があるにもかかわらず、一部の臨床ガイドラインでは、依然として医療従事者に対し、患者へ完全禁煙法のみを指導するよう指示しているものがあります。

つまり、私たちが効果のない戦略を教えるとき、単にリソースを無駄にしているだけではありません。**学習者の成功を実際に助ける戦略から、リソースを奪っているのです。** そしてその過程で、本来助けるべき人々に対して直接的な害を与えてしまっています。

## リーダー層は現場の実情（科学的根拠）に疎い

根拠のない教育理論を放置し、それらをエビデンス（科学的根拠）に基づく理論と同等に扱い続けることは、意思決定者にとって深刻な問題を引き起こします。病院の管理者、大学のリーダー、政府関係者などは、多くの場合、学習科学や教育心理学の専門家ではありません。彼らは耳にした情報や「もっともらしく聞こえる」話を頼りにし、その結果、実際には効果のない戦略にリソースを配分してしまうことがあります。

彼らは組織内の教育専門家である私たちに助言を求めるかもしれません。もし私たちが根拠のない戦略を勧めた場合、限られたリソースを無駄にするだけでなく、研修が期待通りの結果を出せなかったときに、リーダーからの信頼を失うリスクがあります。一度リーダーシップ層からの信頼を失うと、将来的に「本当に効果のある方法」を提案することが非常に難しくなります。

なぜなら、後になってその誤解（神話）を支持する世間の常識に反論し、流れに逆らって進言しなければならなくなるからです。エビデンスには基づいているがあまり知られていない教育戦略に「GOサイン」を出してもらうには、以前よりも大きな信頼が必要になりますが、過去の（失敗した）研修経験のせいで、その信頼はすでに枯渇しているかもしれません。

## 学習者が自信を失う

効果のない教育戦略を教えることのもう一つのリスクは、学習者が自分の能力に対する自信を失ってしまうことです。

まず、学習者のモチベーションと自己効力感（セルフ・エフィカシー）は、成功体験と密接に関連していることがわかっています。言い換えれば、自分の進歩を実感できたときにやる気が高まり、「将来もっと学べば成功できる」という信念も向上します。もし効果のない教育戦略を使えば、学習者を失敗へと導くことになり、結果として学習への意欲と「自分はできる」という信念の両方を失わせてしまう恐れがあります。

自信とモチベーションの喪失は、「学習スタイル」神話における大きなリスクでもあります。学習者が「学習スタイルは実在し、科学的だ」と信じ込んでいる状態で、自分の「スタイル」と一致しない教材に出会ったとき、彼らは「自分の好みに合っていないから、うまくいかないだろう」と思い込むかもしれません。その結果、最初から教材に取り組もうとせず、本来なら有益であったはずの学習機会を完全に逃してしまう可能性があります。

いずれのケースでも、モチベーションと自己効力感の低下は、学習者の将来の意思決定を左右します。新しい学習への努力を惜しむようになったり、能力開発の機会を避けたり、大学院進学やリーダー職への挑戦を諦めたりするかもしれません。こうした選択は、仕事のパフォーマンス低下やキャリアの停滞につながり、さらに自分の能力に対する否定的な信念を強化してしまいます。時間の経過とともに、この悪循環は学習者の自信、収入、そしてキャリアや人生の満足度を蝕んでいくのです。

学習スタイルに関する一見無害な思い込みが、最終的には学習者の現在および将来の可能性を狭めることになりかねません。

## 社会的信頼と評判への影響

これらの影響は教室の中だけにとどまりません。組織が学習者、リーダー、そして一般社会からどう見られるかという対外的な評価にも影響します。

教育機関、特に学校、大学、医療機関は、単にトレーニングを提供しているだけではありません。彼らは「暗黙の約束」を交わしています。学習者を教育するとき、機関は「効果的で、正当性があり、時間を費やす価値のある指導で支援する」と約束しているのです。プログラムが根拠の薄い理論の上に構築されている場合、その約束は破られたことになります。

もし、ある機関が何十年もの間、研究コミュニティから疑問視、あるいは完全に否定されてきた教育アプローチに巨額の投資をしていたことが報道されたらどうなるか想像してみてください。教育チームがエビデンスに基づく実践を知っていたかどうかは関係ありません。知らなかったとすれば、その機関は情報不足で無能に見えます。知っていたとすれば、学習者の成果を優先していなかったように見えます。いずれにせよ、納税者は自分たちのお金が無駄に使われたり、不適切に使われたりすることに敏感であるため、組織の信頼性は打撃を受けます。

「一般市民はインストラクショナル・デザイン（教育設計）のような専門的なことには関心がないだろう」と思うかもしれません。しかし、歴史はそうではないことを示しています。「ホール・ランゲージ」対「バランス・リテラシー」の論争、探究型数学指導、標準学力テスト、教室でのスクリーン利用などの例は、一般市民が「学習がどのように行われるか」について、特に学習成果が低い場合には、深い関心を持つことを示しています。

教育に関する誤った決定を繰り返せば、時間が経つにつれて、「学習について健全でエビデンスに基づいた決定を下す能力がこの組織にはある」という信頼が損なわれていくのです。

## 教育の専門性を軽視する恐れ

学習スタイルのような根拠のない理論が存続する、あまり議論されていない理由の一つは、教育自体がしばしば「ソフトスキル」として扱われ、「内容さえよく知っていれば誰でも教えられる」と思われていることです。

「できる人は実行し、できない人が教える（Those who can't do, teach）」という言葉を聞いたことがあるでしょう。これは、「ある科目の専門知識があれば、その科目を教える専門知識も自動的に備わっている」というよくある誤解を反映しています。

実際には、効果的な学習体験を設計するには、教育理論、認知科学、評価設計に関する深い知識と、長年の実務経験が必要です。これらは、臨床、工学、法律の専門知識と同様に、高度な専門スキルです。だからこそ、『セサミストリート』のカリキュラムは、常に訓練を受けた幼児教育の専門家と緊密に連携して作られてきました。制作者たちは教育効果の高い製品を求めていたため、学習科学に関する深い背景知識を持つ人々に投資したのです。

組織が一見直感的でありながら根拠のない理論を受け入れると、意図せずしてその専門性を損なうことになり、教育のプロフェッショナルは「主題の専門家（SME）やアドバイザー」ではなく、単なる「実行者」になってしまいます。私はこれを直接目にしてきました。教育の専門知識が軽視されると、カリキュラム設計の決定は、学習を実際に改善するものではなく、個人的な好み、逸話、直感によって左右されるようになります。

教育のプロフェッショナルがエビデンスに基づく実践を主張する権限を与えられない場合、学習者の成果は損なわれます。そして、「教育とは研究に基づく学問ではなく、当てずっぽうの作業だ」という信念を強化してしまうことになりかねません。根拠のない理論はリソースを無駄にするだけでなく、教育のプロフェッショナルが訓練された通りの仕事をすること、そしてその仕事の価値を証明することを困難にするのです。

## まとめ：私たちがすべきこと

では、これらを踏まえて私たちはどうすべきでしょうか？

1. **教育上の決定を重く受け止める：** 臨床、政策、運営上の決定と同じ真剣さを持って教育上の決定を扱う必要があります。時間、お金、学習者の労力は常に限られています。「なんとなく良さそうだが根拠がない戦略」を使うことは、学習者、組織、そして社会的信頼に対して現実的な結果をもたらします。
2. **教育の専門家と早めに、頻繁に対話する：** トレーニングプログラムを形成している理論や枠組みは何か、そしてその理由は何かを尋ねてください。多くのインストラクショナル・デザイナーや学習スペシャリストは、学習スタイルのようなポピュラーな疑似科学的アイデアの限界に既に気づいていますが、それに異議を唱える権限や組織的な後ろ盾を持っていない場合があります。既存のトレーニング方法を更新するために組織的な変革が必要な場合は特に、リーダーシップ層のサポートが必要です。
3. **既存のプログラムを批判的な目で監査する：** 根拠のない理論が存続するのは、誰もがそれを積極的に選んだからではなく、カリキュラムがゼロから見直されることなく、受け継がれ、再利用され、修正されてきたからです。価値の低い実践を特定して取り除くことで、実際に学習を改善する戦略に投資するためのリソースを確保できます。
4. **知的誠実さを持つ：** エビデンスに基づく教育とは、流行や完璧さを追い求めることではありません。それは「知的誠実さ」を持つことです。つまり、たとえ馴染みがあり、直感的に魅力的に見えたとしても、エビデンスが支持しない場合はその考えを手放す意思を持つことです。そのマインドセットが学習者を守り、組織を強化し、教育を真の専門分野として確立させるのです。

この議論に興味を持ち、さらに読み進めたい方は、私がこの投稿を書き終えた頃にデビッド・ディダウ（David Didau）が自身の見解を投稿していますので、そちらもご覧ください。デビッドは、K-12（幼稚園から高校まで）の識字教育におけるエビデンスに基づくベストプラクティスについて多くの著作を持つ作家です。

次回のニュースレターでは、もう一つのポップな現象となっている概念――「成人の学習原則（adult learning principles）」――について深掘りし、大人が最もよく学ぶ方法についてエビデンスが実際に何を示しているかを見ていきます。
### Des décennies de recherche ne confirment pas l'existence de styles d'apprentissage.
URL: https://www.kyleslinn.ca/french/des-decennies-de-recherche-ne-confirment-pas-lexistence-de-styles-dapprentissage/
Last updated: 2026-02-10T01:58:59.000Z
*Cet article a été initialement rédigé en anglais et traduit par intelligence artificielle. Les liens vers des sources externes ne sont disponibles que dans les articles en anglais.*

**Préambule :** *Je suis désolé, cet article est un peu long. Les prochains seront plus courts, c'est promis !*

Je suis persuadé que vous avez probablement déjà entendu parler des styles d'apprentissage et de l'hypothèse selon laquelle il existerait une méthode d'apprentissage idéale pour chaque personne. Vous avez peut-être entendu des gens dire « Je suis un apprenant visuel », « J'apprends mieux par la pratique » ou « J'apprends mieux en écoutant ». La théorie des styles d'apprentissage propose que chacun possède une manière unique d'apprendre. Au sein de cette théorie, c'est « l'hypothèse de la correspondance » (ou *meshing hypothesis*) qui suggère que si nous adaptons la conception pédagogique d'une leçon au style d'apprentissage d'un élève, alors celui-ci retiendra mieux la matière.

Par exemple, si un apprenant s'identifie comme visuel et que nous concevons une leçon remplie d'images et de diagrammes, l'hypothèse de la correspondance prédit que cet apprenant comprendra et retiendra mieux la matière que s'il suivait une leçon qui ne correspond pas à sa préférence, comme une leçon basée principalement sur l'audio.

Me croiriez-vous si je vous disais que plus de 70 modèles de styles d'apprentissage ont été conçus au cours des 120 dernières années ? C'est pourtant vrai ! Voici quelques-uns des plus populaires (Coffield et al., 2004 ; Mayer & Fiorella, 2021) :

- Apprenants visuels, auditifs, kinesthésiques ou tactiles (modèle VAK/VARK, par Burke Barbe et réitéré plus tard par Neil Fleming)
- Apprenants convergents, divergents, assimilateurs ou accommodateurs (modèle de David Kolb)
- Apprenants dépendants du champ ou indépendants du champ (modèle de Herman A. Witkin)

On pourrait raisonnablement supposer que, puisque les styles d'apprentissage existent depuis longtemps et qu'il existe tant de modèles différents, l'idée centrale — selon laquelle les gens ont des styles d'apprentissage distincts — doit être soutenue par de solides preuves empiriques. Vous pourriez également supposer que notre confiance en la théorie des styles d'apprentissage devrait être similaire à notre confiance en d'autres principes éducatifs bien établis, comme la théorie de la charge cognitive. Cependant, comme nous allons le voir, ce n'est pas le cas ! Lorsque nous avons mené des tests expérimentaux bien conçus sur la théorie des styles d'apprentissage et l'hypothèse de la correspondance, les résultats ont toujours montré qu'il n'y a pas de différences significatives entre les leçons qui répondent aux différents styles d'apprentissage et celles qui ne le font pas.

## Pashler et al.

L'étude de Pashler et al. (2008) est l'un des articles les plus fréquemment cités explorant la recherche autour des styles d'apprentissage. Les auteurs ont constaté que, bien que les styles d'apprentissage et l'hypothèse de la correspondance aient gagné une popularité significative, très peu d'études présentaient des conceptions suffisamment robustes pour permettre de déterminer de manière fiable si l'hypothèse de la correspondance est soutenue ou non par des preuves empiriques.

Pour remédier à cela, Pashler et al. ont proposé leur propre conception d'étude. Ils ont suggéré qu'un plan factoriel aléatoire (*factorial randomized design*) serait le moyen le plus efficace de confirmer ou de rejeter l'hypothèse de la correspondance. En bref, une expérience factorielle aléatoire est une étude où les participants sont assignés au hasard à différentes combinaisons de deux ou plusieurs variables (par ex., style d'apprentissage × type d'instruction) afin que les chercheurs puissent tester non seulement les effets séparés de chaque variable, mais aussi si les variables interagissent entre elles pour influencer les résultats.

Dans le contexte de la recherche sur les styles d'apprentissage, l'étude doit démontrer une interaction croisée claire, ce qui signifie qu'une méthode pédagogique devrait produire les meilleurs résultats pour un groupe de style d'apprentissage, tandis qu'une méthode différente devrait produire les meilleurs résultats pour un second groupe. Par exemple, les apprenants visuels devraient mieux réussir avec des livres qu'avec des livres audio, tandis que les apprenants auditifs devraient mieux réussir avec des livres audio qu'avec des livres. Sans ce schéma, l'hypothèse de la correspondance n'est pas soutenue.

Après avoir décrit leur proposition de conception d'étude, les auteurs ont passé en revue la littérature existante sur les styles d'apprentissage pour voir lesquelles utilisaient un plan factoriel aléatoire. Presque aucune ne l'avait fait, et parmi les rares qui l'avaient fait, leurs résultats ne soutenaient pas l'hypothèse de la correspondance, ne nous laissant aucune raison de soutenir sa légitimité continue.

## Rogowsky, Calhoun et Tallal

Quelques années plus tard, Rogowsky, Calhoun et Tallal (2015) ont mené une étude empirique conçue pour répondre aux normes méthodologiques décrites par Pashler et al. (2008). Les auteurs se sont concentrés sur les préférences d'apprentissage des mots (auditif et visuel) chez 121 adultes de niveau universitaire. (Oui, il faut admettre que c'est un échantillon assez petit).

1. Premièrement, les chercheurs ont déterminé le style d'apprentissage préféré de chaque participant. Tous les participants ont rempli un questionnaire standardisé en ligne sur les styles d'apprentissage qui les classait selon leur préférence pour apprendre de nouvelles informations : en les écoutant ou en les lisant.
2. Deuxièmement, les chercheurs ont mesuré les capacités réelles de compréhension orale et écrite de chaque participant. Chaque participant a passé deux tests d'aptitude : l'un où il écoutait de courts passages enregistrés et répondait à des questions de compréhension, et un autre où il lisait silencieusement des passages similaires et répondait à des questions de compréhension. Ces tests ont permis aux chercheurs de comparer ce que les participants préféraient avec leur performance réelle dans chaque modalité.
3. Troisièmement, les participants ont été assignés au hasard à l'une des deux conditions pédagogiques. La moitié du groupe a écouté une version livre audio numérique d'un texte documentaire, tandis que l'autre moitié a lu exactement le même matériel. Pour être clair, tous les participants ont reçu le contenu exact, présenté dans un seul des deux formats.
4. Enfin, les chercheurs ont évalué dans quelle mesure les participants avaient appris et retenu la matière. Tout d'abord, immédiatement après la session d'étude, les participants ont répondu à un test de compréhension écrit couvrant le passage. Ensuite, deux semaines plus tard, ils ont refait le même test en ligne sans revoir la matière. Cela a permis aux chercheurs de comparer l'apprentissage immédiat et la mémoire à plus long terme à travers les groupes de styles d'apprentissage et les formats pédagogiques.

Cette étude visait à répondre à deux questions centrales :

1. **Si la préférence de style d'apprentissage était liée à l'aptitude à la compréhension verbale (écoute ou lecture).** Les résultats n'ont montré aucune relation statistiquement significative. Au lieu de cela, les participants qui préféraient apprendre par la lecture ont surpassé ceux qui préféraient l'écoute, tant aux tests d'aptitude à la compréhension orale qu'écrite.
2. **Si l'alignement du format pédagogique avec la préférence de style d'apprentissage améliorait l'apprentissage.** Les résultats ont montré que les résultats d'apprentissage ne s'amélioraient pas lorsque le format pédagogique s'alignait avec la préférence déclarée de l'apprenant.

En résumé, l'étude n'a trouvé aucune preuve soutenant l'hypothèse de la correspondance pour la compréhension verbale. Les auteurs ont conclu que l'aptitude — et non la préférence — est le meilleur prédicteur de la performance, et que s'adapter systématiquement aux préférences auditives peut être contre-productif si cela limite le développement des compétences verbales visuelles.

*Une petite parenthèse : Il y a des similitudes ici avec les conclusions en médecine, où l'âge et les années d'expérience d'un clinicien sont de mauvais prédicteurs des résultats des patients, alors que la performance aux mesures d'aptitude est un prédicteur plus fort (Ericsson et al., 2018, pp. 928–932). Hmm !*

## Une petite sélection d'autres recherches sur les styles d'apprentissage

Bien que je vous aie présenté deux articles ici, beaucoup plus de recherches ont été effectuées sur les styles d'apprentissage. Je tiens à souligner depuis combien de temps nous étudions les styles d'apprentissage avec des résultats douteux (au mieux) et que nous avons donc de très fortes raisons d'être hautement sceptiques à leur égard. Ces études soulignent à quel point nous devrions être convaincus que les résultats des deux études décrites plus tôt ne sont pas uniques.

- **Kampwirith, T., & Bates, M. (1980)** \- Cette revue a révélé que l'adaptation des méthodes d'enseignement aux modalités auditives ou visuelles préférées des enfants n'est largement pas soutenue par la recherche, la plupart des études ne montrant aucun avantage — voire de meilleurs résultats lors de l'enseignement via des modalités non préférées — malgré la croyance répandue parmi les éducateurs.
- **Doyle, W., & Rutherford, B. (1984)** \- Cet article passe en revue la recherche sur l'appariement des styles d'apprentissage et conclut qu'aucune préférence unique de l'apprenant ne dicte l'instruction. Au contraire, la plupart des élèves s'adaptent à divers modes d'enseignement, et les méthodes pédagogiques uniformes sont souvent plus pratiques et efficaces que les approches différenciées.
- **Curry (1990)** \- Cet article soutient que, malgré les affirmations selon lesquelles les styles d'apprentissage peuvent améliorer le curriculum, l'instruction, l'évaluation et l'orientation des élèves, leur application est minée par des définitions floues, des mesures peu fiables et la difficulté d'identifier les caractéristiques pertinentes de l'apprenant.
- **Constantinidou, F., & Baker, S. (2002)** \- Cette étude a révélé que bien que les adultes plus âgés (comparés aux adultes plus jeunes) se souvenaient de moins de mots dans l'ensemble, les deux groupes d'âge apprenaient à des rythmes similaires, et les présentations visuelles ou combinées visuelles-auditives menaient à une meilleure performance mémorielle que la présentation auditive seule.
- **Massa, L. J., & Mayer, R. E. (2006)** \- Cette étude n'a trouvé aucune preuve significative que les apprenants verbaux ou visuels bénéficient davantage d'une instruction multimédia adaptée, suggérant que l'adaptation des écrans d'aide aux styles d'apprentissage individuels n'améliore pas les résultats d'apprentissage.
- **Husmann, P. R., & O’Loughlin, V. D. (2018)** \- Cette étude n'a trouvé aucune relation entre les styles d'apprentissage VARK des étudiants, leurs stratégies d'étude choisies et leur performance au cours d'anatomie, montrant plutôt que des méthodes d'étude spécifiques — et non l'alignement avec le style d'apprentissage — prédisaient de meilleurs résultats.
- **Seddik, M., Attou, Y., & Benaissa, M. (2025)** \- Cette étude a révélé que l'adaptation de l'enseignement de l'anglais aux styles d'apprentissage préférés des étudiants n'améliorait pas la performance en écoute, en expression orale ou en écriture.

La liste continue. Je pense que vous avez compris l'idée.

## Pourquoi les styles d'apprentissage sont-ils toujours si populaires ?

Alors pourquoi l'idée des styles d'apprentissage persiste-t-elle après tout ce temps et toutes ces preuves ? Pashler et al. ont quelques idées :

1. Les gens aiment être classés dans des « types », comme avec les horoscopes et le test Myers-Briggs (MBTI). Ces modèles basés sur des types ont un fort attrait intuitif, mais ne sont pas soutenus par des preuves empiriques.
2. Cela offre une solution simple — à savoir que tout le monde peut réussir si l'instruction correspond à son style d'apprentissage, offrant un message optimiste sur le potentiel d'apprentissage et un cadre facile à suivre pour y parvenir.
3. Cela déplace la responsabilité loin de l'apprenant, rendant plus facile l'attribution d'une mauvaise performance à un enseignement inadéquat plutôt qu'à la capacité intrinsèque d'un individu ou à la quantité d'effort que l'apprenant fournit.
4. Il existe une industrie avec des enjeux financiers liés aux styles d'apprentissage. Des entreprises publient des évaluations de styles d'apprentissage, des guides et des ateliers de développement professionnel basés sur l'idée que les styles d'apprentissage existent, et en tirent des revenus.

J'aimerais ajouter une raison supplémentaire à la liste ci-dessus. Les styles d'apprentissage semblent tout simplement intuitivement vrais. C'est parce que nous entendons parler des styles d'apprentissage tout au long de notre parcours éducatif — par des institutions en qui nous avons confiance, des ateliers de développement professionnel et des programmes de formation — donc quand tout le monde en parle, cela semble juste. La même chose se produit avec la croyance que le sucre rend les enfants hyperactifs ; ce n'est pas le cas, mais on a l'impression que c'est vrai. Les manuels scolaires et la formation des enseignants continuent de répéter le mythe des styles d'apprentissage, et des matériels obsolètes le transmettent à chaque nouvelle génération d'éducateurs. Je peux attester qu'on m'a enseigné les styles d'apprentissage pendant ma maîtrise en éducation, et cela a été présenté comme une théorie fondée sur des preuves.

Si vous êtes comme moi, vous pourriez trouver que la persistance de ce mythe (et d'autres comme lui) est vraiment très frustrante. J'ai l'impression que Mayer et Fiorella (2021) capturent vraiment mes sentiments sur toute cette situation :

> « En effet, on pourrait suggérer que la croyance continue en l'utilité des styles d'apprentissage par les éducateurs, malgré des décennies de preuves contraires, est un indicateur inquiétant du manque de pratique fondée sur des preuves dans l'éducation et dans les programmes universitaires de formation des enseignants. »

Et c'est en partie pourquoi j'ai décidé de lancer un bulletin d'information.

## Les apprenants restent des individus uniques

Bien que la théorie des styles d'apprentissage ne repose sur rien, je veux être clair sur le fait que chaque apprenant est unique. Ils ont des antécédents, des expériences et des capacités de mémoire de travail différents. Certains apprenants peuvent également nécessiter des aménagements pour des handicaps sensoriels ou une neurodivergence. Mais malgré ces différences, les mécanismes cognitifs sous-jacents impliqués dans l'apprentissage sont largement les mêmes chez les humains. Il n'y a aucune bonne raison de croire que le fait d'adhérer aux préférences d'apprentissage de quelqu'un améliorera les résultats d'apprentissage.

## Les apprenants ne peuvent pas choisir de manière fiable les meilleures expériences pédagogiques pour eux-mêmes

En fait, Clark (1982) montre que lorsque les apprenants ont la possibilité de choisir parmi une variété d'expériences pédagogiques, ils choisissent souvent l'expérience qui leur est la moins bénéfique. Il a constaté que les élèves ayant un niveau académique élevé avaient tendance à apprendre davantage avec une instruction moins structurée et ouverte qui exigeait qu'ils planifient, organisent et utilisent leurs propres stratégies d'apprentissage. Mais ces élèves très performants avaient tendance à préférer des leçons très structurées avec beaucoup d'encadrement de la part de l'instructeur, peut-être parce qu'ils étaient plus familiers avec ces types de leçons et sentaient qu'une instruction familière exigerait moins d'effort de leur part. À l'inverse, les élèves en difficulté étaient à l'opposé. Ils apprenaient davantage avec les leçons plus structurées, mais préféraient les leçons moins structurées, possiblement parce qu'ils sentaient qu'elles attiraient moins l'attention sur eux-mêmes et sur leur performance académique dans des environnements moins structurés.

En résumé, les conclusions de Clark suggèrent que les élèves veulent les meilleurs résultats pour le moins d'effort et qu'ils jugent systématiquement mal l'effort impliqué dans les leçons vers lesquelles ils gravitent. Et l'une des règles d'or de l'apprentissage est que vous devez fournir un effort cognitif pour apprendre quelque chose. Plus vous fournissez d'efforts, meilleurs sont vos résultats d'apprentissage.

## Applications pour les instructeurs en soins de santé

Pour conclure, voici quelques conseils pratiques que je suggère :

- Soyez vigilant lorsque vous entendez des gens discuter des styles d'apprentissage ou des préférences d'un apprenant, surtout lorsqu'ils proposent d'aligner l'instruction pour correspondre aux préférences d'un apprenant.
- Ne laissez pas les apprenants choisir leur propre matériel éducatif. Cela inclut le fait de leur dire de chercher sur YouTube ou un autre moteur de recherche pour une leçon. Les étudiants graviteront vers le contenu qu'ils perçoivent comme nécessitant moins d'effort cognitif. En tant qu'instructeur, vous devez décider quelles ressources d'apprentissage conviennent à vos étudiants.

## À venir...

Maintenant, après tout cela, vous pourriez penser : est-ce que tout cela a de l'importance ? Quel mal y a-t-il à laisser les gens croire que les styles d'apprentissage existent ? Quelques-uns de mes amis et collègues m'ont posé cette question récemment. J'approfondirai ce sujet la prochaine fois !

## Références

1. Mayer, R. E., & Fiorella, L. (Eds.). (2021). *The Cambridge Handbook of Multimedia Learning* (3rd ed.). Cambridge University Press. [https://doi.org/10.1017/9781108894333](https://doi.org/10.1017/9781108894333?ref=kyleslinn.ca)
2. Clark, R. E. (1982). Antagonism Between Achievement and Enjoyment in ATI Studies. *Educational Psychologist*, *17*(2), 92–101\. [https://doi.org/10.1080/00461528209529247](https://doi.org/10.1080/00461528209529247?ref=kyleslinn.ca)
3. Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence. *Psychological Science in the Public Interest: A Journal of the American Psychological Society*, *9*(3), 105–119\. [https://doi.org/10.1111/j.1539-6053.2009.01038.x](https://doi.org/10.1111/j.1539-6053.2009.01038.x?ref=kyleslinn.ca)
4. Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2015). Matching learning style to instructional method: Effects on comprehension. *Journal of Educational Psychology*, *107*, 64–78\. [https://doi.org/10.1037/a0037478](https://doi.org/10.1037/a0037478?ref=kyleslinn.ca)
5. Kampwirth, T. J., & Bates, M. (1980). Modality Preference and Teaching Method: A Review of the Research. *Academic Therapy*. [https://doi.org/10.1177/105345128001500509](https://doi.org/10.1177/105345128001500509?ref=kyleslinn.ca)
6. Doyle, W., & Rutherford, B. (1984). Classroom research on matching learning and teaching styles. *Theory Into Practice, 23*(1), 20–25\. [https://doi.org/10.1080/00405848409543085](https://psycnet.apa.org/doi/10.1080/00405848409543085?ref=kyleslinn.ca)
7. Curry, L. (1990). A Critique of the Research on Learning Styles. *Educational Leadership*, *48*(2).
8. Constantinidou, F., & Baker, S. (2002). Stimulus modality and verbal learning performance in normal aging. *Brain and Language*, *82*(3), 296–311\. [https://doi.org/10.1016/S0093-934X(02)00018-4](https://doi.org/10.1016/S0093-934X%2802%2900018-4?ref=kyleslinn.ca)
9. Massa, L. J., & Mayer, R. E. (2006). Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style? *Learning and Individual Differences*, *16*(4), 321–335\. [https://doi.org/10.1016/j.lindif.2006.10.001](https://doi.org/10.1016/j.lindif.2006.10.001?ref=kyleslinn.ca)
10. Husmann, P. R., & O’Loughlin, V. D. (2019). Another Nail in the Coffin for Learning Styles? Disparities among Undergraduate Anatomy Students’ Study Strategies, Class Performance, and Reported VARK Learning Styles. *Anatomical Sciences Education*, *12*(1), 6–19\. [https://doi.org/10.1002/ase.1777](https://doi.org/10.1002/ase.1777?ref=kyleslinn.ca)
11. Seddik, M., Attou, Y., & Benaissa, M. (n.d.). The meshing hypothesis revisited: A quasi-experimental study of the impact of tailoring English instruction to learning styles on academic performance. *Pedagogies: An International Journal*, *0*(0), 1–18\. [https://doi.org/10.1080/1554480X.2025.2564357](https://doi.org/10.1080/1554480X.2025.2564357?ref=kyleslinn.ca)
12. Ericsson, K. A., Hoffman, R. R., Kozbelt, A., & Williams, A. M. (Eds.). (2018). *The Cambridge Handbook of Expertise and Expert Performance* (2nd ed.). Cambridge University Press. [https://doi.org/10.1017/9781316480748](https://doi.org/10.1017/9781316480748?ref=kyleslinn.ca)
### 「学習スタイル」を裏付ける証拠なし：数十年にわたる研究の結論
URL: https://www.kyleslinn.ca/japanese/xue-xi-sutairu-woli-fu-keruzheng-ju-nasi-shu-shi-nian-niwataruyan-jiu-nojie-lun/
Last updated: 2026-02-11T16:10:16.000Z
この記事は元々英語で書かれ、人工知能を用いて翻訳されました。外部ソースへのリンクは、記事の英語版でのみ利用可能です。

**前置き：** *すみません、今回の記事は少し長くなります。次回からはもっと短くすると約束します！*

おそらく皆さんも「学習スタイル」について、そして「人それぞれに最適な学習方法が一つある」という前提について聞いたことがあるでしょう。「私は視覚的学習者（ビジュアルラーナー）だ」「やってみるのが一番覚えられる」「聞いて覚えるのが得意だ」といった言葉を耳にしたことがあるかもしれません。学習スタイル理論は、誰もが独自の学習方法を持っていると提唱しています。この理論の中で、「適合仮説（meshing hypothesis）」と呼ばれるものが、授業の構成（インストラクショナルデザイン）を生徒の学習スタイルに合わせれば、学習者は内容をより良く定着できると示唆しています。

例えば、ある学習者が「視覚的学習者」であると認識している場合、適合仮説に基づけば、画像や図表をふんだんに使った授業を行えば、その人の好みに合わない授業（例えば、主に音声に基づく授業）を行うよりも、内容を理解し記憶に留めやすくなると予測されます。

過去120年の間に、70以上の学習スタイルモデルが考案されてきたと言ったら、信じられますか？本当なんです！ここでは、その中でも特に有名なものをいくつか紹介します（Coffield et al., 2004; Mayer & Fiorella, 2021）：

- **VAK/VARKモデル**：視覚（Visual）、聴覚（Auditory）、運動感覚（Kinesthetic）、触覚（Tactile）の学習者（Burke Barbeによって提唱され、後にNeil Flemingによって改良）。
- **コルブのモデル**：収束型、発散型、同化型、調節型の学習者（David Kolb）。
- **ウィトキンのモデル**：場依存型、または場独立型の学習者（Herman A. Witkin）。

さて、学習スタイルは昔から存在し、これほど多くの異なるモデルがあるのだから、その核心となるアイデア――人々には明確な学習スタイルがある――は、強力な実証的証拠によって裏付けられているに違いないと考えるのはもっともです。また、学習スタイル理論に対する信頼度は、認知負荷理論のような他の確立された教育原則に対する信頼度と同じくらいであるべきだと考えるかもしれません。しかし、これから見ていくように、実際はそうではないのです！学習スタイル理論と適合仮説について、適切に設計された実験的テストを行うと、異なる学習スタイルに対応した授業とそうでない授業との間に、有意な差はないという結果が繰り返し出ています。

## パシュラーら（Pashler et al.）の研究

パシュラーら（2008）の論文は、学習スタイルに関する研究を調査したもので、最も頻繁に引用されるものの一つです。著者らは、学習スタイルと適合仮説が大きな人気を博している一方で、適合仮説が実証的証拠によって支持されているか否かを確実に判断できるほど堅牢な設計の研究は、ごくわずかしかないことを発見しました。

そこでパシュラーらは、独自の実験デザインを提案しました。彼らは、「要因配置ランダム化デザイン（factorial randomized design）」こそが、適合仮説を肯定または否定する最も効果的な方法であると示唆しました。簡単に言えば、要因配置ランダム化実験とは、参加者を2つ以上の変数の組み合わせ（例：学習スタイル × 指導タイプ）にランダムに割り当て、各変数の単独の効果だけでなく、変数同士が相互作用して結果に影響を与えるかどうかをテストできる研究のことです。

学習スタイル研究の文脈では、この研究は明確な「交差相互作用（crossover interaction）」を示す必要があります。つまり、ある指導法がある学習スタイルグループに最良の結果をもたらし、別の指導法が別の学習スタイルグループに最良の結果をもたらす、ということです。例えば、視覚的学習者はオーディオブックよりも本で学習した方が成績が良く、聴覚的学習者は本よりもオーディオブックで学習した方が成績が良い、となるはずです。このパターンがなければ、適合仮説は支持されません。

著者らは提案した実験デザインを説明した後、既存の学習スタイルに関する文献をレビューし、この要因配置ランダム化デザインを使用しているものがあるかを確認しました。その結果、使用しているものはほとんどなく、使用していた数少ない研究の結果も適合仮説を支持しておらず、その正当性を支持し続ける理由は見当たりませんでした。

## ロゴウスキー、カルフーン、タラル（Rogowsky, Calhoun, and Tallal）の研究

数年後、ロゴウスキー、カルフーン、タラル（2015）は、パシュラーら（2008）が概説した方法論的基準を満たすように設計された実証研究を実施しました。著者らは、大学教育を受けた成人121名を対象に、聴覚的および視覚的な単語学習の好みに焦点を当てました。（確かに、これはかなり小さなサンプルサイズであることは認めます。）

1. まず、研究者は各参加者の好む学習スタイルを決定しました。全参加者が標準化されたオンラインの学習スタイル質問票に回答し、新しい情報を「聞くこと」で学ぶのを好むか、「読むこと」で学ぶのを好むかに分類されました。
2. 次に、研究者は各参加者の実際の「聴解力」と「読解力」を測定しました。すべての参加者が2つの能力テストを受けました。1つは短い録音を聞いて理解度を問う質問に答えるもの、もう1つは同様の文章を黙読して質問に答えるものです。これにより、研究者は参加者の「好み」と、各モダリティ（様式）での実際の「パフォーマンス」を比較することができました。
3. 第三に、参加者はランダムに2つの指導条件のいずれかに割り当てられました。グループの半分はノンフィクションのテキストのデジタルオーディオブック版を聞き、もう半分は全く同じ資料を読みました。念のために言っておくと、すべての参加者は全く同じ内容を、2つの形式のうちの1つだけで受け取りました。
4. 最後に、研究者は参加者がどれだけ学習し、内容を記憶しているかを評価しました。まず、学習セッション終了直後に、その文章に関する記述式の理解度テストに回答しました。そして2週間後、資料を見直すことなく、オンラインで同じテストを再度受けました。これにより、研究者は学習スタイルグループと指導形式の両方において、即時の学習と長期的な記憶を比較することができました。

この研究は、以下の2つの中心的な問いに答えることを目的としていました。

- **学習スタイルの好みが、聴くことや読むことの言語理解適性（能力）と関連しているかどうか。** 結果は、統計的に有意な関係を示しませんでした。むしろ、「読むこと」による学習を好む参加者は、「聞くこと」を好む人々に比べて、聴解力と読解力の両方の適性テストで優れた成績を収めました。
- **指導形式を学習スタイルの好みに合わせることで学習が改善するかどうか。** 結果は、指導形式が学習者の表明した好みに一致しても、学習成果は向上しないことを示しました。

要約すると、この研究は言語理解における適合仮説を支持する証拠を見つけられませんでした。著者らは、「好み」ではなく「適性（能力）」こそがパフォーマンスのより強力な予測因子であり、聴覚的な好みに日常的に合わせることは、視覚的な単語スキルの発達を制限する場合、逆効果になる可能性があると結論付けました。

*ちょっと脱線：これは医学における知見といくつかの類似点があります。臨床医の年齢や経験年数は患者の予後の予測因子としては乏しく、一方で適性測定のパフォーマンスの方がより強力な予測因子であるというものです（Ericsson et al., 2018, pp. 928–932）。ふむ！*

## 学習スタイルに関するその他の研究セレクション

ここでは2つの論文を紹介しましたが、学習スタイルについてはもっと多くの研究が行われています。私が強調したいのは、私たちがどれほど長い間、疑わしい（良く言っても）結果しか出ていない学習スタイルを研究してきたかということであり、したがって、学習スタイルに対して非常に懐疑的になる強い根拠があるということです。以下の研究は、先に述べた2つの研究の結果が決して特異なものではないと確信させてくれるものです。

- **Kampwirith, T., & Bates, M. (1980)** \- このレビューでは、指導法を子供の好む聴覚的または視覚的モダリティに合わせることは、研究によってほとんど支持されていないことがわかりました。教育者の間で広く信じられているにもかかわらず、多くの研究は利点がないこと、あるいは好まないモダリティで教える方が良い結果が出ることさえ示しています。
- **Doyle, W., & Rutherford, B. (1984)** \- この論文は、学習スタイルのマッチングに関する研究をレビューし、単一の学習者の好みが指導を決定することはないと結論付けています。むしろ、ほとんどの学生は多様な教育モードに適応し、画一的な指導法の方が、差別化されたアプローチよりも実用的で効果的であることが多いとしています。
- **Curry (1990)** \- この論文は、学習スタイルがカリキュラム、指導、評価、および学生指導を改善できるという主張にもかかわらず、その適用は不明確な定義、信頼性の低い測定、および関連する学習者の特性を特定することの難しさによって損なわれていると論じています。
- **Constantinidou, F., & Baker, S. (2002)** \- この研究では、高齢者は（若年成人と比較して）全体的に想起できる単語数が少なかったものの、両方の年齢層が同様の速度で学習し、視覚のみ、または視覚と聴覚を組み合わせた提示の方が、聴覚のみの提示よりも記憶パフォーマンスが良いことがわかりました。
- **Massa, L. J., & Mayer, R. E. (2006)** \- この研究では、言語的または視覚的学習者が、自分に合ったマルチメディア指導からより多くの恩恵を受けるという意味のある証拠は見つかりませんでした。これは、ヘルプ画面を個々の学習スタイルに合わせて調整しても、学習成果は向上しないことを示唆しています。
- **Husmann, P. R., & O’Loughlin, V. D. (2018)** \- この研究では、学生のVARK学習スタイル、彼らが選択した学習戦略、および解剖学コースの成績の間に関係は見られませんでした。代わりに、学習スタイルの適合ではなく、特定の学習方法がより良い結果を予測することを示しました。
- **Seddik, M., Attou, Y., & Benaissa, M. (2025)** \- この研究では、英語の指導を学生の好む学習スタイルに合わせても、リスニング、スピーキング、ライティングのパフォーマンスは向上しないことがわかりました。

リストはまだまだ続きますが、全体像はお分かりいただけると思います。

## なぜ学習スタイルは今なお人気なのか？

これほどの時間と証拠がありながら、なぜ学習スタイルのアイデアは存続しているのでしょうか？パシュラーらはいくつかの考えを持っています。

1. **カテゴリー化への欲求：** 人々は星座占いやマイヤーズ・ブリッグス・タイプ指標（MBTI）テストのように、「タイプ」に分類されることを好みます。これらのタイプに基づくモデルは、直感的に強く訴えかけるものがありますが、実証的証拠には支えられていません。
2. **シンプルな解決策：** 指導を学習スタイルに合わせれば誰もが成功できるという、学習の可能性に関する楽観的なメッセージと、それを達成するための簡単な枠組みを提供してくれます。
3. **責任の転嫁：** パフォーマンスの低さを、個人の本質的な能力や学習時の努力量ではなく、不適切な教育のせいにしやすくし、学習者から責任を遠ざけます。
4. **ビジネス的利害：** 学習スタイルには金融的な利害関係を持つ産業が存在します。企業は、学習スタイルが存在するという考えに基づいて、評価ツール、ガイドブック、専門能力開発ワークショップを出版・開催し、収益を上げています。

上記のリストにもう一つ理由を加えたいと思います。「学習スタイルは直感的に正しく感じられる」ということです。私たちは教育システム全体（信頼する機関、専門能力開発ワークショップ、トレーニングプログラムなど）を通じて学習スタイルについて耳にするため、誰もがそれについて話していると、それが正しいことのように感じられます。「砂糖が子供を多動にする」という迷信と同じことが起きています（実際はそうなりませんが、そうであるかのように感じられます）。教科書や教員教育は学習スタイルの神話を繰り返し続け、時代遅れの教材がそれを新しい世代の教育者に伝えています。私自身、教育学修士課程で学習スタイルについて教わりましたが、それは証拠に基づく理論として枠組みされていました。

もしあなたが私と同じように感じているなら、この神話（そしてこれに類する他の神話）のしぶとさに、かなりフラストレーションを感じているかもしれません。MayerとFiorella（2021）の言葉は、この状況全体に対する私の気持ちを実によく捉えています。

> 「実際、数十年にわたる反対の証拠があるにもかかわらず、教育者たちが学習スタイルの有用性を信じ続けていることは、教育および大学における教員養成プログラムにおいて、証拠に基づく実践（エビデンスベースド・プラクティス）がいかに欠如しているかを示す、嘆かわしい指標であると言えるかもしれない。」

これが、私がこのニュースレターを始めようと決めた理由の一部でもあります。

## それでも学習者はユニークな個人である

学習スタイル理論には拠り所となる根拠がありませんが、すべての学習者がユニークであることは明確にしておきたいと思います。彼らは異なる背景、経験、ワーキングメモリ（作業記憶）の容量を持っています。一部の学習者は、感覚障害やニューロダイバーシティ（神経学的多様性）のために配慮が必要な場合もあります。しかし、こうした違いはあるものの、学習に関わる基本的な認知メカニズムは、人間全体で概ね同じです。誰かの学習の好みに固執することが学習成果を向上させないと信じる正当な理由はありません。

## 学習者は自分にとって最適な学習体験を確実に選べるわけではない

実際、Clark（1982）は、学習者に様々な学習体験から選ぶ機会を与えると、彼らはしばしば自分にとって最も利益の少ない体験を選んでしまうことを示しています。彼は、高い学力を持つ学生は、自分で計画し、整理し、独自の学習戦略を使用する必要がある、構造化されていないオープンエンドな指導からより多くを学ぶ傾向があることを発見しました。しかし、これらの成績優秀な学生は、おそらくそのような授業に慣れており、親しみのある指導の方が自分の努力が少なくて済むと感じたためか、講師による手厚いサポートがある非常に構造化された授業を好む傾向がありました。逆に、成績の低い学生はその反対でした。彼らはより構造化された授業から多くを学びましたが、構造化されていない授業を好みました。これはおそらく、構造化されていない環境の方が、自分自身や学業成績に注目が集まりにくいと感じたためでしょう。

要約すると、クラークの発見は、学生は「最小の努力で最大の結果」を求めており、自分が惹かれる授業に伴う努力量を日常的に見誤っていることを示唆しています。そして、学習の黄金律の一つは、「何かを学ぶには認知的努力を費やす必要がある」ということです。努力すればするほど、学習成果は良くなります。

## 医療インストラクターへの応用

これらをまとめると、私が提案する実践的な重要ポイントは以下の通りです。

- 人々が学習スタイルや学習者の好みについて議論しているとき、特に「学習者の好みに合わせて指導を調整する」ことを提案しているときは、警戒してください。
- 学習者に自分の教材を選ばせないでください。これには、YouTubeや他の検索エンジンでレッスンを探すように指示することも含まれます。学生は、認知的努力が少なくて済むと感じるコンテンツに引き寄せられます。インストラクターとして、学生に適した学習リソースを決めるのはあなたの役割です。

## 次回予告...

さて、ここまで読んで、「これってそんなに重要なの？人々が学習スタイルが存在すると信じたままでいることに、どんな害があるの？」と思っているかもしれません。最近、友人や同僚数人からも同じことを聞かれました。次回は、この点についてさらに深く掘り下げていきます！

## 参考文献

1. Mayer, R. E., & Fiorella, L. (Eds.). (2021). *The Cambridge Handbook of Multimedia Learning* (3rd ed.). Cambridge University Press. [https://doi.org/10.1017/9781108894333](https://doi.org/10.1017/9781108894333?ref=kyleslinn.ca)
2. Clark, R. E. (1982). Antagonism Between Achievement and Enjoyment in ATI Studies. *Educational Psychologist*, *17*(2), 92–101\. [https://doi.org/10.1080/00461528209529247](https://doi.org/10.1080/00461528209529247?ref=kyleslinn.ca)
3. Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence. *Psychological Science in the Public Interest: A Journal of the American Psychological Society*, *9*(3), 105–119\. [https://doi.org/10.1111/j.1539-6053.2009.01038.x](https://doi.org/10.1111/j.1539-6053.2009.01038.x?ref=kyleslinn.ca)
4. Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2015). Matching learning style to instructional method: Effects on comprehension. *Journal of Educational Psychology*, *107*, 64–78\. [https://doi.org/10.1037/a0037478](https://doi.org/10.1037/a0037478?ref=kyleslinn.ca)
5. Kampwirth, T. J., & Bates, M. (1980). Modality Preference and Teaching Method: A Review of the Research. *Academic Therapy*. [https://doi.org/10.1177/105345128001500509](https://doi.org/10.1177/105345128001500509?ref=kyleslinn.ca)
6. Doyle, W., & Rutherford, B. (1984). Classroom research on matching learning and teaching styles. *Theory Into Practice, 23*(1), 20–25\. [https://doi.org/10.1080/00405848409543085](https://psycnet.apa.org/doi/10.1080/00405848409543085?ref=kyleslinn.ca)
7. Curry, L. (1990). A Critique of the Research on Learning Styles. *Educational Leadership*, *48*(2).
8. Constantinidou, F., & Baker, S. (2002). Stimulus modality and verbal learning performance in normal aging. *Brain and Language*, *82*(3), 296–311\. [https://doi.org/10.1016/S0093-934X(02)00018-4](https://doi.org/10.1016/S0093-934X%2802%2900018-4?ref=kyleslinn.ca)
9. Massa, L. J., & Mayer, R. E. (2006). Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style? *Learning and Individual Differences*, *16*(4), 321–335\. [https://doi.org/10.1016/j.lindif.2006.10.001](https://doi.org/10.1016/j.lindif.2006.10.001?ref=kyleslinn.ca)
10. Husmann, P. R., & O’Loughlin, V. D. (2019). Another Nail in the Coffin for Learning Styles? Disparities among Undergraduate Anatomy Students’ Study Strategies, Class Performance, and Reported VARK Learning Styles. *Anatomical Sciences Education*, *12*(1), 6–19\. [https://doi.org/10.1002/ase.1777](https://doi.org/10.1002/ase.1777?ref=kyleslinn.ca)
11. Seddik, M., Attou, Y., & Benaissa, M. (n.d.). The meshing hypothesis revisited: A quasi-experimental study of the impact of tailoring English instruction to learning styles on academic performance. *Pedagogies: An International Journal*, *0*(0), 1–18\. [https://doi.org/10.1080/1554480X.2025.2564357](https://doi.org/10.1080/1554480X.2025.2564357?ref=kyleslinn.ca)
12. Ericsson, K. A., Hoffman, R. R., Kozbelt, A., & Williams, A. M. (Eds.). (2018). *The Cambridge Handbook of Expertise and Expert Performance* (2nd ed.). Cambridge University Press. [https://doi.org/10.1017/9781316480748](https://doi.org/10.1017/9781316480748?ref=kyleslinn.ca)
### Decades of Research Find No Support for Learning Styles
URL: https://www.kyleslinn.ca/decades-of-research-find-no-support/
Last updated: 2026-02-08T07:26:11.000Z
*Preamble: I’m sorry, this post is a bit long. Future posts will be shorter, I promise!*

I’m confident you’ve probably heard of learning styles and the assumption that there is one best way for each person to learn. You might have heard people say “I’m a visual learner,” or “I learn best by doing,” or “I learn best by listening.” *Learning styles theory* proposes that everyone has a unique way in which they learn. Within learning styles theory, it’s the *meshing hypothesis* that suggests that if we match the instructional design of a lesson to a student’s learning style, then the learner will retain the material better.

So for example, if a learner identifies as a visual learner, and we design a lesson filled with images and diagrams, the meshing hypothesis predicts this learner will understand and retain the material better than if they were given a lesson that does not align with their preference, such as one based mainly on audio.

Would you believe it if I told you there have been more than 70 models of learning styles conceived over the last 120 years? It’s true! Here’s just a few of the more popular ones (Coffield et al., 2004; Mayer & Fiorella, 2021):

- Visual, auditory, kinesthetic or tactile learners (VAK/VARK model, by Burke Barbe and later iterated on by Neil Fleming)
- Convergent, divergent, assimilating, or accommodating learners (David Kolb’s model)
- Field dependent or field independent learners (Herman A. Witkin’s model)

Now, you might reasonably assume that because learning styles have been around for a long time, and because so many different models exist, the core idea—that people have distinct learning styles—must be supported by strong empirical evidence. You may also assume that our confidence in learning styles theory should be similar to our confidence in other well-established educational principles, like cognitive load theory. However, as we’ll see, this is not the case! When we’ve run well-designed experimental tests on learning styles theory and the meshing hypothesis, the results keep coming back showing that there are **no significant differences** between lessons that cater to different learning styles and those that don’t.

## Pashler et al.

Pashler et al. (2008) is one of the most frequently cited papers that explores the research around learning styles. The authors found that while learning styles and the meshing hypothesis have gained significant popularity, very few studies have sufficiently robust study designs that would allow them to reliably determine if the meshing hypothesis is supported or unsupported by empirical evidence.

So to address this, Pashler et al. proposed their own study design. They suggested a factorial randomized design would be the most effective way to confirm or reject the meshing hypothesis. In short, a factorial randomized experiment is a study where participants are randomly assigned to different combinations of two or more variables (e.g., learning style × type of instruction) so researchers can test not only the separate effects of each variable but also whether the variables interact with each other to influence outcomes.

![](https://www.kyleslinn.ca/content/images/2026/02/f2bf4e37-7993-4968-b125-8e7120ac912b_2054x1226.png)

In the context of learning styles research, the study must demonstrate a clear crossover interaction, meaning one instructional method should produce the best outcomes for one learning style group, while a different method should produce the best outcomes for a second learning style group. For example, visual learners should perform better with books than audiobooks, while auditory learners should perform better with audiobooks than books. Without this pattern, the meshing hypothesis is not supported.

After describing their proposed study design, the authors then reviewed the body of existing learning styles literature to see which ones used a factorial randomized design. Almost none of them did, and of the few that did use the design, **their results did not support the meshing hypothesis**, leaving us no reason to support its ongoing legitimacy.

## Rogowsky, Calhoun, and Tallal

![](https://www.kyleslinn.ca/content/images/2026/02/b504f416-d053-4cc7-9340-f1fb55d92a49_2017x660.png)

A few years later, Rogowsky, Calhoun, and Tallal (2015) conducted an empirical study designed to meet the methodological standards outlined by Pashler et al. (2008). The authors focused on auditory and visual word-learning preferences in 121 college-educated adults. (Yes, admittedly this is quite a small sample size.)

First, the researchers determined each participant’s preferred learning style. All participants completed a standardized online learning-style questionnaire that classified them as either preferring to learn new information by listening to it or reading it.

Second, the researchers measured each participant’s actual listening and reading comprehension abilities. Every participant completed two ability tests: one where they listened to short recorded passages and answered comprehension questions, and another where they silently read similar passages and answered comprehension questions. These tests allowed the researchers to compare what participants preferred with how they actually performed in each modality.

Third, the participants were randomly assigned to one of two instructional conditions. Half of the group listened to a digital audiobook version of a nonfiction text, while the other half read the exact same material. To be clear, all participants received *the exact same content*, presented in just one of the two formats.

Finally, the researchers assessed how well participants learned and retained the material. First, immediately after completing the study session, the participants answered a written comprehension test covering the passage. Then, two weeks later, they completed the same test again online without reviewing the material. This allowed the researchers to compare immediate learning and longer-term memory across both learning-style groups and instructional formats.

This study set out to answer two central questions:

1. **Whether learning-style preference was related to verbal comprehension aptitude in listening or reading.** The results showed *no statistically significant relationship*. Instead, participants who preferred learning through reading outperformed people who preferred listening, on *both* listening and reading comprehension aptitude tests.
2. **Whether matching instructional format to learning-style preference improved learning.** The results showed *learning outcomes didn’t improve* when instructional format aligned with a learner’s stated preference.

In summary, the study found no evidence supporting the meshing hypothesis for verbal comprehension. The authors concluded that aptitude—not preference—is the stronger predictor of performance, and that routinely accommodating auditory preferences may be counterproductive if it limits the development of visual word skills.

A quick tangent: There are some similarities here with findings in medicine, where a clinician’s age and years of experience are poor predictors of patient outcomes, while performance on aptitude measures is a stronger predictor (Ericsson et al., 2018, pp. 928–932). Hrm!

## A small selection of other research on learning styles

While I’ve introduced you to two papers here, there has been much moremresearch done on learning styles. I want to emphasize how long we’ve been studying learning styles with shaky results (at best) and therefore have very strong grounds to be highly skeptical of learning styles. These studies highlight how confident we should be that the results of the two studies I described earlier are not unique.

- *Kampwirith, T., & Bates, M. (1980)* \- This review found that matching teaching methods to children’s preferred auditory or visual modalities is largely unsupported by research, with most studies showing no benefit—or even better outcomes when teaching non-preferred modalities—despite widespread belief among educators.
- *Doyle, W., & Rutherford, B. (1984)* \- This article reviews research on learning-style matching and concludes that no single learner preference dictates instruction. Rather, most students adapt to various teaching modes, and uniform instructional methods are often more practical and effective than differentiated approaches.
- *Curry (1990)* \- This article argues that despite claims that learning styles can improve curriculum, instruction, assessment, and student guidance, their application is undermined by unclear definitions, unreliable measurement, and difficulty identifying relevant learner characteristics.
- *Constantinidou, F., & Baker, S. (2002)* \- This study found that while older adults (when compared with younger adults) recalled fewer words overall, both age groups learned at similar rates, and visual or combined visual-auditory presentations led to better memory performance than auditory presentation alone.
- *Massa, L. J., & Mayer, R. E. (2006)* \- This study found no meaningful evidence that verbal or visual learners benefit more from matched multimedia instruction, suggesting that tailoring help-screens to individual learning styles does not improve learning outcomes.
- *Husmann, P. R., & O’Loughlin, V. D. (2018)* \- This study found no relationship between students’ VARK learning styles, their chosen study strategies, and anatomy course performance, showing instead that specific study methods—not learning-style alignment—predicted better outcomes.
- *Seddik, M., Attou, Y., & Benaissa, M. (2025)* \- This study found that tailoring English instruction to students’ preferred learning styles did not improve performance in listening, speaking, or writing.

The list goes on. I think you get the picture.

## Why are learning styles still so popular?

![](https://www.kyleslinn.ca/content/images/2026/02/631b2afe-3fc2-4468-8123-10f153a9eae1_2017x660.png)

So why does the idea of learning styles persist after all this time and all this evidence? Pashler et al. have some ideas:

- **People like being categorized into “types”**, and type-based models, such as horoscopes and the Myers–Briggs Type Indicator test. These type-based models have strong intuitive appeal, but are not supported by empirical evidence.
- **It offers a simple solution** \-namely, that everyone can succeed if the instruction is matched to their learning style, offering an optimistic message about learning potential, and an easy framework to follow to achieve that.
- **It shifts responsibility away from the learner**, making it easier to attribute poor performance to inadequate teaching rather than an individual’s intrinsic ability or the amount of effort the learner applies when learning.
- **There is industry with financial stakes in learning styles.** Companies publish learning style assessments, guidebooks, and professional development workshops based on the idea that learning styles do exist, and make revenue from them.

I would like to add one more reason to the list above. Learning styles just **feel intuitively true.** This is because we hear about learning styles throughout our education systems—from institutions we trust, professional development workshops, and training programs—so when everyone is talking about it, it feels right. The same thing happens with the belief that sugar makes children hyperactive; it doesn’t, but it *feels* like it does. Textbooks and teacher education continue to repeat the learning styles myth, and outdated materials pass it to each new generation of educators. I can attest that I was taught about learning styles during my Master of Education degree, and it was framed as an evidence-based theory.

If you’re like me, you might feel like the persistence of this myth (and others like it) is really quite frustrating. I feel like Mayer and Fiorella (2021) really capture my feelings about this whole situation:

> “Indeed, it might be suggested that the continuing belief in the utility of learning styles by educators, despite decades of contrary evidence, is a distressing indicator of the lack of evidence-based practice in education and in university-based teacher education programs.”

And this is partly why I decided to start a newsletter.

## Learners are still unique individuals

While learning styles theory has no ground to stand on, I want to be clear that every learner is unique. They have different backgrounds, experiences, and working memory capacities. Some learners may also require accommodations for sensory disabilities or neurodivergence. But despite these differences, the underlying cognitive mechanisms involved in learning are largely the same across humans. There is no good reason to believe that adhering to someone’s learning preferences will not improve learning outcomes.

## Learners can’t reliably pick the best instructional experiences for themselves

In fact, Clark (1982) shows that when learners are given the opportunity to pick from a variety of instructional experiences, they often pick the experience that is *least* *beneficial* to them. He found students with high academic ability tended to learn more from less structured, open-ended instruction that required them to plan, organize, and use their own learning strategies. But these high achieving students tended to prefer very structured lessons with lots of hand-holding by the instructor, perhaps because they were more familiar with these types of lessons and felt familiar instruction would require less effort on their part. Conversely, low achieving students were the opposite. They learned more from the more structured lessons, but preferred the less structured lessons, possibly because they felt they drew less attention to themselves and their academic performance in less structured environments.

In summary, Clark’s findings suggest students want the best results for the least effort and they routinely misjudge the effort involved in the lessons they gravitate toward. And one of the golden rules of learning is that you need to put in cognitive effort to learning something. The more effort you put in, the better your learning outcomes.

## Applications for healthcare instructors

To tie this all together, here’s some actionable takeaways I suggest:

- Be vigilant when you hear people discuss learning styles or a learner’s preferences, especially when they propose aligning instruction to match a learner’s preferences.
- Don’t let learners pick their own educational material. This includes telling them to search YouTube or another search engine for a lesson. Students will gravitate towards content they perceive will require less cognitive effort. As the instructor, you must decide what learning resources suitable for your students.

## Coming up next...

Now, after all this you might be thinking, does any of this matter? What harm is there in letting people believe learning styles exist? I’ve had a few of my friends and colleagues ask me this recently. I’ll dig into this more next time!

## **References**

1. Mayer, R. E., & Fiorella, L. (Eds.). (2021). *The Cambridge Handbook of Multimedia Learning* (3rd ed.). Cambridge University Press. [https://doi.org/10.1017/9781108894333](https://doi.org/10.1017/9781108894333?ref=kyleslinn.ca)
2. Clark, R. E. (1982). Antagonism Between Achievement and Enjoyment in ATI Studies. *Educational Psychologist*, *17*(2), 92–101\. [https://doi.org/10.1080/00461528209529247](https://doi.org/10.1080/00461528209529247?ref=kyleslinn.ca)
3. Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning Styles: Concepts and Evidence. *Psychological Science in the Public Interest: A Journal of the American Psychological Society*, *9*(3), 105–119\. [https://doi.org/10.1111/j.1539-6053.2009.01038.x](https://doi.org/10.1111/j.1539-6053.2009.01038.x?ref=kyleslinn.ca)
4. Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2015). Matching learning style to instructional method: Effects on comprehension. *Journal of Educational Psychology*, *107*, 64–78\. [https://doi.org/10.1037/a0037478](https://doi.org/10.1037/a0037478?ref=kyleslinn.ca)
5. Kampwirth, T. J., & Bates, M. (1980). Modality Preference and Teaching Method: A Review of the Research. *Academic Therapy*. [https://doi.org/10.1177/105345128001500509](https://doi.org/10.1177/105345128001500509?ref=kyleslinn.ca)
6. Doyle, W., & Rutherford, B. (1984). Classroom research on matching learning and teaching styles. *Theory Into Practice, 23*(1), 20–25\. [https://doi.org/10.1080/00405848409543085](https://psycnet.apa.org/doi/10.1080/00405848409543085?ref=kyleslinn.ca)
7. Curry, L. (1990). A Critique of the Research on Learning Styles. *Educational Leadership*, *48*(2).
8. Constantinidou, F., & Baker, S. (2002). Stimulus modality and verbal learning performance in normal aging. *Brain and Language*, *82*(3), 296–311\. [https://doi.org/10.1016/S0093-934X(02)00018-4](https://doi.org/10.1016/S0093-934X%2802%2900018-4?ref=kyleslinn.ca)
9. Massa, L. J., & Mayer, R. E. (2006). Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style? *Learning and Individual Differences*, *16*(4), 321–335\. [https://doi.org/10.1016/j.lindif.2006.10.001](https://doi.org/10.1016/j.lindif.2006.10.001?ref=kyleslinn.ca)
10. Husmann, P. R., & O’Loughlin, V. D. (2019). Another Nail in the Coffin for Learning Styles? Disparities among Undergraduate Anatomy Students’ Study Strategies, Class Performance, and Reported VARK Learning Styles. *Anatomical Sciences Education*, *12*(1), 6–19\. [https://doi.org/10.1002/ase.1777](https://doi.org/10.1002/ase.1777?ref=kyleslinn.ca)
11. Seddik, M., Attou, Y., & Benaissa, M. (n.d.). The meshing hypothesis revisited: A quasi-experimental study of the impact of tailoring English instruction to learning styles on academic performance. *Pedagogies: An International Journal*, *0*(0), 1–18\. [https://doi.org/10.1080/1554480X.2025.2564357](https://doi.org/10.1080/1554480X.2025.2564357?ref=kyleslinn.ca)
12. Ericsson, K. A., Hoffman, R. R., Kozbelt, A., & Williams, A. M. (Eds.). (2018). *The Cambridge Handbook of Expertise and Expert Performance* (2nd ed.). Cambridge University Press. [https://doi.org/10.1017/9781316480748](https://doi.org/10.1017/9781316480748?ref=kyleslinn.ca)
### The Scientific Method
URL: https://www.kyleslinn.ca/the-scientific-method/
Last updated: 2026-02-08T08:35:11.000Z
For my first real post, I want to briefly review the scientific method. I’m confident most of you are already familiar with it, so I won’t go into too much detail. The reason I’m bringing this up is because we’ll be referring back to this process quite often in future posts. So please stick with me — this is important!

Here’s a diagram summarizing the process:

![](https://www.kyleslinn.ca/content/images/2026/02/625c6ef2-406e-47c6-8446-c6800da62ce9_2000x1528.png)

## Make an Observation

All research begins from observation. At some point, we take note of something that perplexes us and that we want to investigate further. For example, you might observe learners completing their workplace orientation don’t seem to be retaining much the information that’s taught to them. Instead, their preceptors (i.e., more senior professionals who show them the ropes) are having to re-explain many concepts that were covered in orientation.

## Ask a Question

Based on this observation, we next ask a question. In our example above, it could be a simple as “Why aren’t learners retaining information presented in orientation?”

## Form a Hypothesis

Although there are many possible causes that might explain the observation we made and the question we asked, it’s impossible to test them all. (And even more impossible to test them all at once!) Instead, we narrow in on a very limited number of potential explanations for the observation - deductions. If we can test these deductions using the scientific method, that’s when our explanation becomes a hypothesis.

Using the example above, maybe learners aren’t retaining information because the orientation environment is filled with distractions. Maybe the orientation room is beside a high-traffic hallway, and the sound of foot traffic and passing conversation leaks into the room. Maybe the room is physically too small to house all the learners comfortably. Or maybe someone from IT is roaming the room to assist learners with computer login issues, which is distracting to learners. The overall hypothesis here is that the learning environment is affecting the learners’ retention of information delivered in their workplace orientation.

![](https://www.kyleslinn.ca/content/images/2026/02/82e23ed0-bac4-444a-ae86-c482073777bf_1232x928.png)

## Make Testable Predictions

With this hypothesis in mind, the next step is to design a way to test our predictions. The design of our test is important, because the better we design our test, the more confidence we can have in the accuracy and meaningfulness of our results. That said, it’s often not possible to have a perfect study design, especially if we’re hoping to conduct experiments. Often there are tons of constraints we have to account for, such as time, financial, or geographical constraints, to name only a few. So we often have to make the most of the available resources.

Here’s a simplified list of things we should consider when setting up a test of our prediction(s):

**Selecting a Sample:** Ideally, we want a group of participants (a sample) that’s big and diverse enough to generalize our results to a broader population. The goal isn’t necessarily to generalize to the entire world, but at least to a culturally similar population beyond our own institution — like an industry, province, country, or continent.

**Choosing a Research Approach:** Next, we must decide on whether to conduct quantitative or qualitative research.

- *Qualitative research* helps us understand the meaning behind human behaviour, it excels at exploring motivation, perception, or experience.
- *Quantitative research,* allows us to measure what changes and by how much. It’s particularly useful for evaluating instructional strategies and assessing improvements in learning outcomes.

While both approaches are valuable, I’ll focus primarily on experiments and quasi-experimental studies that use quantitative inquiry to examine data-driven educational strategies and their impact on learner performance.

**Controlling for Confounding Variables:** If we decide to go the quantitative research route, we need to control for confounding variables — factors that could influence the results in unintended ways. By doing so, we ensure our findings reflect what we’re actually trying to test, rather than something else entirely.

A common mistake I often see in educational psychology research is *failing to control for time spent learning*. For example, researchers may have a control group and an experimental group. The experimental group receives the same instruction as the control group, plus the additional experimental instruction being tested. Meanwhile, the control group receives no extra instruction. It’s not surprising, then, that the experimental group tends to perform better. It turns out the more time you spend learning something, the better you remember it! As a result, these kinds of studies contribute little to advancing the field, since the improvement can be attributed to increased learning time (that is, the confound) rather than the intervention itself.

**Reliable measurement:** Finally, we need to figure out a reliable way to measure whatever outcome we’re investigating. If we’re trying to measure knowledge retention, we might want a test at the end of the lesson so we can objectively assess what learners remember. And then maybe we could administer another test a few weeks later (or a series of tests staggered over the next few months) to see how retention changes over time.

Sometimes researchers will administer questionnaires asking learners to reflect on their performance. While these can be valuable for understanding individual beliefs or opinions, they are not ideal for measuring learning outcomes. Learners often don’t have the introspective skills required to accurately assess their own knowledge or the quality of their learning experience. Even those who do possess these skills typically can’t evaluate their knowledge at a detailed level.

## Test Hypothesis and Gather Data

After all the preparation, we can finally move on to testing our hypothesis and collecting data. Sticking with our earlier example, we might measure knowledge retention and application among a group of learners in a distracting environment, then test a new group of learners in a distraction-free environment. By comparing the post-orientation test scores of both groups using robust statistical methods (a t-test in this case!), we can determine which cohort performed better and whether this difference is statistically significant. We might also consider whether this result is practically meaningful.

![](https://www.kyleslinn.ca/content/images/2026/02/0a7b7158-561e-43f9-88bd-c6bf47ff7ad1_1232x928.png)

## Iterate or Reject the Hypothesis

Once we have gathered and analyzed the data, we should have enough information to determine whether our hypothesis has merit. If the evidence doesn’t support our proposed explanation, that’s okay. We can either form a new hypothesis and test that, or we can refine our experiment to see if a different approach will give us new insights.

What we *shouldn’t* do — and this is important — is to reformulate our hypothesis based on the data of our original experiment, and present it as though it was our original hypothesis all along. Unfortunately, this practice is very common — so common, that it has its own term “HARKing”, or hypothesizing after the results are known. Researchers, eager to publish positive results, may reframe their hypotheses post hoc in order to report a “significant” finding. This practice introduces **methodological flaws** and clutters the field with misleading studies, making it harder to identify truly impactful research.

## Develop Theories

If our results support our hypothesis, then we can continue to test the same hypothesis under different conditions (e.g., with different groups of learners, in different settings), until we feel confident enough to have a working theory that explains what might be happening in our original observation.

Theories are overarching frameworks that propose why our explanations (or hypotheses) might be true and why we’re observing what we are in our experiments. Theories are what pull together the findings of various research studies to make sense of them on a broader scale.

Returning to our example, let’s say learners in the distraction-free room scored, on average, 10% better than learners in the distraction-filled room — a finding that is potentially both statistically significant and meaningful. From this, we might reasonably conclude that learners learn best in a distraction-free environment! This evidence supports our hypothesis, and it’s a good start, but it isn’t a theory. Our theory, in this case, could be that being in a distraction-free environment lowers the cognitive load that learners are facing and improves memory encoding and storage, which would explain the improved test results. This theory then allows us to connect our research finding — that learners perform best after learning in a distraction-free environment — to a whole literature on cognitive load and memory. Theories provide us with a stronger anchor for our research findings because they give us reasons why our hypotheses and observations came to be.

And at this point, the cycle should begin all over again. Once we’ve have a working theory, testable hypotheses, and robust observations, it might be tempting to say, “Case closed! We’ve solved it!” However, this is risky and premature because there is a very real possibility that our results don’t always hold true. This realization is an important one because it can lead us to hypothesize boundary conditions—the specific situations or contexts in which our theory applies, and those in which it doesn’t. We need to test edge cases to see when and when our explanations might not apply. In terms of our example, maybe learners who have had previous exposure to the material they’re learning might not be as bothered by distractions — this would be an important edge case (i.e., boundary condition) to discover.

## Why is this important?

I’ve made a point of reviewing this because, as we’ll explore in later posts, there is a lot of misinformation swirling about within the education field. This is partly because learning theories founded on evidence that doesn’t adhere to the scientific method are given equal—or even greater—credibility than those that have been rigorously developed and tested through scientific research.

This causes problems when we design our educational experiences based on theories that we believe hold true, but which in reality may:

1. Have never been tested at all.
2. Have been tested and have no reliable data to support them.
3. Have been tested but show only negligible impact on learning outcomes.

To give a concrete example, as I was writing this post, a new report from the *Global Education Evidence Advisory Panel* landed in my inbox*.* The panel noted that nearly 70% of children aged 10 in the Global South cannot read and understand simple text—largely due to a failure to use teaching methods proven effective by research (1).

In my next post, we’ll look into one of the most persistent and widely believed myths in educational psychology: learning styles.

References:

1. [https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099448110272527300](https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099448110272527300?ref=kyleslinn.ca)
### Hello!
URL: https://www.kyleslinn.ca/hello-698609c1fc1c26001bc33dac/
Last updated: 2026-02-06T15:38:51.000Z
Hi folks!

My day job is Project Manager - Clinical Learning at a publicly funded children’s hospital here in Canada. As part of my role, I give a presentation 3-4 times a year about evidence-based best practices in education—specifically, strategies we can use to train new healthcare providers joining our hospital. Most of my audience are nurses who will soon be paired with a student or new hire to mentor for several weeks, but I often get attendees from other professions, such as respiratory therapists and physiotherapists.

I face three challenges with this training. First, I have far too many topics to cover in just one hour. Second, I desperately want to dive into the details of educational research—the kind of depth that nurse educators or respiratory therapist educators might appreciate, with clear examples tied to real situations they’ll encounter while training others. But much of that information falls outside the scope of what my usual audience needs. And third, I only reach a handful of people each year. Maybe my ego has gotten the better of me from the positive feedback I’ve received, but I feel like more people might benefit from this content.

So here we are. I’m launching a newsletter about applying evidence-based best practices in educational psychology to healthcare training. While nursing educators (and educators in any health profession) are my primary audience, I welcome anyone who finds this material interesting.

While I know a fair bit about educational psychology from my Master of Education and from reading research in my spare time, I’m very much still a student of the field myself. I’m not a researcher or a leading expert—just someone passionate about the subject who loves applying this knowledge to real-world situations. If you follow this newsletter, you’ll be joining me on my learning journey.

Thanks for being here and listening to my musings.