the science of desirable difficulty

DOMS ABCD Objectives Framework™️

the science of motivation & mastery

DOMS Edge of Possible Framework™️

the science of experience & interaction

DOMS Minimal Viable Content Framework™️

Learning Science 101

Five key lessons from the research for course designers

The one question I get asked more than any other is: what does the research tell us about how we should design learning experiences?Here’s my answer, broken down into five golden design rules:

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Design Rule #1: Learners learn best when information is minimised & presented in a way that doesn’t unnecessarily tax their working memory.What it means in practice: use the DOMS™️ Minimal Viable Content Framework to ensure the correct balance of content and activity - i.e. 10% prompt content, 80% activity, 10% feedback.When selecting modes, be mindful of cognitive load - e.g. a 3 min video or piece of audio is far less of a strain on working memory than the same 500 words delivered as text on a page.If you read one thing…. **Hardman, 2022 **

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Design Rule #2: Learners learn best when learning objectives & outcomes are aligned to their personal as well as professional and “in course” goals.What it means in practice: take time to understand your learners’ personal & professional pain & aspirations.Use the DOMS™️ Learner Transformation Framework to deep dive your learners' "why". Ensure that you have a crystal clear understanding of who your learner is and how to motivate them through both the content & the structure of your course.If you read one thing…. Mager, 1997

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Design Rule #3: Learners learn better when the learning experience progresses from simple to complex at an appropriate level for the learners in question.What it means in practice: take time to understand your learners’ Zone of Proximal Development.Take time to map out two things: 1. what your learners already know and can do, 2. what your learns want to know & be able to do.Next, identify: 1. what your learners could learn without your help (e.g via YouTube or a book), and 2. what your learners could never realistically achieve in a single learning experience, even with your help.Between these two extremes is your learners' so-called Zone of Proximal Development (ZPD).The ZPD contains knowledge and skills that your learners can only achieve with your help, and at a stretch within the confines of a single learning experience. This is your course “sweet spot” and where your experience needs to sit in order to optimise for motivation & mastery and deliver value.If you read one thing…. Vygotsky, 1978

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Design Rule #4: Learners learn better when they are driven more by internal reasons than external rewards or consequences.What it means in practice: take time to understand & articulate how the experience is connected with your learners’ broader personal & professional goals (see Rule #1).To really drive your learners' motivation you need to make sure that they feel a sense of of competence & progression towards both their course & life goals (e.g. through feedback) regularly, ideally at least once per hour.If you read one thing…. Ryan & Deci, 2000

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Design Rule #5: Learners learn best when the experience is as authentic as possible.What it means in practice: as a rule, the most effective design strategy is to select content, activities, assessments & modes which best replicate real scenarios.We often think of immersive learning as complex experiences involving virtual realities or work placements, but simple strategies like using case studies & having learners work on real problems using real assets (e.g. give feedback on a real life project plan) is as effective at building an authentic experience and supporting learning transfer as more complex approaches.If you read one thing…. Herrington & Herrington, 2007

____If you want to keep on top of all the latest learning science research, distilled into course design practices, sign up to my monthly Learning Science Digest.Happy Designing!
Phil 👋

AI for Learning Designers

Two ways to optimise learner motivation & mastery using AI

Whether we like it or not, AI will change how we design and deliver learning experiences.The good news is that, used with intention, AI can be a powerful tool for delivering learning strategies that we know drive motivation and mastery of the subject.Here are two ways you can use free, open source AI to optimise your learning experience for learner motivation & mastery.

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#1: Use AI to Optimise Your FeedbackFeedback is most powerful when it is:

Initial experimentation with ChatGPT suggests that AI is capable of all of the above.On copying and pasting a series of essays into ChatGPT, the feedback I received was consistently:

Initial research suggests that AI is capable of delivering high quality, immediate feedback in a way that even the most committed educator simply cannot compete with.These findings open us some incredibly exciting potential to solve the until-now wicked problem of scaling high quality feedback, which has for so long limited our ability to deliver high quality learning experiences to anyone, anywhere.Try it now for yourself!

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#2: Use AI to Optimise Your Learning ObjectivesResearch shows that objectives are optimised when they are:

My early experimentation with ChatGPT suggests that AI is capable of making it easy to write objectives that are optimised for learner motivation and mastery:

Step 1: I asked ChatGPT to write me some objectives for a course on sustainability leadership for leaders with no experience of sustainability - the results were, well, not too bad. Probably similar to that of a junior learning designer or teacher:

Step 2: To optimise the objectives for motivation, I asked ChatGPT to add "so that you can" statements to the end of each of my objectives.The AI did exactly as I asked. Immediately the rationale + use of "you" language made the objectives more focused and motivating:

Step 3: Next, I asked ChatGPT to make them more measurable. Here's what it came up with:

Step 4: The objectives were taking shape, but they were also getting a bit confusing (written in third person + first person).So, I asked ChatGPT to turn them into learner-facing "you will" statements:

Step 5: I wanted to ensure adequate stretch, so I asked AI to only use Bloom’s higher order verbs. It got straight on to it:

Step 6: So I can communicate to my learners how their performance will be measured, I asked ChatGPT to rustle me up an assessment rubric.It created four levels of mastery for each objective. Here's an example of what it wrote for objective #1:

Bingo! Through asking the right questions, I was able to create an above-average set of learning objectives in ~2 minutes - a great starting point.For laughs, I asked the AI to create me two more versions of the objectives, one more and one less challenging. It did both with ease.Overall, I think this a great example of the power of combined human + AI expertise, and a fascinating window into the world of Learning Design 3.0.For now at least, AI plays a game-changing role in accelerating the learning design process, but the Learning Designer plays an essential part in acting as coach & expert to turn AI-generated objectives into objectives capable of driving learner motivation & mastery.Try it now for yourself!

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If you want to learn more about AI and other emerging technologies, sign up to my Learning Futures Digest.Happy Designing!Phil 👋

Course Ideation 101

A five step process to generate a high-leverage course idea

A question I get asked a lot is, how do I know if my course idea is a good one? If I build it, will they come?.The harsh truth is that of the millions of courses that we put online every year, only ~3% find Course Market Fit.In practice, this means only 3% of courses inspire learners to complete & tell others about it in numbers large enough to drive growth, impact & profitability.So, how do you avoid common errors and optimise your course idea for Course Market Fit?

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The Formula for Course Market Fit (CMF)My research shows that course creators build the wrong thing because they misunderstand the formula for CMF.Most course creators think they will deliver a successful course if they:

In reality, CMF lies at the intersection of what you know (aka your unique insight) and what the world needs (aka learner pain).Research shows that those courses which achieve Course Market Fit:

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The DOMS™️ Course Ideation Framework takes what we know about how & why humans learn and translates it into a four step process to help optimise your course idea for learner attraction, value & revenue.Use it today to eliminate tumbleweed & put you on the track to achieve learner joy & Course Market Fit.

If you want to learn more about the science of course design, sign up to my weekly Course Design Newsletter.Happy Designing!Phil 👋

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