Start with the problem, not the tool
A companion to Chapter 14 of the book, Designing Effective Learning Tools. The same ideas in several forms: film, conversation, 2 infographics, a mind map and 6 activities. Start with whichever suits you.
Chapter 14 in two minutes
Many learning tools are built around what the technology can do. They measure whatever is measurable and hand over long reports that nobody has time to read. Chapter 14 argues that design should begin with the learning problem: what a trainer needs to know before a session, and how learners actually process information.
That means managing cognitive load for the people using the tool. A concise summary of a group's preferences is more useful than a data dump. Tools should also explain how they reach their conclusions, so trainers can act on recommendations with professional confidence rather than blind trust.
The educator stays central. Good tools present options rather than directives, and add to professional judgement instead of automating it. Privacy, data minimisation and freely given consent are treated as design requirements from day one, and tools grounded in how learning works keep their value as technology changes.
Impressive and useful are different qualities, and only one of them survives a session.
Watch or listen
Prefer to take it in by eye or by ear? Both cover the core ideas of Chapter 14 in a few minutes.
Film, 2 min
How to design ed-tech that actually works
Why learning tools should start from the problem a trainer faces, not from what the platform can measure. Captions are built in.
Conversation, 6 min
Ed-tech needs psychology, not raw data
A conversation about cognitive load, explainable recommendations and keeping the educator in charge of teaching decisions.
Chapter 14 at a glance
A quick overview, then the full argument with the evidence. Select either one to see it full size.
How the ideas connect
Every idea in Chapter 14 on one page. Look at it before you read to see the shape of the argument, or afterwards as a recap.
Put it into practice
Short activities to run with a group or work through on your own. Each one has a printable card.
With a group (3)
On your own (3)
Go deeper
The research and writing behind Chapter 14.
- Don Norman, Internet ArchiveThe Design of Everyday ThingsThe classic case for designing around how people actually think and act, not around the machine.
- Sweller, Ayres and Kalyuga, SpringerCognitive Load TheoryThe theory behind the chapter's argument for concise, decision-ready information.
- Ribeiro, Singh and Guestrin, ACM SIGKDD, 2016"Why Should I Trust You?": Explaining the Predictions of Any ClassifierThe paper behind the chapter's point that people need to see why a system reached its conclusion before they can trust it.
- OECDOECD Digital Education Outlook 2021An international review of smart technologies in education, including guidance on the responsible use of education data.
- Rose Luckin, Educate Ventures ResearchMachine Learning and Human IntelligenceWhy AI in education should strengthen human intelligence rather than stand in for it.
- Neil Selwyn, BloomsburyEducation and Technology: Key Issues and DebatesA critical look at the gap between what education technology promises and what it changes.
