Educational Technology as Design
EdTech as design in one page
- Source: Diana Laurillard, Teaching as a Design Science (2012). Argues that teaching is best understood as a design discipline, not an analytic one.
- The shift: From “what makes good teaching?” (analysis) to “how do we build a learning experience that produces a specific outcome?” (design).
- What design adds:
- Specific outcomes that can be tested.
- Iteration: build, test, revise, ship.
- Reusable patterns: lesson designs that other teachers can pick up and adapt.
- Implication for ICT: Educational technology is most useful when it supports the design loop. A tool that lets teachers prototype, test, and share lesson designs has more impact than a tool that just delivers content.
- Related: John Dewey on the classroom as a laboratory. Engineering disciplines as a model for what teaching could become.
For most of its history, teaching has been treated as an art. Some people are good at it, some are not, and the difference is mysterious. The science of teaching has mostly meant analysis: studying what good teachers do, identifying patterns, publishing papers. Useful work, but it does not by itself produce better teaching at scale.
Diana Laurillard’s argument in Teaching as a Design Science is that teaching needs to be treated more like engineering and less like analysis. The job is not only to understand learning, but to design things that produce it. The job is to build, test, and ship.
Analysis sciences vs design sciences
Some disciplines exist to understand the world. Biology explains how cells work. Psychology explains how memory operates. Sociology explains how groups behave. These are analysis sciences. Their output is description and explanation.
Other disciplines exist to make new things. Mechanical engineering does not just describe machines; it builds them. Architecture does not just analyse buildings; it produces them. Software engineering does not just study code; it ships products. These are design sciences. Their output is artefacts that work.
The two types use each other. Engineering uses physics. Architecture uses materials science. But the design sciences are not the same as the analysis sciences they draw on. The design sciences are organised around making things, with their own methods: prototyping, iteration, testing, version control, shared patterns and standards.
Teaching has historically been positioned as a craft on the analysis side. Researchers analyse what teachers do; teachers learn by apprenticeship and trial. Most of teacher preparation is about understanding learning theories, child development, and subject matter. The design half (how to build a learning experience that produces a specific outcome) is largely left to the individual teacher to work out.
Laurillard’s argument is that this is a missed opportunity. The design half could be a discipline of its own, with the same tools other design disciplines use: shared patterns, iteration, testing, public revision.
An analysis science explains the world. A design science builds new things.
Biology and psychology are analysis. Engineering and architecture are design. The two use each other but have different methods. Laurillard argues that teaching has been treated as a near-analysis craft and would be more powerful as a design science.
What design adds to teaching
When teaching is treated as a design science, three things change.
Specific outcomes that can be tested. A design discipline does not work in vague terms. A bridge has to hold a specific load; a circuit has to pass a specific current; a programme has to produce a specific output. Teaching that is designed sets specific outcomes for each lesson: not “understand fractions” but “convert a fraction to a decimal without a calculator.” Vague outcomes cannot be tested, and untested designs cannot improve.
Iteration. Engineers do not get the design right on the first try. They prototype, test, see what fails, revise, and ship. Most teaching does not have a structured iteration loop. A lesson is delivered, students do or do not learn, the term ends, the lesson is repeated next year mostly the same way. A design discipline builds in the version-up: this year’s lesson is better than last year’s because the failures from last year drove a redesign.
Reusable patterns. Other design disciplines share patterns. Software has design patterns; architecture has typologies; engineering has standard components. Teachers largely build from scratch each time, or copy from colleagues without a vocabulary for what they are copying. A design discipline would produce reusable lesson patterns that other teachers can pick up and adapt, with named structures and known trade-offs.
These three together would change how teaching improves over time. Without them, each teacher’s growth is private and slow. With them, the field gets better collectively, the same way other design fields do.
What ICT changes
If teaching becomes a design discipline, technology shifts from “tool used during a lesson” to “infrastructure for the design loop itself.”
A useful comparison is software engineering. A modern programmer relies on much more than code itself: version control, testing frameworks, code review, continuous integration, package managers, design pattern libraries, and shared documentation. These tools do not produce software directly. They produce the environment in which producing software is fast, reliable, and improving.
Teaching could have an analogous stack. Tools for prototyping lessons. Tools for testing them with students and seeing the results. Tools for revising based on what failed. Repositories of shared lesson designs with named patterns and feedback. Versioning so that a lesson improves over the years instead of starting fresh each cycle.
Some of this exists in fragments. Curriculum-sharing platforms, open educational resource repositories, lesson study communities, learning analytics dashboards. None of them is yet at the maturity of the software-engineering stack. The argument is that the gap is the design opportunity for educational technology over the next decade.
How design thinking changes a teacher’s day
A teacher who treats their work as design rather than performance behaves differently across a term.
They start each lesson by writing down a specific outcome the lesson should produce. Not a topic; a testable change in what students can do.
They build the lesson backward from that outcome. The assessment comes first: how will I know if students reached the outcome? Then the activities that produce the kind of student work the assessment will measure. Then the inputs that prepare students to do those activities. The order is the reverse of the usual planning order, and produces a tighter lesson.
They run the lesson knowing it is a prototype. The first time a new lesson is taught, the expectation is that something will not work. The teacher pays attention to what went wrong and writes it down.
After the lesson, they revise. Not the whole plan, but the specific piece that failed. The next time the lesson runs, that piece is different. Over a few cycles, the lesson gets reliable.
They share the lesson with colleagues, with notes on what works and what does not. Other teachers adapt it to their classes. The design improves through use, not just through the original author’s iteration.
A teacher who never does any of this can still be a good teacher. The argument is that a teacher who does this is a better teacher than they would otherwise be, and that the school where most teachers do this gets better faster than the school where they do not.
What this means for ICT in education
Two practical implications.
Tools that support the design loop matter more than tools that deliver content. A platform that lets teachers prototype, test, and share lesson designs adds more value than a platform that just hosts video lessons or graded quizzes. The first changes how teaching improves; the second is just a delivery channel.
Learning analytics should serve the teacher, not the institution. Data on what students did during a lesson is most useful when it flows back to the teacher in time for them to revise the next iteration. Data that goes only to an institutional dashboard for accountability does not feed the design loop. The same data, routed to the teacher with a “what to fix next” suggestion, would.
The shift is small in implementation and large in framing. It moves educational technology from “make the existing lesson smoother” to “make the field of teaching better.”
Tools for the design loop matter more than tools for delivery. Data should serve the teacher, not just the institution.
A platform that helps teachers prototype, test, share, and revise lessons changes how teaching improves over time. Learning analytics that flow back to the teacher in time to fix the next iteration support the loop; data that only flows to admin does not.
Common misreadings
Treating teaching as design does not mean teaching is only design. It still draws on learning science, child development, and subject knowledge. The argument is that design is an additional discipline alongside these, not a replacement.
It does not mean lessons should be over-engineered. A good design discipline aims for simple solutions, not elaborate ones. A short clear lesson with a tested outcome is the goal, not a long complicated one.
And it does not require expensive technology. Pencil and paper can support iteration, testing, and shared patterns if the school’s culture supports them. The technology helps at scale, but the mindset comes first.
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