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Futures of education glossary
30 terms from C24, Futures of education — each defined in the primer's own words. Every term the primer teaches links to the slide that teaches it.
C24 · Evidence and change
Futures of education
“The future of education is a technology forecast.”
Every term below is defined in the words of futures of education, primer C24 of understanding the context of education, and opens the primer at the slide where it is taught. 1 term is also defined by another primer in the series; where the two differ, both wordings are given. The whole context glossary holds all of them together.
| Term | Definition | Referred to in | Read further |
|---|---|---|---|
| A | |||
| AI and the purpose of schooling | The question, reopened by generative models, of what schooling is for when answers are cheap to produce. It is a question about aims, treated in primer C01, rather than a question about any particular tool. |
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| Anticipatory governance | Guston’s (2014) term for “a broad-based capacity extended through society” to manage emerging technologies while management is still possible, built from foresight, public engagement and integration into decisions. |
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| Automation and work | The displacement and reshaping of tasks by machines. For education its importance is indirect: it changes what qualifications are worth, how often adults must retrain, and which skills schools are asked to guarantee. |
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| B | |||
| Backcasting | Starting from a chosen future, desired or feared, and working backwards to the steps that would connect it to the present. It is used to overcome present bias in planning (Government Office for Science, 2024). |
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| Black swan | A rare, high-impact event that was not anticipated and is rationalised afterwards. Singapore’s Centre for Strategic Futures names identifying them as one reason it exists (Centre for Strategic Futures, 2026a). |
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| C | |||
| Causal layered analysis | A method that reads an issue at four levels: the litany, the systemic causes, the worldview and the underlying myth or metaphor (Inayatullah, 1998). |
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| Co-agency | The OECD’s term for agency exercised with others: students are “surrounded by their peers, teachers, families and communities, all of whom interact with and guide the student towards well-being” (OECD, 2019). Primer C01 covers it. |
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| D | |||
| Deschooling | Illich’s (1971) argument that universal education cannot be delivered through schooling, and that “educational webs” should replace institutional funnels. Used today as shorthand for any serious case that schooling is not the only form education can take. |
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| Drivers of change | The forces that move the issue being studied, sorted in practice by how certain they are and how far the user can influence them. Sorting them is the step that turns a scan into a scenario. |
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| E | |||
| Education for sustainable development | UNESCO’s programme of education that “empowers people with the knowledge, skills, values, attitudes and behaviors to live in a way that is good for the environment, economy, and society” (UNESCO, n.d.-b). |
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| F | |||
| Foresight | The structured consideration of ideas about the future in order to make better decisions in the present. It assumes prediction is limited and works with several futures at once (OECD, 2020). |
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| Futures literacy | UNESCO’s term for the capability of using images of the future well: “the skill that allows people to better understand the role of the future in what they see and do” (UNESCO, n.d.-a; Miller, 2018). |
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| Futures thinking | The general habit of treating the future as plural and partly open, rather than as a single extrapolation of the present. Foresight is its disciplined form. |
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| H | |||
| Horizon scanning | “The systematic collection of insights on emerging trends and weak signals of change to identify potential threats, risks and opportunities” (Government Office for Science, 2024). |
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| Human-centred AI | Design and policy that treat artificial intelligence as subordinate to human judgement, rights and agency. UNESCO makes “a human-centred mindset” the first dimension of both its AI competency frameworks (Miao, Shiohira, & Lao, 2024). |
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| L | |||
| Learning ecosystems | A way of describing provision as a connected set of settings — schools, families, workplaces, libraries, online communities — rather than as one institution. The OECD’s “schools as learning hubs” scenario is one version of it. C16 A way of describing the whole set of places a person can learn — institutions, employers, platforms, libraries, communities — and the connections between them. Useful as a framing; rarely operationalised well enough to be measured. | ||
| Lifelong learning societies | Societies organised so that learning continues across the whole life course, with funding, time and recognition to match. Ageing populations make this a practical question rather than a slogan. Primer C16 covers it. |
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| M | |||
| Megatrends | Large, slow forces that shape many domains at once, such as ageing, urbanisation or digitalisation. They are the background against which weak signals are read. |
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| N | |||
| New social contract for education | UNESCO's call for an education "that can repair injustices while transforming the future", grounded in the right to education throughout life and education as a common good (International Commission on the Futures of Education, 2021). |
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| O | |||
| OECD scenarios for schooling | Four alternative futures for 2040: schooling extended, education outsourced, schools as learning hubs, and learn-as-you-go. None is a prediction, and ranking them by probability wastes the exercise (OECD, 2020). | ||
| P | |||
| Possible, plausible, probable and preferred futures | The four claims a statement about the future can make: it might happen, it could happen given how the world works, it is likely on current trends, or it ought to happen. The classes nest (Voros, 2003, 2017). |
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| S | |||
| Scenario | A fictional, internally coherent account of one future, written to be thought with. The OECD (2020) insists scenarios “never contain predictions or recommendations”. |
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| Scenario Planning Plus | The Centre for Strategic Futures' approach, which "retains Scenario Planning as its core but taps on a broader suite of tools" suited to weak signals, black swans and wild cards (Centre for Strategic Futures, 2026b). |
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| T | |||
| Techno-solutionism | The habit of answering structural problems with a product. A system can adopt every tool available and leave the distribution of teachers, money and time exactly as it was. |
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| Three Horizons | A framework that separates the pattern that currently dominates and is losing its fit (H1), the turbulent innovations tried in response (H2), and the emerging pattern growing at the fringe (H3) (Sharpe et al., 2016). |
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| Transformative competencies | The OECD’s (2019) name for creating new value, taking responsibility, and reconciling conflicts, tensions and dilemmas — the competencies its Learning Compass says learners need to shape a changing world. |
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| U | |||
| UNESCO AI competency frameworks | Two 2024 frameworks: 12 competencies for students and 15 for teachers, treating ethics and a human-centred view as competencies in their own right (Miao & Cukurova, 2024; Miao, Shiohira, & Lao, 2024). |
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| W | |||
| Weak signals | Small, early indications that something may be shifting, visible before a trend is established. Most turn out to be nothing, which is why they are gathered in quantity rather than judged one at a time. |
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| Wild cards | Low-likelihood events with very large effects. Foresight treats them as worth rehearsing precisely because they cannot be forecast. |
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| Wind-tunnelling | Also called policy stress-testing: running an existing plan, policy or product through each of a set of scenarios to see where it holds, where it needs work and where it fails (Government Office for Science, 2024). |
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