It makes a case from DreamSpace Academy’s own record, states the counter-argument at full strength, and marks how well each claim is evidenced. Where it describes what we run, the core pages are the standing description and this is the reasoning behind them.
Education is not DreamSpace Academy’s charitable side. It is how the ecosystem gets built.
One of three essays on how the education and the organisation fit together.
What this is. An argument for why an organisation whose category is Innovation & Entrepreneurship Ecosystem Builder must run education itself rather than buy it in — and how DreamSpace Academy actually does it.
How to read the evidence marks. Claims about what happened are drawn from DreamSpace Academy’s own delivery record; claims about what the organisation has decided are drawn from its written model. Each carries a grade: 🟢 primary-sourced or corroborated across sources · 🟡 supported but partial · 🔴 asserted, and under validation.
⚠️ Several figures below are recorded as what DreamSpace Academy states rather than as verified counts, and the honesty section at the end is part of the argument rather than a disclaimer attached to it.
1. The question nobody asks out loud
An organisation that says it builds an innovation and entrepreneurship ecosystem is expected to do certain things: convene people, make introductions, run an incubator, find capital, put on a demo day. Running a robotics class for eleven-year-olds in a rural government school is not on the list. It looks like a different organisation’s work, bolted on.
The argument of this article is that it is the opposite: that for an ecosystem builder working in an underserved community, education is the only part of the job that produces the thing everything else needs — people who will build. Every other function assumes a supply of founders, makers, trainers and delivery partners. In a place where that supply does not already exist, someone has to make it, and there is no way to make it except by teaching.
Two things have to be established for that argument to hold, and they pull in opposite directions. The first is that education really is the constraint. The second is that education on its own is not a mechanism for income — which is well evidenced, and which DreamSpace’s own model states in writing. Both are true. The interesting organisation is the one that lives with both.
2. What ecosystem theory actually says — and where it stops
The entrepreneurial-ecosystem literature is unusually candid about its own weaknesses. Its leading proponents describe the concept as “under-developed and under-theorized”, and the most-repeated criticism inside the field is that it is tautological: ecosystems are systems that produce successful entrepreneurship, and where there is successful entrepreneurship there is apparently a good ecosystem [Stam 2015; Stam & van de Ven 2021]. A review of 181 empirical studies found much of the literature uses the term “in name only” [Wurth et al. 2023]. The full definitional review, with its limits, is in the definitional review of entrepreneurial ecosystem.
Two things in that literature do survive the criticism, and both bear directly on why an ecosystem builder should teach.
One: the elements only matter through their interaction. Isenberg’s original 2010 formulation is explicit — leadership, culture, capital markets and customers are “in isolation… conducive to entrepreneurship but insufficient to sustain it. That’s where many governmental efforts go wrong — they address only one or two elements.” An inventory of universities, mentors, capital and events is therefore not evidence that an ecosystem exists.
Two: entrepreneurs are treated as builders of the system, not only as its output [Stam 2015]. This is the distinctive move of the whole framework, and it is the one that turns education from a peripheral good deed into the central act. If the people are the system’s builders and not merely its product, then the supply of people is not a downstream metric. It is the upstream input, and it is the input that is missing where the ecosystem is missing.
And the warning that comes with the theory is the one most often ignored: stop emulating Silicon Valley. The academic reviews report that policy isomorphism — importing a template from a thriving ecosystem without regard to local conditions — is the observed practice [Spigel 2017; Brown & Mawson 2019]. An accelerator dropped into a district with no founders will accelerate nobody. That is not a funding problem. It is a supply problem, and supply is an education problem.
3. The constraint DreamSpace actually hit
This is not a theoretical claim in DreamSpace’s case. It is a documented operational finding, and it is the single most useful sentence in the model spec:
DreamSpace Academy’s hardest constraint was never the labs, the funding or the curriculum — it was identifying changemakers. (DreamSpace Academy’s own specification of the venture pathway)
Note precisely what was hard. Not access to people. Intake was already open and already worked at volume — field visits, open application calls and DreamSpace Academy’s own bootcamps brought in large numbers, and that is how most documented changemakers arrived. One open call in October 2022 ran across four districts and produced 360 applications → 30 selected, through district workshops and one-to-one interviews 🟢. Access was never the bottleneck.
What was hard was that the model waited for already-motivated individuals to surface. Finding rare, self-selected, already-formed people does not scale, and it makes supply unpredictable and exhausting to sustain. Every discovery event has to be run again next year, from zero.
The fix DreamSpace adopted is the whole argument of this article in one line:
Co-creation changes the supply from found to built. The Maker Journey — Explorer → Maker → Innovator → Changemaker — develops the motivation rather than screening for people who arrive with it. “Converts discovery from a search problem into a delivery problem.” (DreamSpace Academy’s own specification of the venture pathway)
A search problem has an unknown yield and no schedule. A delivery problem has a curriculum, a timetable, a cohort and a measurable rate. That conversion is what education buys an ecosystem builder, and nothing else on the standard ecosystem-builder menu buys it.
4. The counter-argument, stated at full strength
If the article stopped there it would be making a claim the evidence refutes. It has to deal with the strongest objection, which is not “education is nice but soft” — it is “education does not produce livelihoods, and the data says so.”
It does say so. From the national statistics DreamSpace’s own root-cause analysis is built on:
- Unemployment rises with education in Sri Lanka — 0.7% at Grade 5 and below, 3.4% at Grades 6–10, 6.0% at O/L, 8.0% at A/L and above, and the gradient holds in every province 🟢.
- 67.6% of Sri Lanka’s unemployed are already computer literate — 75.5% of those aged 20–24, 81.2% aged 25–29 🟢.
Two out of three unemployed Sri Lankans can already use a computer. Any theory of change whose mechanism is “teach underserved young people ICT and they will get work” is already refuted by the national statistics. (DreamSpace Academy’s root-cause analysis)
The intervention literature reaches the same verdict from the other direction. Training alone is null-to-modest and often fades: only ~29% of short-term earnings estimates are positive; a 37-evaluation meta-analysis finds “no immediate translation into business set-up or increased income”; the most rigorous skills RCTs show effects fading by 12–15 months 🟢. But training plus a complementary input is categorically different — a job referral produced +40% earnings where training alone did nothing; multi-component bundles produced durable gains across six countries; in post-conflict Uganda, cash + training + supervision doubled incomes 🟢. Peer-reviewed FabLab work finds that making fosters some entrepreneurial skills and needs explicit programmes and incubation layered on top 🟢.
The model calls this coupling, and it is stated as root cause R3: the capability→income link fails for want of coupling, not training.
So the honest position is not “education works”. It is sharper and more useful than that:
Education is the mechanism that produces builders. It is not the mechanism that produces income. An organisation that teaches without the couplings will watch the gains decay on a schedule the literature can already predict.
This is exactly why the teaching has to sit inside an ecosystem builder rather than inside a
school. A school can only offer the first half. What makes DreamSpace’s education work defensible is
what is attached to it — the labs, the bridging, the seed capital, the mentors, the multi-year
contact — and the model says plainly that DreamSpace Academy holds three of the four couplings today and has never
assembled them as one designed bundle, or measured the bundle (00-root-cause-analysis.md §5, R3).
That is a stated gap, not a claimed strength.
5. How DreamSpace uses education to build the ecosystem
Five distinct mechanisms are visible in the record. They are worth separating, because they are usually collapsed into the single word “programmes” — and collapsed, they look like a training centre. Separated, they look like ecosystem construction.
① The school programme — the supply line
Empowerment Inside School (EIS) is DreamSpace Academy’s flagship in-school initiative: ICT aligned to the Sri Lankan government syllabus, plus Robotics & STEAM, delivered free to underserved schools, designed as a sustained six-year engagement, Grade 6 → Grade 11, using challenge-based learning rather than rote instruction. It runs on a 13-phase standard operating procedure that begins with school screening — no ICT teacher, no computer lab, low O/L ICT results, rural or marginalised — and passes through Zonal Education Department approval, baseline assessment, delivery, baseline-vs-final measurement, and a closure step that trains teachers and leaves a student ICT club behind 🟢.
Delivery on record, quoted from narrative reports only (never spreadsheet row counts, which the archive inflates): “Reached 194 students across Grades 6–9” in the Batticaloa pilot, Jul–Dec 2025, 5 schools · 306 students in Hatton across Dickoya and Ireby, late 2025 · 114 students across four Nuwara Eliya schools, Apr–May 2026, 13 sessions, 21 projects 🟢. The concept report’s “616 students across 9 schools in 3 regions” is a planning target that includes unimplemented Mullaitivu — it is a plan, not delivered reach.
② The makerspace — where the journey is run
MakerSpace by DreamSpace Academy is one programme inside the ecosystem, not the organisation itself. It runs the Maker Journey, seven curriculum tracks, and the delivered in-house bootcamps: seven numbered robotics batches (two of which ran dual concurrent sub-cohorts), a three-batch music programme with graded bilingual exams, AI & Electronics with Scratch, Make & Play, a university-preparation programme, and monthly one-day workshops with prepared agendas and slides 🟢. Article 2 of this series covers the method.
⛔ A precision that matters: DreamSpace Academy runs no lab units. Software, media and music work happens inside the makerspace as communities of practice. Any published list of eleven labs is historical record, not a description of the present.
③ Devolving delivery — teaching that creates organisations
This is the mechanism most easily missed, and it is the most literally ecosystem-building thing in the record. DreamSpace does not deliver every EIS cluster itself. It hands clusters to local bodies that employ their own staff:
| Body | What it runs | Evidence |
|---|---|---|
| Kathira Greens | the Vakarai · Kalkudah EIS cluster (3 schools) | director testimony, 2026-08-05 🟢 |
| Inverta | the Kantale cluster (5 schools), employing its own trainers | director testimony, 2026-08-05 🟢 |
| Eegai | incubated 2021 → now the EIS managing organisation for Trincomalee | DreamShot cohort record 🟡 |
| Thiru & team | Hatton estate schools | director testimony, 2026-08-05 🟢 |
Read the second column again. The education programme is the instrument through which local organisations acquire an operating contract, a payroll and a reason to exist. Kathira Greens is itself a venture founded by a changemaker who came through the pathway. The teaching produced the founder; the teaching then produced the founder’s contract.
④ Bridging — spending a network position on other people
DreamSpace Academy’s rarest documented capability is not teaching. It is converting a regional network position an international programme cannot buy into work for local people — and the model calls the bridging evidence “the strongest non-training evidence in the record.”
The clearest instance is in the director’s own words: “IREX wanted to spread its media-literacy programme across Sri Lanka and they didn’t have a good partner — DreamSpace Academy brought them to the Central and the North… I introduced Ladhushan and Donald as trainers for their training programme” — they trained ~60 people 🟢. Four distinct modes are now separated in the evidence base: placement (individuals into a funder’s programme as paid trainers), devolution (§3 above), convening (a partner’s premises and standing carry a DreamSpace Academy event), and exposure (DreamSpace Academy spends a standing international position to put its own people on a stage).
⚠️ What is not established, and matters: no money is evidenced for any of it — not trainer day-rates, not EIS cluster terms, not what DreamSpace Academy earned as intermediary. ⛔ It must not be described as a revenue model. It is a delivery pattern whose economics are unrecorded.
⑤ Alumni returning as the ecosystem’s staff — the bench
The record supports something stronger than “alumni do well”. Alumni now run the labs, and two are directors 🟢. When the model exported to Erode, Tamil Nadu, it was “delivered by two people who are themselves products of the pathway”. A substantial share of the people entrusted with DreamSpace Academy’s teaching came through DreamSpace Academy.
⚠️ The honest reading, and the model states it: that is Batticaloa’s bench travelling. It is not yet evidence that a new site can grow its own. The one test of the second claim failed — DreamSpace Mullaitivu closed, and the cause was a custodian-succession failure: the person running it could not continue, no successor with the interest was found, and the search ran locally only. Not funding, not operations, not capability. A replication claim that omits a closed unit is not defensible, and this one does not.
6. The system reason: the state has committed to something it cannot yet deliver
Sri Lanka’s curriculum reform makes ICT and “Entrepreneurship & Financial Literacy” compulsory essential subjects in Grades 6–9 for the first time, phasing in from 2026 and reaching the full band by 2029 🟢. The delivery capacity was never built: 19% of type-2/3 schools have IT labs against 72% of top-tier schools, and the technology-stream student/teacher ratio is 35.3 against a 12.8 average 🟢. On the household side, 1.5% of estate households own a computer, and 92.6% of estate internet access is by smartphone alone — you cannot learn CAD, code or a laser cutter on a phone.
The model’s own strategic review calls the inversion out: government STEM reform had been read internally as a competitive threat. It is a demand signal. The state has a mandate it cannot yet meet rurally, which creates a partner-and-feeder position rather than a rival.
⚠️ And the honest qualifier travels with it: whether that position is contractible — an MoU, a provincial agreement, a recognised delivery-partner status — remains an open gap. The root is proven; DreamSpace Academy’s licence to act on it is not. What exists today is real but narrower: written Zonal Education Office approvals in three zones (Batticaloa, Kantale, Nuwara Eliya).
There is also a national-policy sentence that belongs in every proposal DreamSpace writes, and it is not DreamSpace Academy’s own: Sri Lanka’s startup ecosystem is “confined to the urban areas especially Colombo”, and “decentralizing support infrastructure” is named verbatim as a national policy priority. DreamSpace is executing a stated national priority, not requesting an exception to one.
7. The organisation is itself the argument
DreamSpace Academy was founded in BOOKBRIDGE’s 11th Capability Program in 2018 — a four-module, roughly six-month programme ending in a pitch to investors, whose published mechanism sets each centre up as a social enterprise run by a local entrepreneur, financed by a soft loan repaid out of the centre’s own trading income 🟢.
That is an education programme producing an organisation — the exact claim this article is making, run on DreamSpace itself seven years before the organisation wrote the mechanism down. DreamSpace Academy asks of the ventures it supports what was asked of it.
⛔ Three fences travel with that fact and must not be dropped. Whose loan it was, whether it is repaid, and any amount are all unconfirmed. ⛔ And it is not an argument against grants. DreamSpace Academy runs on grant funding and says so — 20+ grants since 2019 — and the model puts grants at the service of the Social Mission vertical by design. The founding critique is not about the money’s form. It is about a grant that ends and leaves nothing running. What DreamSpace Academy is building is not independence from grants; it is that grant money buys something that keeps going after the grant stops.
8. What this argument does not claim
The case above is for why an ecosystem builder should teach. It is not a claim that DreamSpace’s ecosystem has yet produced what it aims at, and the repo is strict about the difference.
- The conversion rate is unknown. Candidates in, Changemakers out — the denominator does not exist yet. Until it does, no claim about how well the pathway works is available; only that its parts are individually evidenced. 🔴
- The “Earn” pillar is a hypothesis under validation, not a result. That a skilled maker can sell self-made products for small income is near-term and low-risk 🟡. That this becomes a sustained livelihood at a reliable rate, in this place, through this pipeline, has never been measured anywhere 🔴. ⛔ No jobs-created figure exists and none may be published.
- Ecosystem outcomes are largely unmeasured. The identity — Innovation & Entrepreneurship Ecosystem Builder — is evidenced by what DreamSpace Academy has built, not yet by what the ecosystem has yielded.
- Every reported outcome is completer-derived. In a trainer’s own words: “The most important feedback is from the students who stopped attending. We currently do not know why they left.” 🟢 Retention cannot be modelled and every success statistic carries survivorship bias.
- Self-reported figures are recorded as “DreamSpace Academy states”, never as verified counts, and cohort totals have never been de-duplicated.
The strategic task, in the words of DreamSpace Academy’s own audit: “not to become something new. It is to say, accurately, what it already is — and then to fund and measure that thing on purpose.”
9. The claim in one paragraph
An innovation and entrepreneurship ecosystem is built by its entrepreneurs, not merely populated by them. In a community where those people are not already present, an ecosystem builder has exactly two options: wait for them to surface, or make them. Waiting is a search problem with no schedule and no yield — DreamSpace ran it for years and named it as its hardest constraint. Making them is a delivery problem with a curriculum, a cohort and a measurable rate, and it is called education. The evidence is equally clear that teaching alone will not produce income, which is precisely why the teaching has to be attached to labs, bridges, capital and multi-year contact rather than to a certificate. That attachment is the ecosystem. The education is how it acquires people to attach.
A note on sources
Written from DreamSpace Academy’s own record — the delivery and asset inventories, the case studies, director testimony and the funder history — together with its written model: identity, root-cause analysis, theory of change, the DreamSpace Lifecycle, the engine, and the incubation ecosystem.
National statistics resolve to their publishers: the Department of Census and Statistics Labour Force Survey 2023 and Computer Literacy Bulletin 2024, UNDP and OPHI district profiles 2023, the World Bank Sri Lanka Development Update (October 2024), and the WIPO Global Innovation Index 2025. Intervention evidence is cited to the published studies named in the text; the full list is on the references page.
⚠️ Some figures that circulate near this material are refuted and must never be cited — the “90% franchise versus 30% startup survival” statistic and a branded “Five Stages of Scale” among them. Neither appears here.
⚠️ A third party restating DreamSpace Academy’s own wording is not independent evidence. Partner pages, directories, award listings and news items quoting the organisation are restatements of the source, not observations of it, and nothing here treats one as corroboration.