It makes a case from DreamSpace Academy’s own record, states the counter-argument, and marks how well each claim is evidenced. Where it describes what the academy runs, the core pages are the standing description and this is the reasoning behind them.
Education is how the ecosystem gets built
One of three essays on how the education and the organisation fit together.
The argument. An organisation whose category is Innovation & Entrepreneurship Ecosystem Builder has to run education itself rather than buy it in. DreamSpace Academy does this in five ways (§5).
Evidence marks. Claims about what happened come from DreamSpace Academy’s own delivery record. Claims about what the organisation has decided come 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.
1. Why an ecosystem builder runs education
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.
DreamSpace Academy holds the opposite view. 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 there are already founders, makers, trainers and delivery partners to work with. Where there are not, someone has to bring them through, and teaching is the only way to do that.
The argument rests on two facts that pull in opposite directions. Education is the constraint. And education on its own does not produce income: this is well evidenced, and DreamSpace Academy’s own model states it in writing. The model accepts both.
2. What ecosystem theory says, and its limits
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 review of entrepreneurial ecosystem sets out the full definition and its limits.
Two points in that literature survive the criticism, and both explain 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 puts education at the centre. If people build the system, their number is an input at the start, not a result measured at the end. Where the ecosystem is missing, that input is missing.
The theory also carries a warning that policy often ignores: 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 in a district with no founders has nobody to accelerate. The problem there is supply, and education is how supply is built.
3. The constraint DreamSpace Academy found: identifying changemakers
DreamSpace Academy recorded this constraint in its own operations:
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)
Access to people was not the hard part. Intake was open and worked at volume: field visits, open application calls and DreamSpace Academy’s own bootcamps brought in large numbers, and most documented changemakers arrived that way. One open call in October 2022 ran across four districts and produced 360 applications, of which 30 were selected, through district workshops and one-to-one interviews 🟢.
The hard part 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.
DreamSpace Academy changed the model:
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. Education gives an ecosystem builder that conversion. No other item on the standard ecosystem-builder menu does.
4. The main argument against: education does not produce income
The strongest objection to this argument is “education does not produce livelihoods, and the data says so.”
The data does say so. DreamSpace Academy’s root-cause analysis rests on these national statistics:
- Unemployment rises with education in Sri Lanka: 0.7% at Grade 5 and below, 3.4% at Grades 6 to 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 to 24, 81.2% of those aged 25 to 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 to 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: the money, market access, introductions and continued support that turn skill into a livelihood. Its root-cause analysis states: the link from capability to income fails for want of coupling, not training.
DreamSpace Academy’s position is therefore narrower than “education works”:
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.
For this reason the teaching sits inside an ecosystem builder rather than inside a school. A school can offer only the first half. DreamSpace Academy’s education depends on what is attached to it: the labs, the bridging, the seed capital, the mentors, the multi-year contact. The model states that several of these exist today (an impact-loan fund and co-founding, both held by DreamSpace (Pvt) Ltd rather than the Academy; bridging and market access; and multi-year contact), but they have never been assembled as one designed bundle, or measured as one. The model lists this as a gap.
5. How DreamSpace Academy uses education to build the ecosystem
The record shows five distinct mechanisms. Grouped under the single word “programmes”, they look like a training centre. Taken one at a time, each one builds part of the ecosystem.
① Empowerment Inside School: the school programme
Empowerment Inside School (EIS) is DreamSpace Academy’s flagship in-school initiative: ICT aligned to the Sri Lankan government syllabus, plus Robotics & STEAM, at no charge to underserved schools. The programme is planned as a sustained six-year engagement, Grade 6 to Grade 11, and uses 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 🟢.
The delivery figures here come from the programme’s narrative reports, not from spreadsheet row counts, which overstate reach: “Reached 194 students across Grades 6–9” in the Batticaloa pilot, July to December 2025, 5 schools; 306 students in Hatton across Dickoya and Ireby, late 2025; 114 students across four Nuwara Eliya schools, April to 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 Maker Journey: where it runs, including the MakerSpace
Maker education is one part of what DreamSpace Academy teaches. The academy also runs business and entrepreneurship trainings, digital security training, and workplace and teacher training. The Maker Journey is the progression used in maker education. It can run in schools, at partner sites, online and in the academy’s own spaces. MakerSpace by DreamSpace Academy is something narrower: a design for a physical space (its equipment specification and layout) and an operating standard, built to be replicated and franchised in a space a local partner provides, and one of the places the journey can run. It is not the organisation itself, and the academy’s education does not depend on it. The delivery record so far covers several curriculum tracks and the 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.
DreamSpace Academy runs no lab units. Software, media and music work happens as communities of practice, not as standing units. Any published list of eleven labs is historical record, not a description of the present.
③ Devolved delivery: local bodies run school clusters
DreamSpace Academy 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 🟢 |
Through the education programme, local organisations gain an operating contract, a payroll and a reason to exist. A changemaker who came through the pathway founded Kathira Greens. The teaching produced the founder, and then produced the founder’s contract.
④ Bridging: placing local people in partners’ programmes
DreamSpace Academy states that bridging is its distinctive contribution. Bridging is not teaching. It turns a regional network position, which an international programme cannot buy, into work for local people.
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”, and they trained about 60 people 🟢. The record shows four modes: 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 the record does not show: any money. Trainer day-rates, EIS cluster terms and what DreamSpace Academy earned as intermediary are all unevidenced. Bridging is not a revenue model. It is a delivery pattern whose economics are unrecorded.
⑤ Alumni: returning as teachers and directors
Alumni now lead much of the software, media and music work, and two are directors 🟢. When DreamSpace Academy took the model to Erode, Tamil Nadu, it was “delivered by two people who are themselves products of the pathway”. A substantial share of the people who teach for DreamSpace Academy came through DreamSpace Academy.
The limit, as the model states it: this is Batticaloa’s bench travelling. It is not yet evidence that a new site can grow its own. The one test of that claim failed. DreamSpace Mullaitivu closed because of a custodian-succession failure: the person running it could not continue, no successor with the interest was found, and the search ran locally only. Funding, operations and capability were not the cause. A replication claim has to include the closed unit, and this one does.
6. National reform: a mandate the state cannot yet deliver rurally
Sri Lanka’s curriculum reform makes ICT and “Entrepreneurship & Financial Literacy” compulsory essential subjects in Grades 6 to 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. A phone is not enough to learn CAD, coding or a laser cutter.
Government STEM reform is a demand signal for this work. The state has a mandate it cannot yet meet rurally, which creates a partner-and-feeder position rather than a rival.
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 narrower: written Zonal Education Office approvals in three zones (Batticaloa, Kantale, Nuwara Eliya).
National policy, not DreamSpace Academy, makes a related point: 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 Academy’s work carries out that stated priority.
7. BOOKBRIDGE: an education programme that produced an organisation
DreamSpace Academy began 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 🟢.
So an education programme produced an organisation: DreamSpace Academy itself, seven years before the organisation wrote the mechanism down.
Whose loan it was, whether it was repaid, and any amount are not confirmed. And it is not an argument against grants. DreamSpace Academy is funded from three sources: grants and partnerships, revenue it earns itself, and the founders’ own capital. The relative shares have never been measured. The academy is not building independence from grants. It is building work that keeps running after the grant that paid for it stops.
8. What DreamSpace Academy does not claim
The argument above explains why an ecosystem builder should teach. It does not claim that DreamSpace Academy’s ecosystem has yet produced what it aims at.
- The conversion rate is unknown. No denominator yet exists for candidates in against Changemakers out. Until it does, no claim about how well the pathway works is available; only that its parts are individually evidenced. 🔴
- The “Earn” verb 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 not been measured 🔴. No jobs-created figure exists, and none is 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. Summary of the argument
Entrepreneurs build an innovation and entrepreneurship ecosystem; they do not just fill it. In a community where those people are not already there, an ecosystem builder has two options: wait for them to appear, or bring them through. Waiting is a search with no schedule and no guaranteed result. DreamSpace Academy ran it for years and named it as its hardest constraint. Bringing them through is a delivery problem with a curriculum, a cohort and a measurable rate, and that is education. The evidence also shows that teaching alone does not produce income. So the teaching has to be attached to labs, bridges, capital and multi-year contact rather than to a certificate. That attachment is the ecosystem, and education brings it the people.
A note on sources
This essay draws on 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 and the incubation model.
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, 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.