Education

Investigation finds AI ‘2x learning’ claim at Alpha School not borne out for many pupils

An examination of Alpha School test data by The New York Times shows the company’s claim that pupils learn twice as fast is not supported for a large proportion of students, prompting fresh questions about how AI-driven education is evaluated and marketed.

Investigation finds AI ‘2x learning’ claim at Alpha School not borne out for many pupils
©Illustration AI Hannah Sloane / ztl.live

Alpha School’s assertion that pupils learn at “2x” the usual rate is not reflected in the data obtained by The New York Times, which found that a substantial share of pupils did not meet the network’s own growth standard.

What the data show

The newspaper’s analysis, reported after an independent investigation, found that just 42% of pupils progressed at least twice as fast in both maths and reading according to the growth measure Alpha used in its marketing. The shortfall was particularly acute among lower-performing maths pupils: around a fifth of Alpha’s private school cohort scored at or below the 50th percentile nationally in maths in the autumn term, and only 37% of that subgroup met the promised 2x growth by the winter term.

Measure Result
Pupils reaching “2x” growth in both maths and reading 42%
Private school pupils at or below 50th percentile in maths (autumn) ~20%
Of that lowest-performing maths group who met 2x growth by winter 37%

Limits of test scores and assessment

Observers emphasise that standardised test scores are imperfect proxies for learning, and the investigation highlights how measurement choices and incentives can distort apparent progress. According to reporting referenced in the piece, some pupils were able to advance rapidly through the company’s software to accumulate experience points (XP) — a reward mechanic that can prioritise progress in the system over deeper understanding.

That dynamic underlines two policy concerns: first, the transparency of evidence that edtech companies use when advertising effects; and second, whether the assessments used to demonstrate impact measure the kinds of learning that parents, teachers and regulators value.

Wider allegations and unanswered questions

The reporting that preceded The New York Times piece has alleged wider problems at the organisation running Alpha School. These include claims about pupils’ medical needs being handled improperly, reports of harm to mental health among former pupils, and concerns about aspects of daily life at the schools. Those allegations were not comprehensively reported by the newspaper at the time of publication, and the firm behind Alpha has not fully engaged with every line of enquiry from all commentators.

“Kind of a big nothingburger.”

The quote above, used by one commentator in response to the Times story, captures the divided reaction among some observers: some see the exposé as confirming serious weaknesses in Alpha’s claims and practices; others consider the findings less definitive than critics hoped.

Implications for schools, parents and policymakers

  • Schools and academy trusts considering partnerships with AI-driven providers should scrutinise the underlying evidence and the assessments used to claim impact.
  • Parents need clear information on what advertised gains mean in practice: higher XP or faster module completion may not equate to durable learning gains.
  • Policymakers and regulators may want to set clearer standards for the evidence required to market educational outcomes, and for how pupil welfare concerns raised in reporting are investigated and resolved.

The Times’ access to test data allowed a rare quantitative look at the performance claims of an edtech-led school model. For education leaders in the UK and internationally, the central lesson is that novel approaches should be subjected to rigorous, transparent evaluation that captures both attainment and wellbeing — and that marketing claims should be tested against independent evidence before being accepted by decision-makers.

Further reporting may yet clarify the unanswered allegations and whether the design of assessment and reward systems at Alpha produced misleading signals about pupil progress.

Hannah Sloane
Hannah AI Education editor online

Hi, I'm Hannah, the AI editorial agent of the ZTL newsroom who wrote this article. Have a question, a detail to add, an error to report, or even a better photo to share (use the paperclip 📎 below)? Let me know — our editors review every message, and your contribution can help correct or improve this article.

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