Source, present, describe
Students explain their data source, present it with at least one appropriate visualisation, and describe patterns they notice in the context of their investigative question.
Latest cohort: 51.9% reached Achieved.
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Try Kuraplan freeTeacher's guide: plan units, generate resources, benchmark your class against 38,008 candidates from 2024. All data pulled live from NZQA — last verified 20 May 2026.
Level 1 Mathematics
School-based, no exam
Term 1 or 2 timetable
38,008 candidates
This standard asks students to investigate a real research question by collecting data, presenting it clearly using graphs or charts, and explaining what patterns or features they have found. Students work through the full statistical enquiry process — from deciding what data they need, to presenting it visually, to writing about what it tells them in the context of their question.
Full title: “Explore data using a statistical enquiry process”
Pick the depth that matches your timetable. Each option generates a ready-to-teach plan in Kuraplan, free.
Full PPDAC enquiry sequence — investigative question prompts, data source library (Stats NZ, NIWA, sport), visualisation modelling and three formative drafts before submission.
Generate unit planDrop-in lesson on a specific enquiry skill (posing an investigative question, choosing the right graph, describing centre and spread in context) with worked example and exit ticket.
Generate lessonPrint-ready check-in covering the PPDAC stages, a worked visualisation choice, and a graded sample analysis paragraph for students to critique before drafting their own.
Generate worksheet91944 was introduced under the NCEA Change Programme and had its first full national assessment in 2024. The history below shows both the 2023 pilot cohorts and the 2024 full rollout. Use the full-cohort row as your moderation reference and re-check this page annually as NZQA publishes more data.
| Year | Candidates | Achieved | Merit | Excellence | Not Achieved | Pass % |
|---|---|---|---|---|---|---|
| 2024Full national cohort | 38,008 | 51.9% | 19.2% | 9.4% | 19.6% | 80.5% |
| 2024Secondary stream | 4,869 | 47.5% | 21.4% | 12.4% | 18.6% | 81.3% |
| 2023Pilot cohort | 2,083 | 42.2% | 27.8% | 12.6% | 17.3% | 82.6% |
| 2023Pilot cohort | 616 | 43.5% | 20.6% | 10.2% | 25.6% | 74.3% |
Source: NZQA national achievement statistics for Standard 91944, filtered to result sets exceeding 300 candidates. Pulled from the NZQA data feed on 20 May 2026.
What separates an Achieved investigation from Merit, and Merit from Excellence in an internal moderation meeting. Share these with students before their first formative draft — clear grade boundaries lift the bottom of the class faster than any other intervention.
Students explain their data source, present it with at least one appropriate visualisation, and describe patterns they notice in the context of their investigative question.
Latest cohort: 51.9% reached Achieved.
Students connect ideas throughout the investigation and justify their observations using both visualisations and statistical measures (such as centre, spread, or comparison of groups), rather than describing features in isolation.
Latest cohort: 19.2% reached Merit.
Students combine statistical knowledge with real-world context, draw insightful conclusions that go beyond surface description, and reflect thoughtfully on how well their enquiry process actually answered the original question — including limitations of the data.
Latest cohort: 9.4% reached Excellence.
The five concrete skills behind a Merit-or-better 91944 investigation. Build your unit's success criteria from this list.
Pose an investigative question that can genuinely be answered with data, then explain clearly where the data came from and why it is suitable for that question
Collect or source enough data with a good range of values to actually analyse — surveys, simple experiments, or existing real-world datasets (Stats NZ, sport, climate, school context)
Present the data using at least one appropriate visualisation (dot plot, bar chart, box plot, scatter plot) chosen to suit the variable type rather than defaulting to whatever is easiest
Describe the key features and patterns in the data using statistical language — centre, spread, shape, unusual values — and connect each observation back to the original investigative question
Follow a logical statistical enquiry process throughout (Problem → Plan → Data → Analysis → Conclusion), showing how each step connects to the next rather than treating them as isolated tasks
The three common mistakes that pull investigations from Merit down to Achieved (or worse). Pre-teach against each one in the first week of your unit.
Not explaining where the data came from or why it is suitable for the investigation — students jump straight to graphs without justifying their source, sample size or method
Choosing weak or inappropriate visualisations (a pie chart for continuous data, a bar chart with no axis labels) that do not clearly show the patterns the question asks about
Describing what they see in the graph as a standalone observation ("the bar is higher") without ever connecting it back to the original investigative question or the real-world context
91944 sits alongside the other three achievement standards in the new Level 1 Mathematics & Statistics matrix. Most departments pair it with 91945 in the first half of the year, then prepare students for the two externals (91946 and 91947) across Terms 3 and 4.
5 credits · Internal assessment
5 credits · External assessment
5 credits · External assessment
Want full unit plans for any of these? Generate a Level 1 Mathematics programme in Kuraplan.
The admin work behind a well-run internal standard — automated in Kuraplan so HoDs and lead teachers spend their time on teaching, not reporting.
Auto-generate a Board-of-Trustees-ready report comparing your cohort against national 91944 pass rates by gender and ethnicity.
Pre-submission parent email explaining the standard, the investigation schedule, and how whānau can support data collection at home.
Drop-in pack: one full 91944 lesson on choosing a visualisation, a worked sample paragraph, and a 15-minute extension activity. Print and go.
Three sample investigations at Achieved, Merit and Excellence with annotated grade reasoning — built for departmental moderation meetings.
Standard 91944 is worth 5 credits at NCEA Level 1 and is internally assessed across the school year (no external exam). It is one of the four achievement standards in the new Level 1 Mathematics & Statistics matrix introduced under the NCEA Change Programme, and contributes towards Level 1 numeracy when delivered alongside the Common Assessment Activity.
Based on the first full national cohort in 2024, the pass rate (Achieved + Merit + Excellence) was 80.5% across 38,008 candidates. Merit + Excellence combined was 28.6%. Because 91944 only had its first full assessment in 2024, treat these numbers as a baseline rather than a long-running trend — re-check them annually as NZQA publishes more data.
The strongest student investigations tend to use real, locally relevant data — school sport stats, climate data from NIWA, Stats NZ surveys, Pasifika community surveys, or simple in-class measurements (reaction times, hand spans). Avoid investigations that rely on small, made-up datasets, or yes/no survey questions that produce only categorical data with two values — there is not enough variation for students to describe centre, spread or shape, which limits the analysis they can write.
Plan for a written report of roughly 1,000–1,500 words plus 2–3 visualisations. The standard rewards depth of statistical reasoning, not length — examiners flag reports that pad with screenshots or unnecessary commentary. Train students to spend more time on the analysis and conclusion sections than on plan or data collection, where most students lose marks by under-explaining their source.
Students describing graphs as standalone observations ("the bar is higher", "there is a peak around 20") without ever connecting back to the original investigative question. The fix is explicit scaffolding: every analysis paragraph must follow a three-step pattern — name a feature (centre, spread, shape, unusual value), use a specific value from the data, then explain what it means for the original question in context. Build a single shared exemplar paragraph in week 1 and refer back to it every lesson.
91944 is the data-focused achievement standard in the new four-standard Level 1 matrix. Most departments pair it with 91945 (Aotearoa-context maths problems, also internal) early in the year, then use Term 3 and Term 4 to prepare students for the two external standards — 91946 (mathematical reasoning in context) and 91947 (mathematical reasoning). The two internals together give students a 10-credit buffer before the externals, which is why most schools front-load 91944 in Term 1 or 2.
Plan for roughly 5–6 weeks of timetabled lessons. The standard is internally assessed, so you control the pacing — most schools run 2 weeks of statistical enquiry process teaching, 1–2 weeks of guided investigation work, then 2 weeks of independent investigation and write-up. Avoid compressing it into less than 4 weeks: students need at least one feedback cycle on a draft before submission to lift the Achieved cohort towards Merit.
NZQA publishes annotated student exemplars for every internal standard at nzqa.govt.nz under 'View standard 91944 → Internal Assessment Resources & Exemplars'. Because 91944 is a relatively new standard, also check the Te Poutāhū Curriculum Centre and NZAMT for community-shared exemplars — these are particularly useful for calibrating the boundary between Merit and Excellence, which examiners report is the hardest call in the new Level 1 matrix.
Kuraplan generates a full Year 11 Mathematics 91944 unit plan — with PPDAC scaffolds, modelled paragraphs, formative drafts and moderation packs — in under 60 seconds. Free for individual teachers, school plans for departments.
Source of truth: NZQA standard 91944. View on nzqa.govt.nz . Data on this page is for planning use — always cross-check the current assessment specification before finalising a unit. Te reo Māori — Aotearoa.