Year 5 · 65 minutes · Similarity
Who decides what a good match looks like?
Our fictional books have two features: length and adventure level. A request is a point on the same map. Weighted distance squares the differences, multiplies them by chosen weights and adds them. Changing a weight stretches one direction of the map and can reorder recommendations. The nearest point is best only according to those features and weights; it says nothing about an unrepresented quality such as accessibility.
Print the six fictional book records. Work through one squared-distance calculation with equal weights. Clarify that adventure scores are supplied invented metadata, not reader judgements collected from students.
Measure distance on a feature map. Useful earlier investigations: y2-creature Use pairs with predictor/operator roles. Swap after the first comparison. Each learner draws or writes their own explanation using one exact case.
Australian Curriculum Version 9 · Digital Technologies: AC9TDI6P01, AC9TDI6P06. Selected aspects only. This activity contributes evidence; it does not cover the full descriptor or achievement standard. A programming descriptor is not claimed for merely moving controls. ACARA AI curriculum connection · V9 Technologies These are planning connections, not ACARA endorsement or exhaustive descriptor alignment.
Draw two book points and a requested length/adventure point.
Ask: “Which book is closest using both directions?”
Listen for: “We need to consider both differences.”
Predict the leading book when the length weight increases with request fixed.
Ask: “Which difference now costs more?”
Listen for: “Being far from the requested length.”
Move the request, inspect linked distance segments and then freeze it while changing one weight. Record three rank lists.
Ask: “Did the books change when the ranking changed?”
Listen for: “No, the rule for comparing them changed.”
Read the edge-case reader who needs large print. No map feature represents it.
Ask: “Can the smallest distance guarantee a suitable book?”
Listen for: “No, it ignores print accessibility.”
Choose weights for a stated fictional request, then add a human-check field for an omitted need. Justify one trade-off numerically.
Ask: “What can your score claim, and what must someone still check?”
Listen for: “It matches the two features; someone must check accessibility.”
Submit a fixed-query comparison and limitations note.
Ask: “Would another reasonable person choose different weights?”
Listen for: “Yes, if their priorities differ.”
Closest means objectively best.
Increase the length weight while the request and all book records remain fixed. Predict which rank changes first.
The nearest book can fail an unrepresented accessibility requirement.
Choose a transparent weighting and a separate human check for an omitted need; reproduce the ranking from distances.
Ask the learner to calculate the two feature contributions for the leading book. Check they distinguish the score’s claim from overall suitability.
Use integer coordinates and squared-distance sums without square roots. Offer a printed coordinate table.
Compare Euclidean and Manhattan distance for the same points and identify a ranking disagreement.
An annotated recommendation map with weights, a ranking comparison and an omitted-needs check.
No reading histories or student preference profiles are collected. All books and requests are fictional.
Compute weighted distances for a large synthetic catalogue on MPS/CUDA. Move the query and inspect recommendation stability over six feature-weight settings; repeat on CPU for comparison.
| Criterion | Beginning | Secure | Extending |
|---|---|---|---|
| Distance reasoning | Uses visual proximity only | Explains weighted contributions | Reproduces a rank change numerically |
| Value critique | Treats rank as objective quality | Names an omitted need | Designs and tests a complementary check |
Australian Curriculum Version 9 · Digital Technologies
References: AC9TDI6P01, AC9TDI6P06. Read the current source (checked 2026-09-07).
Evidence to assess: An annotated recommendation map with weights, a ranking comparison and an omitted-needs check.
Selected aspects only. This activity contributes evidence; it does not cover the full descriptor or achievement standard. A programming descriptor is not claimed for merely moving controls. Moderate the supplied illustrative responses against your school unit and current achievement standard.
These are planning estimates to test with your class. A short session develops one supported claim; it does not compress the whole senior project.
| Stage | 45 minute focus | 60 minute investigation |
|---|---|---|
| Readiness and prediction | 0–5 | 0–5 |
| Trace the supplied example | 5–13 | 5–15 |
| Author and run cases | 13–25 | 15–35 |
| Counterexample and redesign | 25–35 | 35–45 |
| Explain and discuss | 35–42 | 45–55 |
| Export and handover | 42–45 | 55–60 |
For a longer project, use three 50-minute sessions. Session 1 (0–50): readiness, model, hypothesis and initial cases. Export a project and record the next test. Session 2 (50–100): reopen, check settings, author counterexamples and revise the design. Export the changed project and identify unresolved evidence. Session 3 (100–150): independent peer test, final artefact, individual explanation and moderation. If using two 60-minute sessions, stop at minute 60 after saving the first comparison; use 60–120 for redesign, independent test and defence.
Entry check: Measure distance on a feature map. Ask the learner to demonstrate it before choosing the level of support.
Preparation: allow about 15 minutes to run the starter, print the cards and check a project can be reopened. This estimate has not yet been measured in a classroom pilot.
Read the entry question aloud, model one row, and label the units. Offer the case table as a large-print sheet. Keep mathematical derivations optional until the learner can explain the comparison.
For one device, use a projector: one pair predicts, one operates, and the class records on paper. Swap roles after the first comparison. For individual access, support keyboard controls and a written table equivalent to each visual. Learners may explain orally or with an annotated diagram. Never require personal data, a recorded voice, or a photograph.
Mixed readiness: if the entry check is difficult, use the linked prerequisite and the first two case cards; retain the same central question. If secure, ask the learner to design an unseen test and state which explanation it could disprove.
Rank books by weighted squared distance, with an optional accessibility requirement before ranking.
Starting parameters: Wanted length = 4, Wanted difficulty = 3, Difficulty importance = 1, Require accessible format = True
4 cases calculated from your supplied inputs. Compare the evidence with your prediction.
| book | eligible | distance |
|---|---|---|
| Reef tales | True | 2 |
| Bush poems | True | 5 |
| Long voyage | True | 50 |
| Bird atlas | False | 20 |
These are authored examples, not work collected from children. Assess reasoning using the lesson rubric, not whether the first prediction was correct.
Beginning: “It worked because the result looks right.” This identifies no exact case, control or measurement. Ask the learner to point to one row and say what happened.
Developing: “In the first case I recorded book: Reef tales; eligible: True; distance: 2.” This cites evidence, but does not yet explain how the result follows from the rule. Ask the learner to trace the relevant step.
Secure: “For the first supplied case, book: Reef tales; eligible: True; distance: 2. I can trace it using this mechanism: Rank books by weighted squared distance, with an optional accessibility requirement before ranking. My result supports a claim about these supplied cases. It does not establish that the same result holds outside them.” Look for an accurate trace, the actual settings and a bounded claim; accept equivalent oral or visual evidence.
Extending: The learner constructs and reruns a new case, reports whether the first explanation survives, and defends a revised design. Use this concrete challenge: Define two book features and a reader need. Find a recommendation that is close but unsuitable. Require the original and changed evidence and this boundary: Distance represents the chosen features, not every reader need or book quality.
Moderation: first assess independently against each lesson criterion. Compare the exact trace or artefact that led to your judgement. Resolve differences using evidence, not polished language. Keep each learner's individual explanation even when the artefact was produced in a group.