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7.3 Multi-Attribute Pattern Rules

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ADF YOU Session Job Opportunities Assessment

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1 Introduction & JOA Overview

1.1 What the JOA Is and Why the ADF Uses It 1.2 Current Exam Facts (51 Questions, 20 Minutes) 1.3 JOA vs YOU Session vs the Wider Process

2 Logistics, Access & Attempt Rules

2.1 Access, Devices & Browser Setup 2.2 Three Attempts & Six-Month Wait 2.3 After the JOA: JOR and Recruiter Contact

3 Official Tips & Test-Day Strategy

3.1 Official Top Tips & Natural Ability 3.2 Pacing, Flagging & Order of Attack 3.3 Integrity, Help Rules & Supervised Verification

4 Numerical Reasoning: Series & Matrices

4.1 Number Series Patterns 4.2 Number Matrices & Missing Values 4.3 Numerical Speed & Estimation Under Time

5 Numerical Reasoning: Word Problems

5.1 Rates, Distance & Averages 5.2 Ratios, Proportions & Percentage Reasoning 5.3 Multi-Step Numerical Reasoning

6 Verbal Reasoning

6.1 Word Meaning & Relationships 6.2 Verbal Analogies 6.3 Verbal Odd-One-Out 6.4 Verbal Logic & Multi-Statement Proofs

7 Abstract Reasoning: Sequences & Rules

7.1 Sequence & Next-Item Patterns 7.2 Rotation, Reflection & Orientation 7.3 Multi-Attribute Pattern Rules

8 Abstract Reasoning: Odd-One-Out & Complex Figures

8.1 Shape Odd-One-Out 8.2 Complex Figures & Spatial-Style Abstract Items 8.3 Abstract Speed Habits

9 Integrated Prep & Common Traps

9.1 Mixed Timed Practice 9.2 Common Traps Across All Item Types 9.3 Day-of Checklist

10 Results & Next Steps

10.1 Understanding the Job Opportunities Report 10.2 Pathway After the JOA

7.3 Multi-Attribute Pattern Rules

Key Takeaways Explain This Topic AI

Multi-attribute abstract items layer two or more independent change tracks—commonly count, position, shading, size, and orientation.

The name-the-change method lists each attribute’s state per frame, then writes a one-line rule per attribute before combining them.

Distractors usually get one attribute right and another wrong; scoring your prediction attribute-by-attribute catches half-right traps.

Prefer the smallest set of rules that fits every frame; do not add a third track the strip never uses.

When layered rules will not separate within ~35–40 seconds on the JOA, flag and protect overall throughput.

Last updated: August 2026

When one rule is not enough

Many JOA abstract items—especially harder sequence and matrix-style figure sets—change more than one property at a time . Official familiarisation themes include dot patterns and shape sequences where quantity, placement, and appearance can all matter. These are still tests of natural reasoning under time , not art criticism and not a school design syllabus.

A multi-attribute rule is simply several simple rules running in parallel. Candidates fail when they track only the loudest feature (usually size or count) and ignore a quieter one (shading schedule or position path).

The name-the-change method

Use this exact structure on layered strips. It is the abstract twin of listing first differences in number series.

Step 1 — Inventory attributes

For each figure, note only features that can change:

Attribute Questions to answer

Count How many dots / shapes / lines?

Position Where is each element? Path?

Shading / colour Empty, half, full, black/white?

Size Small / medium / large steps?

Shape type Triangle, square, circle…?

Orientation Facing which way?

Arrangement Row, column, diagonal, clustered?

You will not need every row every time. Cross out attributes that stay constant across all given figures—they are background , not rules.

  • Step 2 — Build a state table (mental or scratch)
  • Example skeleton: Frame | Count | Position | Shading | Size
  • 1 | 1 | top-left | white | S
  • 2 | 2 | top-left+right| black | S
  • 3 | 3 | top row+BR | white | S
  • Step 3 — One-line rule per active column
  • Count: +1 each step
  • Position: fills clockwise from top-left
  • Shading: toggles white/black
  • Size: constant (ignore)
  • Step 4 — Synthesise the next frame

Apply each one-line rule once. Then find the option that matches all predicted attributes.

Step 5 — Half-right audit

Before clicking, ask: “Is there an option that matches count but wrong shading?” If yes, you nearly got trapped—confirm every track.

  • Worked examples (original, fully described)
  • Example A — count + position (classic dots)

Strip: 2×2 grid of cells.

  • Figure 1: one black dot in top-left cell
  • Figure 2: black dots in top-left and top-right
  • Figure 3: black dots in top-left , top-right , and bottom-right

Figure 4: ?

Name-the-change:

  • Count: 1 → 2 → 3 → 4
  • Position: cells fill in clockwise order starting top-left → next adds bottom-left
  • Shading: all dots black (constant)

Next: four black dots, one in each cell.

Distractors: three dots with bottom-left instead of bottom-right (wrong path); four dots with one white (invented shading).

Example B — size + shading

Strip: a single circle, no grid.

  • Figure 1: small circle, empty
  • Figure 2: medium circle, filled black
  • Figure 3: large circle, empty

Figure 4: ?

Rules:

Size: S → M → L → (if only three sizes cycle, next might return to S , or if the scale continues and options show “extra large,” only choose XL if the stem’s option set supports a fourth size—otherwise prefer a 3-cycle return to small when that matches options)

Shading: empty → full → empty → full (toggle)

Suppose options include “small filled” and “large filled.” With a 3-size ladder and only three figures, the size rule may be strictly increasing with no fourth size shown—then inspect whether the question is next-item with options limited to S/M/L. If L is already used and no XL exists, cycling S after L is the clean continuation: small + filled .

Lesson: multi-attribute does not mean unlimited invention; size and shading each need a schedule supported by frames and options.

Example C — orientation + count of marks

Object: a square pointer (arrow-like chevron) with tick marks on the base.

  • Figure 1: points up , one tick on the base
  • Figure 2: points right , two ticks
  • Figure 3: points down , three ticks

Figure 4: ?

Rules: +90° CW orientation; tick count +1.

Next: points left , four ticks.

Half-right traps: left with two ticks; up with four ticks; left with three ticks.

Example D — three tracks (count, position path, fill of centre)

Strip: large circle with orbit positions at 12, 3, 6, 9 o’clock and a centre that can be empty or filled.

  • Figure 1: one small dot at 12 o’clock ; centre empty
  • Figure 2: two small dots at 12 and 3 ; centre filled
  • Figure 3: three small dots at 12, 3, and 6 ; centre empty

Figure 4: ?

Rules:

  • Count of orbiting dots: +1 each step → four
  • Positions: add next clockwise hour point each step → add 9 o’clock (now dots at 12, 3, 6, 9)
  • Centre fill: toggles empty/filled → next filled

Next: four orbiting dots at cardinal positions, centre filled.

If an option has four dots but skips 9 o’clock and doubles 3 o’clock, count is right and path is wrong—reject.

Example E — constant vs changing (avoid phantom tracks)

Strip:

All figures are blue-outlined squares (colour constant—if the real test is black-and-white, treat outline style as constant)

  • Inner shape: triangle → triangle → triangle (shape constant)
  • Only the triangle’s pointing direction and a corner dot count change

Do not invent a “square is slowly becoming a circle” story. Name-the-change begins by deleting constants so working memory holds only active rules.

Example F — matrix-style multi-attribute (rows and columns)

Sometimes abstract items appear in a 2×2 or 3×3 grid of figures with one cell missing (visual analogue of number matrices in chapter 4).

  • Described 2×2: [ small white circle ] [ large white circle ]
  • [ small black circle ] [ ? ]

Row logic candidate: left → right doubles size; shading stays constant within a row.

Column logic candidate: top → bottom toggles shading; size stays constant within a column.

Then ? should be large black circle (large from the top-right size track; black from the left-column shading track).

Verify: top row both white ✓; left column both small ✓; right column both large once ? is large ✓; bottom row both black once ? is black ✓.

Grid multi-attribute items reward checking two directions , just like number matrices.

Priority order when overloaded

Under ~20–25 seconds of confusion, inspect attributes in this order (adjust if one feature screams):

  • Count (fastest to quantify)
  • Shading / fill (usually binary or short cycle)
  • Position / path
  • Orientation
  • Size
  • Shape type

If two attributes already determine a unique option, confirm the others are at least not contradicted , then commit.

Distractor engineering you should expect

  • Distractor type Looks like Defence
  • One-track correct Right count, wrong place Attribute audit
  • Overshoot Applied +2 when rule is +1 Re-count steps
  • Direction reverse Anti-clockwise path Trace path on all frames
  • Phantom feature Adds stripes never seen Delete constants first
  • Swapped schedules Uses shading rule for size Keep separate one-liners
  • Matrix row-only Fits one row, breaks column Check both directions
  • Timing model for layered abstract items

Multi-attribute sequences are among the stickier abstract family members on a mixed JOA paper.

  • Case Budget
  • Two obvious tracks ~20–30s
  • Three tracks or matrix dual logic ~30–40s
  • No stable table by ~40s Flag

Do not let a beautiful three-track puzzle steal the time that would have secured two easier verbal or numerical marks. Official guidance emphasises completing as many as possible in 20 minutes; finishing all 51 is uncommon.

Realistic scenario

Jordan notices dots increasing and stops. Jordan picks an option with the right number of dots in a straight line, but the strip filled corners of a square clockwise. The option is a designed half-right trap. Name-the-change would have forced a position line in the state table and blocked the trap.

Practice routine that builds layered fluency

In review, force a written state table for every multi-attribute miss (30 seconds of structure beats 5 minutes of staring).

Cover the options, predict each attribute of the next figure, then uncover.

Drill pairs: (count+position), (orientation+shading), (size+count), then triple combinations once doubles are solid.

Interleave with 7.1 pure sequences and 7.2 orientation-only strips so you can classify item type before diving into full tables.

Keep prep aligned to numerical + verbal + abstract mixed timing—not retired two-test maths curricula.

Linking the whole abstract sequences chapter

Section Core question

7.1 What single progression produces the next item?

7.2 How does orientation change—turn or flip, by how much?

7.3 Which attributes move together, on which schedules?

Chapter 8 will extend abstract skill into shape odd-one-out , complex figures , and abstract speed habits . The shared discipline remains: describe the figure, name the rule, verify on all evidence, decide or flag.

Before leaving 7.3, lock the mantra: One line per attribute; all lines must fit; options must match every line. That is multi-attribute abstract reasoning on the JOA.