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ARMH: Fitts’ Law Paul Cairns [email protected]

ARMH : Fitts ’ Law

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ARMH : Fitts ’ Law. Paul Cairns [email protected]. A law?!?!. One of the few in HCI Predictive Reliable Valuable research tool!. Today’s objectives. Fitts’ Law Theoretical basis Adaptations for HCI Implications for design Thoughts on modelling. Overview. Model for prediction - PowerPoint PPT Presentation

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Page 1: ARMH :  Fitts ’ Law

ARMH: Fitts’ Law

Paul [email protected]

Page 2: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

A law?!?!

One of the few in HCI Predictive Reliable Valuable research tool!

Page 3: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Today’s objectives

Fitts’ Law Theoretical basis Adaptations for HCI Implications for design Thoughts on modelling

Page 4: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Overview

Model for prediction Time to point Difficulty of target

Page 5: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

A demo

Interactive Fitts' Law talk– Not quite accurate!

Page 6: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Fitts’ Proposed Law

D 1/W a, b Log?

T a b.log 22DW

Page 7: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Theory (or Analogy?)

Analogy with Shannon information

Meyer’s derivation MacKenzie’s improvement

C B.log 2S NN

T a b.log 2D WW

Page 8: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Terms

Index of difficulty– bits

Index of Performance, 1/b– bits per second

ID log2D WW

log2DW

1

Page 9: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Impact in HCI

Reduce ID– Bigger icons, more space

Compare IP– “Capacity” of input devices

Put things in edges and corners

Page 10: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Deconstructing Fitts

Ecological validity Construct validity

Page 11: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

What Fitts did:

D

W

Page 12: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Let’s have a go!

Page 13: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

What we apply it to:

Page 14: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Correcting for W

W’ – actual cross-section Smaller of W and H Area, W x H Sum, W + H Stick with W Which is best?

Page 15: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Implications debunked

Edges are better Corners are best Mice are non-linear anyway!

Page 16: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

What remains?

D/“W” is key – Target size (angle)– Stopping range (proportion)

Non-linear (concave), monotonic– Quite possibly log function

IP is meaningful a is important

Page 17: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Toolbars

This is annoying not useful

Edges and corners?

Page 18: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Novel interactions

Artificially increasing W– “Sticky” buttons– Bubbles

Changing select– Goal-crossing

Page 19: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Novel devices

Comparing IP– iPhone– Wii– Kinect– Eye Gaze

Page 20: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Thoughts on Modelling

Is it a good model?– Yes, it fits the data– No, we don’t know why!

Could we produce a better one?– How?

Page 21: ARMH :  Fitts ’ Law

ARMH: Fitts' Law

Advanced Fitts’ Law

Fitts’ law as a model Steering law– Games– Menu navigation– VE/VR?

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ARMH: Fitts' Law

Reading for today MacKenzie (1992) Fitts’ Law as a

Research and Design Tool…, HCI (7), 91-139

MacKenzie & Buxton (1992) Extending Fitts’ Law to 2d tasks, CHI 1992, 219-226

Interaction Design, 2nd edn Cockburn & Firth (2003) Improving the

acquisition of small targets. BCS HCI 03, 181-196

Accot & Zhai (1997) Beyond Fitts’ Law… ACM CHI 97, 295-302