Dr' Martin Schrepp SAP AG

1
A GOMS Model for Keyboard Navigation in Web Pages
and Web Applications

• Dr. Martin SchreppSAP AG
• Patrick FischerUniversity of Mannheim

2
Overview

• Introduction
• GOMS models for mouse and keyboard navigation
• A study to estimate the parameters of the GOMS
  models
• An example for the comparison of mouse and
  keyboard navigation
• Conclusions

3
Introduction

• An unlimited keyboard support is one of the main
  accessibility requirements for web pages and web
  applications
• Users must be able to reach all interactive
  elements of a page (links, fields in online
  forms, etc.) by keyboard actions
• Users must be able to perform all possible
  actions on the page (follow a link, press a
  button, etc.) using the keyboard
• But it is not sufficient that all active page
  elements are available over the keyboard. It is
  important that users are able to navigate a page
  using the keyboard with acceptable performance.
• Performance of keyboard navigation is especially
  important for web applications
• Users work with those applications on a daily
  basis
• It is, for example, not acceptable that a task
  which can be solved using the mouse in 1 minute
  requires 10 minutes if the user is restricted to
  use the keyboard
• If we fail to provide an efficient keyboard
  support we exclude disabled persons from working
  with the software, even if it is accessible
  accordingly to the common accessibility
  guidelines

4
What does efficient keyboard support mean?

• A user must be able to navigate in a web page or
  web application using the keyboard with
  sufficient performance.
• A natural criterion to decide if keyboard
  navigation is efficient is to compare it to mouse
  navigation.
• Let k be the time required by an experienced user
  to finish a task using the keyboard and m be the
  time necessary to finish the same task using the
  mouse and the keyboard.
• We can define that keyboard support is sufficient
  if k lt c m.
• Here c is a constant, which depends on the usage
  scenario. Thus, for a news page on the web
  obviously a higher value is acceptable for c than
  for a web application which is used for
  professional work.

5
GOMS models

• We need thus a method to compare mouse and
  keyboard navigation.
• In principle this can be done with user tests,
  but this requires a huge effort.
• A cheap method to compare different designs
  concerning their efficiency is the GOMS model
  (Goals, Operators, Methods and Selection rules).
• A GOMS model allows to predict how long an
  experienced user needs to perform a given task in
  a given interface design.
• The central idea of the GOMS model is that the
  time necessary to perform a certain task is the
  sum of the times of the elementary actions
  (pressing a button, moving the mouse cursor to a
  certain place at the screen, clicking on a link,
  etc.) required to finish the task.
• Different users will need different times for
  these elementary actions. But for a comparative
  analysis of screen designs it is sufficient to
  use a set of typical or average times for the
  elementary actions. These average times are
  typically determined in laboratory experiments.

6
A GOMS model for mouse navigation

• Task for the user Follow a link on a given page.
  
• If the user works with the mouse this can be
  split into 3 sub-tasks
• locate the target link on the page
• move the mouse focus to the target link
• click on the target link
• The total time t to perform this task can thus be
  estimated as
• t t1 t2 t3
• where
• t1 is the time required to locate the target link
• t2 is the time required to move the mouse to the
  target link
• t3 is the time to click on the target link
  (cognitive time to decide if the link is the
  correct target manual execution time for the
  click)

7
A GOMS model for keyboard navigation

• Task for the user Follow a link on a given page.
  
• If the user works with the keyboard this can be
  split into 3 sub-tasks
• locate the target link on the page
• press n-times the TAB key to place the cursor
  focus on the link
• follow the link by pressing the ENTER key
• The total time t to perform this task can thus be
  estimated as
• t t1 n t4 n p t5 t6
• where
• t1 is the time required to locate the target link
• t4 is the time required to press the TAB key
• p is the probability to loose the cursor focus
  during navigation
• t5 is the time required to locate the lost cursor
  focus again
• t6 is the time to follow the target link by
  pressing the ENTER key (cognitive time to decide
  if the focussed link is the target manual
  execution time to press ENTER)

8
A study to estimate the model parameters

• Task of participants Navigate to a link on a web
  page using only the keyboard. Navigation was only
  possible over the TAB chain, i.e. the pages
  contained no keyboard shortcuts or access keys.
• Participants
• 10 experienced computer users (age 25 - 43 years)
• Material
• 15 common German web pages (web shops,
  information pages of companies, web pages of
  television channels, etc.)
• For each page a target link for the navigation
  task was identified
• The number of links on the pages varied between
  38 and 200
• The number of TAB presses necessary to reach the
  target link varied between 14 and 119

9
A study to estimate the model parameters

• Procedure
• The task and the navigation over the TAB key
  respectively the key combination SHIFT TAB was
  explained in the instruction.
• Each participant solved the navigation task for
  10 web pages (randomly determined per
  participant). The first two pages were trial
  pages (not included in data analysis) so that
  participants could get familiar with this type of
  navigation.
• All 10 web pages could be started over a link
  from the instructions page. These links were
  embedded in a short text which named the target
  link on the page.
• When the participant clicked on such a link, the
  corresponding web page was loaded and the
  participant could start to solve the navigation
  task for this page.
• Measurement was done in the background by a tool
  which was installed locally on the test computer.
  This tool captured all keyboard events of the
  participant and the corresponding system time.
• After the participant has clicked on the target
  link in a test page, he or she was instructed to
  close the browser window.
• The participant was then automatically redirected
  to the instruction page and could start the next
  page in the sequence.

10
Screen flow in the study
Instruction page
Test page 1
Navigate to target using TAB
Instruction text
Target link
Text which explains the target for Link 1
Link 1
Target page
. . .
Close window redirects to instruction page
Text which explains the target for Link 10
Link 10
11
Data analysis

• The time necessary for each keyboard action is
  calculated as the difference of the captured
  system times between two successive keyboard
  actions.
• Parameter estimation
• t1 (time to locate the target) is estimated as
  the average time difference between loading of
  the page and the first hit on TAB minus 200 ms
  (manual execution time to press TAB)
• t6 (time to follow the link by pressing ENTER) is
  estimated as the average time difference between
  the last hit of TAB (sets the focus on the target
  link) and the hit of ENTER
• Differences between TAB events were ordered
  accordingly to their size and analysed by the
  Nalimov test. Detected outliers were identified
  as focus losses. Their average is the estimate
  for t5 and their frequency is the estimate for p.
  
• The average of all other times is the estimate
  for t4 (time required to press TAB).
• Nalimov Test This statistical test is designed
  to detect outliers in the data. A value is called
  an outlier, if the hypothesis that it belongs to
  the population can be rejected with a risk of
  error smaller than a defined probability a (we
  used a 0.1 in our study).

12
Results

• We got the following estimates for the
  parameters
• t1 9.6 sec. (locate target)
• t4 0.27 sec. (press TAB)
• t5 2.61 sec. (locate lost cursor focus)
• t6 1.13 sec. (press ENTER to follow link)
• p 3.18 (prob. to loose cursor focus)
• Focus losses occur relatively seldom, but consume
  20.71 of the total time subjects needed to solve
  the navigation task.
• The initial location of the target accounts for
  33.87 of the total time subjects needed to solve
  the navigation task.

13
An Example

• We have a web page with 100 links which has not
  implemented any shortcuts or access keys. Thus,
  keyboard navigation must be done over the TAB
  chain.
• If users of this page select all links with the
  same probability, then the expected time to
  detect and follow a link using the mouse is in
  average 11.83 seconds. The expected time required
  for this navigation task using the keyboard is
  28.56 seconds.
• If we want to achieve that the performance of
  keyboard users should not exceed two times the
  performance of mouse users we can conclude that
  we must implement additional keyboard support,
  for example access keys.

14
Conclusions

• We presented GOMS models for mouse and keyboard
  navigation in web pages and web applications.
• These models can be used to compare keyboard
  navigation with mouse navigation.
• Such a comparison enables us to decide if the
  amount of keyboard support for a web page or web
  application is sufficient or if the disadvantage
  for keyboard users is not acceptable.
• The model was already used in practice to support
  the design of the keyboard navigation model for a
  SAP application.