Behavioral Aspects of
Text Editors
David W. Embley, George Nagy
University of Nebraska, Lincoln
Assumptions for readers
• Familiar with basic vocabulary of computer
• Sufficient exposure to various text and
program editors
• Innocent of any formal training in psychology
Interactive Text Editors
• Frequently, Primary means of interaction with
Manuscript creation
File System Maintenance
• Important to make their use easy
• Editors
– General Purpose Interactive editors
– Language dependent editors
Editor Design and Evaluation
• Everyone has an opinion, but no consensus
• Some established means:
– Introspection ?
– Field Studies/Observations
– Formal Analysis
– Controlled Experiments
– Psychological Models
Our own intuition and experience, is what we
depend on when we assume that we know as much
about the topic as the next person and are too lazy
to look further
Psychological Models
Characterize human performance
Goal: To predict human behavior in a restricted
environment while performing a set of tasks
Example ( of an editing task)
Applicable areas of Psychology
• Cognitive Psychology
– Study of higher mental processes
• Well studied area but limited application to
study of text editors
• Section 1 : Temporal Models
• Section 2: Impact of Editor structure and
command languages
– How do different editors differ ?
• Section 3: Stimulus and response studies of
input devices : Mouse wins
Performance Time
• To minimize the time incurred by a user performing
a number of editing tasks over a period of time
• Depends on numerous factors
Expertise of the user
Learning methods and procedures
User alertness and motivation
Out of Paper
• Some are within our control and can be improved
Predictive Models
The Keystroke Model [CARD]
Total time = sum of time required to perform individual unit tasks
To acquire a mental
representation of the task
Perform and execute it
• Replacing one word of arbitrary length with a
five letter word
Model Verification
• 12 subjects, 4 different editing tasks, 3
different editors
• Tasks:
– Simple word substitution
– Moving a sentence
• Observed times and predicted times match
• Exploring More or less detailed models [CARD]
The Embley Model
• A simpler model for line-oriented editors
• Objective
– Comparing program editor performance as a
function of time required by a user to perform
editing tasks
The Model
Acquisition time and mental time combined
m = number of command response pairs
Tc = delay per command = mental prep. Time +
computer response time
n = number of keystrokes
Tk = time per keystroke
GOMS Model
• Attempts to explain How an expert user
accomplishes routine editing tasks, not just
time constituents
Can adjust to desired level of detail
• Example
Specify substitute command – specify argument number 1 - specify
argument number 2 – enter command
Which one is more accurate ?
Experimental Studies
• Several variations were explored
• 10 different GOMS models
– 16 second operator duration, 8, 4, 2, 0.5 ( “type an ‘s’,
home hands on keyboard)
• 5 participated, only 1 studied
Derivation Data
Prediction rules for operator sequences
Estimates for operator duration
For calculation of unit task time
using derivation data results
Predicting the task accomplishment method
• Objective: To determine whether a set of
simple selection rules could account for the
methods user select.
• The Experiment
– 3 subjects
– Teletypewriter and CRT
• Each subject appeared to have a dominant
method – the first rule
• S2 applied different dominant method for
different devices – speed difference
• Selection of methods depends on feature of
task – e.g. :
– Locating a line : number of lines between
current line and target line
Users are able to quickly select near-optimal methods by having
assimilated heuristic rules based on a few pertinent task features
Contribution of Errors
• Error ignored in previous experiments
• Even for experts: 5-30% time in errors and
error corrections
For accurate Prediction, errors must also
be considered
Roberts’s Experiments
• 4 experts  4 separate tasks
• Human observer noted time consumed by
significant errors (> 30 seconds )
• Findings : Much of the subject-to-subject variation
is due to error rates
– For error free data, variation can be attributed to editors
than to the subjects
Applying the Keystroke model
• Errors were ignored
• Optimal Method prediction  Predictions 25-30%
too low
• Actual key sequence records  only 87%
accounted for.
• Remaining time  Unknown mental activities
Advantage of Keystroke Model
• Assumes that user is so practiced that:
– Method selection time would be nil
– Choices optimal
– Entry Flawless
• Provides an upper bound for the editing time
• Comparison between predicted time and
observed time  relatively large difference
indicates that editor is difficult to use
Effects of Computer
Response time
Effects of Computer Response time
• System Delay and Unpredictability  Affects
user Productivity and Satisfaction
• Editing : Any perceptible delay may prove
• R.B. Miller  Immediate response is not a
universal requirement in interactive
• Lists various class of user actions and
allowable delays  “best guesses”
Miller’s experiment
• Effects of varying CRT display rates and
output delays on user performance
• Delay: Increasing the display rate from 1200
to 2400 baud produced no significant
performance or attitude changes
• Variance: Increasing the variability of the
output display rate produced a significant
deterioration in both performance and
Grossberg’s Experiment
• Problem Solving Context: System response time
has little effect on performance
• Users simply adjust their tactics to make best use
of their time on system
• Response Times in problem solving activities
varied : 1,4,16 and 64
• As mean delay increased , users became more
cautious and deliberate
• However, no definite effect on time required to
reach solution
Transferring to the Editing environment
• Editing  a routine cognitive skill
• Additional mental preparation time not
useful, in fact would interfere with the task
completion time ( because of irritation )
• Experiments are always motivated to
complete their tasks, but not in the real world
Editor Design
How can we make editor easy to use ?
• Depends on the
– Command language of the editor
– Underlying structure ( editor states or modes…)
• Tradeoff:
– Our inability to learn, remember, and effectively
use large complex command sets
desire to achieve editing objectives within
minimum time
• Limits range of design options
Many approaches
• Popular wisdom
– Principle of Predictable Behavior
– User Engineering Principles
• Observation
– Dzida’s Questionnaire study: User perceived quality as a
multi-dimensional concept
– Identified 7 major categories
• Learning Process
– 1. Self teaching through trial/error with machine
feedback most effective
– 2. Anxiety decreased learning
Controlled Experiments
• Command language structure and learning
– Whether user options are good for everyone’s
performance ?
• Experiment: Two versions of editors
– Inflexible : full commands, no abbrv., extra
spaces, or defaults allowed
– Flexible : lot of freedom
• Flexibility pros and cons
– More prone to syntax errors
– Completed tasks faster
• Role of English-similar commands
– It is more helpful ?
• Tested with two versions of same editor (NOS)
– Typical Notational Syntax
– Legitimate English phrases
• 24 paid subjects
• English version
– Completed more tasks
– Error rate was lower
– Editing efficiency was better
 Surface syntax of an editor is surprisingly
important from human engineering point of
Input and Output Devices
Psychological and Human factors underlying
design and use of keyboards, screen displays
and pointing devices
Key Entry
• The most common means of encoding
letters and numbers
Keyboard Devices
Oldest typewriters
Electric typewriters
Detailed research exists in keyboard design
Detailed research exists in keyboard design
Keyboard layout (e.g. QWERTY)
Numeric keys
Standard Key size
Slope of keyboard
Key depression force required
Key displacement
Type of Kinesthetic feedback from key
Typing speed
• Some factors
– Finger ballistics
– Reaction time
– Motor learning
– Short term memory
– Human information processing capacity
• Average single finger tapping rate: 6 keys/s
Little finger  Index Finger = 20% increase
Some interesting stats
• Good typists: 0.2 secs per keystroke ( 50
• Less Frequent users: 0.7 secs
• Experienced Typists: 0.08 secs (12 taps/sec)
• Typing with alternate hands: 25% faster than
with one hand
•  Control the necessary echo output rate
for a display
Effects of Training
• Poor typing habits are difficult to shed
• Self-taught typists do not reach even half the
speed expected from entry level typists
• Worth considering the benefits of specialized
The Shaffer and Hardwick Experiment
• Limitation of human information processing
• Material:
– Difficult but coherent text
– Randomly selected words
– Short words of Random character sequences
• Explanation
– “Acquisition of a hierarchy of habits” ( ability to type a
whole word as a single unit)
– Able to read farther ahead, as opposed to random
0.159 secs per keystroke
main() { unsigned paddr,pdata;
LOOP: printf("Input port address
(hex): "); scanf("%x",&paddr); pdata
= inp(paddr); printf("Port(%xh) =
%xh\n",paddr,pdata); goto LOOP;
return 0; }
More than double the time
0.162 secs per keystroke
Error rates
• Error rates vary much from operator to
operator than does speed
• Effect of visual feedback
– Masking the keyboard
– Masking the printed text
•reduces the speed and accuracy
•Error : 0.9%  2.6 %
•Speed : 30%
•reduces only the accuracy
•Error : 40% increase !
Other studies
• Signaling errors immediately is helpful ( 25%
• Automatic error correction: many editors
incorporate it
• Lot of scope for studies of human factors aspects of the use
of editors for searching , inspecting and maintaining file
systems using interactive text-editors
• Many research areas exist(ed)
Underlying model of information structure
Techniques for selecting small segments of text
Form of editor commands
2-D editors vs 1-D editors
Error feedback and benefits of automatic error correction
Split-screen and multiple-screen editing operations
Screen size and material exposed to user
Color Displays
Audio Input, audio feedback
Direct use of eye movement for pointing and menu selection

text-editors - Computer Science