Lecture 14

Evaluation techniques Part 2

Today’s Topics We will cover today

Evaluation through user participationStyles of evaluationEmpirical methods: experimental evaluationExperimental DesignAnalysis of dataExperimental studies on groups

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Today’s TopicsObservational MethodsQuery TechniquesPsychological MethodsSelecting appropriate evaluation technique

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Evaluating through user Participation

User participation in evaluation tends to occur in the later stages of developmentwhen there is at least a working prototype of the system in place.

This may range from a simulation of the system’s interactive capabilities, without its underlying functionality.

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Styles of evaluation Two distinct styles of evaluation are

those performed under laboratory conditions and

those conducted in the work environment or ‘in the field’

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Laboratory studies Advantages:

specialist equipment available uninterrupted environment

Disadvantages: lack of context difficult to observe several users cooperating

Appropriate if system location is dangerous or impractical for constrained

single user systems to allow controlled manipulation of use

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Field Studies Advantages:

natural environment context retained (though observation may alter it) longitudinal studies possible

Disadvantages: distractions noise

Appropriate where context is crucial for longitudinal studies

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Empirical methods: experimental evaluation One of the most powerful methods of

evaluating a design or an aspect of a design is to use a controlled experiment.

This provides empirical evidence to support a particular claim or hypothesis.

It can be used to study a wide range of different issues at different levels of detail.

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The evaluator chooses a hypothesis totest, which can be determined by measuring some attribute of participant behavior.

A number of experimental conditions are considered which differ only in the valuesof certain controlled variables.

Empirical methods: experimental evaluation

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Factors to be considered for experiment design mainly includes,Participants chosenVariables tested and manipulatedHypothesis testedExperimental Design

Empirical methods: experimental evaluation

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Participants In evaluation experiments, participants

should be chosen to match the expected user population as closely as possible.This will involve experimental testing with the

actual users but this is not always possible. If participants are not actual users, they

should be chosen to be of a similar age and level of education as the intended user group.

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Participants Their experience with computers in

general, and with systems related to that being tested, should be similar, as should their experience or knowledge of the taskdomain.

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Participants It is no good testing an interface designed

to be used by the general public on a participant set made up of computer science undergraduates: they are simply not representative of the intended user population

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Participants Choose enough sample size of population

to test all aspects of the system. Nielsen and Landauer suggest that

usability testing with a single participantwill find about a third of the usability problems, and that there is little to be gained from testing with more than five.Always test using large number of participants

i.e.; double of five.

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Variables Experiments manipulate and measure

variables under controlled conditions, in order to test the hypothesis.

There are two main types of variable: those that are ‘manipulated’ or changed

(known as the independent variables) and those that are measured (the dependent

variables).

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Variables

independent variable (IV) characteristic changed to produce different conditions e.g. interface style, number of menu items

dependent variable (DV) characteristics measured in the experiment e.g. time taken, number of errors.

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Hypothesis A hypothesis is a prediction of the

outcome of an experiment. It is framed in terms of the independent

and dependent variables, stating that a variation in the independent variable will cause a difference in the dependent variable.The aim of the experiment is to show that this

prediction is correct.

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Hypothesis This is done by disproving the null

hypothesis, which states that there is no difference in the dependent variable between the levels of the independent variable.

If a result is significant at the given level of certainty, that the differences measured would not have occurred by chance (that is, that the null hypothesis is incorrect).

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Hypothesis prediction of outcome

framed in terms of IV and DV

For example “error rate will increase as font size decreases”

null hypothesis: states no difference between conditions aim is to disprove this

e.g. null hyp. = “no change with font size”

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Experimental Design There are two main methods:

between-subjects and within-subjects.

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Experimental design within groups design

each subject performs experiment under each condition. transfer of learning possible less costly and less likely to suffer from user variation.

between groups design each subject performs under only one condition no transfer of learning more users required variation can bias results.

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Between group design The advantage of a between-subjects

design is that any learning effect resulting from the user performing in one condition and then the other is controlled: each user performs under only one condition.

The disadvantages are that a greater number of participants are required, and that significant variation between the groups can negate any results.

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Within-group Design Each user performs under each different

condition. This design can suffer from transfer of

learning effects, but this can be lessened if the order in which the conditions are tackled is varied between users.

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Analysis of data Before you start to do any statistics:

look at data save original data

Choice of statistical technique depends on type of data information required

Type of data discrete - finite number of values continuous - any value

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Analysis - types of test parametric

assume normal distribution robust powerful

non-parametric do not assume normal distribution less powerful more reliable

contingency table classify data by discrete attributes count number of data items in each group

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Analysis of data (cont.) What information is required?

is there a difference?how big is the difference?how accurate is the estimate?

Parametric and non-parametric tests mainly address first of these

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Experimental studies on groups Experimental studies of groups and of

groupware are more difficult than the corresponding single-user experiments already considered.

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Experimental studies on groups

Problems with:subject groupschoice of taskdata gatheringanalysis

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Experimental studies on groups To organize, say, 10 experiments of a

single-user system requires 10 participants.

For an experiment involving groups of three, we will, of course, need 30 participants for the same number of experiments.

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Experimental Studies on groups In addition, experiments in group working

are often longer than the single-user equivalents as we must allow time for the group to ‘settle down’ and some rapport to develop.

This all means more disruption for participants and possibly more expense payments.

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Subject groupslarger number of subjects

more expensive

longer time to `settle down’… even more variation!

difficult to timetable

so … often only three or four groups

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The Task Choosing a suitable task is also difficult.

We may want to test a variety of different task types: creative, structured, information passing, and so on.

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The taskmust encourage cooperation

perhaps involve multiple channels

options: creative task e.g. ‘write a short report on …’

decision games e.g. desert survival task

control task e.g. ARKola bottling plant

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Data gatheringseveral video cameras

+ direct logging of application

problems: synchronisation sheer volume!

one solution: record from each perspective

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Analysis In true experimental tradition, we would

like to see statistical differencesbetween experimental conditions.

We saw earlier that individual differences made this difficult in single-user experiments. If anything, group variation is more extreme. Given randomly mixed groups, one group will act in a democratic fashion. Thus dominating others.

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AnalysisVast variation between groups

solutions: within groups experiments micro-analysis (e.g., gaps in speech) anecdotal and qualitative analysis

look at interactions between group and media

controlled experiments may `waste' resources!

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Field studiesExperiments dominated by group formation

Field studies more realistic:distributed cognition work studied in context

real action is situated action

physical and social environment both crucial

Contrast:psychology – controlled experiment

sociology and anthropology – open study and rich data

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Observational Methods A popular way to gather information about actual use of

a system is to observe users interacting with it. Techniques include

Think Aloud Cooperative evaluation Protocol analysis Automated analysis Post-task walkthroughs

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Think Aloud user observed performing task user asked to describe what he is doing and why,

what he thinks is happening etc.

Advantages simplicity - requires little expertise can provide useful insight can show how system is actually use

Disadvantages subjective selective act of describing may alter task performance

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Cooperative evaluation variation on think aloud user collaborates in evaluation both user and evaluator can ask each other questions

throughout

Additional advantages less constrained and easier to use user is encouraged to criticize system clarification possible

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Protocol analysis paper and pencil – cheap, limited to writing speed audio – good for think aloud, difficult to match with other protocols video – accurate and realistic, needs special equipment, obtrusive computer logging – automatic and unobtrusive, large amounts of data

difficult to analyze user notebooks – coarse and subjective, useful insights, good for

longitudinal studies

Mixed use in practice. audio/video transcription difficult and requires skill. Some automatic support tools available

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Automated Analysis – EVA

Workplace project Post task walkthrough

user reacts on action after the event used to fill in intention

Advantages analyst has time to focus on relevant incidents avoid excessive interruption of task

Disadvantages lack of freshness may be post-hoc interpretation of events

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post-task walkthroughs transcript played back to participant for

comment immediately fresh in minddelayed evaluator has time to identify

questions useful to identify reasons for actions and

alternatives considered necessary in cases where think aloud is not

possible

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Query Techniques Relies on asking the user about the

interface directly. Query techniques can be useful in eliciting

detail of the user’s view of a system. Types of Query Techniques are

InterviewsQuestionnaires

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Interviews analyst questions user on one-to -one basis

usually based on prepared questions informal, subjective and relatively cheap

Advantages can be varied to suit context issues can be explored more fully can elicit user views and identify unanticipated problems

Disadvantages very subjective time consuming

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Questionnaires Set of fixed questions given to users

Advantages quick and reaches large user group can be analyzed more rigorously

Disadvantages less flexible less probing

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Questionnaires (ctd) Need careful design

what information is required? how are answers to be analyzed?

Styles of question general open-ended scalar multi-choice ranked

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Psychological Methods One of the problems with most evaluation

techniques is that we are reliant on observation and the users telling us what they are doing and how they are feeling.What if we were able to measure these things

directly?

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Psychological Methods Interest has grown recently in the use

of what is sometimes called objective usability testing, ways of monitoring physiological aspects of computer use.

Potentially this will allow us not only to see more clearly exactly what users do when they interact with computers, but also to measure how they feel.

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Physiological methods Areas receiving more attention are,

Eye trackingPhysiological measurement

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Eye tracking Head or desk mounted equipment tracks the position of

the eye Eye movement reflects the amount of cognitive

processing a display requires measurements include

fixations: eye maintains stable position. Number and duration indicate level of difficulty with display

saccades: rapid eye movement from one point of interest to another

scan paths: moving straight to a target with a short fixation at the target is optimal

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Eye Tracking Equipment

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Calibrating Eye Tracking

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Eye Tracking Animation

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Physiological measurements

Emotional response linked to physical changes These may help determine a user’s reaction to an

interface Measurements include:

heart activity, including blood pressure, volume and pulse. activity of sweat glands: Galvanic Skin Response (GSR) electrical activity in muscle: electromyogram (EMG) electrical activity in brain: electroencephalogram (EEG)

Some difficulty in interpreting these physiological responses - more research needed

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Selecting an Evaluation Method We have to decide which method is most

appropriate for our needs.There is no hard and fast rule to select any

method. However, there are a number of factors

that should be taken into account when selecting evaluation techniques.

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Factors distinguishing evaluation techniques

The stage in the cycle at which the evaluation is carried out

The style of evaluation The level of subjectivity or objectivity of the

technique The type of measures provided The information provided

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The immediacy of the response The level of interference implied The resources required.

Factors distinguishing evaluation techniques

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Choosing an Evaluation Method

when in process: design vs. implementation

style of evaluation: laboratory vs. field

how objective: subjective vs. objective

type of measures: qualitative vs. quantitative

level of information: high level vs. low level

level of interference: obtrusive vs. unobtrusive

resources available: time, subjects, equipment, expertise

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Summary Evaluation is an integral part of the design

process and should take place throughout the design life cycle.

Its aim is to test the functionality and usability of the design and to identify and rectify any problems.

It can also try to determine the user’sattitude and response to the system.

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Summary It can take place in a specialist laboratory

or in the user’s workplace, and may or may not involve active participation on the part of the user.

Experts can reduce time of evaluation by considering previous experimental results.

The choice of evaluation method is largely dependent on what is required of theevaluation.

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