Chapter 9 evaluation techniques. Evaluation Techniques Evaluation – tests usability and functionality of system – occurs in laboratory, field and/or in.

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Presentation transcript:

chapter 9 evaluation techniques

Evaluation Techniques Evaluation – tests usability and functionality of system – occurs in laboratory, field and/or in collaboration with users – evaluates both design and implementation – should be considered at all stages in the design life cycle

Goals of Evaluation assess extent of system functionality assess effect of interface on user identify specific problems

Evaluating Designs Cognitive Walkthrough Heuristic Evaluation Review-based evaluation

Cognitive Walkthrough Proposed by Polson et al. – evaluates design on how well it supports user in learning task – usually performed by expert in cognitive psychology – expert ‘walks though’ design to identify potential problems using psychological principles – forms used to guide analysis

What You Need System prototype Description of task Complete list of actions Knowledge of intended users

Four Questions Effect of action = user’s goal? Visibility of available actions User knowledge of actions Understandable feedback

Heuristic Evaluation Proposed by Nielsen and Molich. usability criteria (heuristics) are identified design examined by experts to see if these are violated Example heuristics – system behaviour is predictable – system behaviour is consistent – feedback is provided Heuristic evaluation `debugs' design.

10 Heuristics 1. Visibility of system status 2. Match between system and real world 3. User control and freedom 4. Consistency and standards 5. Error prevention

Cont… 6. Recognition rather than recall 7. Flexibility and efficiency of use 8. Aesthetic and minimalist design 9. Help users recover from errors 10. Help and documentation

Review-based evaluation Results from the literature used to support or refute parts of design. Care needed to ensure results are transferable to new design. Model-based evaluation Cognitive models used to filter design options – e.g. GOMS (goals, operators, methods and selection) prediction of user performance. Design rationale can also provide useful evaluation information

Evaluating through user Participation

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

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

Evaluating Implementations Requires an artefact: simulation, prototype, full implementation

Experimental evaluation controlled evaluation of specific aspects of interactive behaviour.

Experimental factors Subjects – who – representative, sufficient sample Variables – things to modify and measure Hypothesis – what you’d like to show Experimental design – how you are going to do it

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.

Hypothesis prediction of outcome – framed in terms of IV and DV – e.g. “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”

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.

General process Determine research questions and conduct literature review Form hypotheses and null hypotheses Identify independent variables and levels of them Identify dependent variables Conduct experiments and analyze data Apply statistical methods and determine p values Reject null hypothesis if p<0.05 Accept/(reject?) hypothesis

Experimental studies on groups More difficult than single-user experiments Problems with: – subject groups – choice of task – data gathering – analysis

Subject groups larger number of subjects  more expensive longer time to `settle down’ … even more variation! difficult to timetable so … often only three or four groups

The task must encourage cooperation perhaps involve multiple channels options: – creative taske.g. ‘write a short report on …’ – decision gamese.g. desert survival task – control taske.g. ARKola bottling plant

Data gathering several video cameras + direct logging of application problems: – synchronisation – sheer volume! one solution: – record from each perspective

Analysis N.B. vast 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!

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

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

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

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

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

post-task walkthroughs transcript played back to participant for comment – immediately  fresh in mind – delayed  evaluator has time to identify questions useful to identify reasons for actions and alternatives considered necessary in cases where think aloud is not possible

Query Techniques Interviews Questionnaires

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

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

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