Collaborative Heuristic Evaluation, UPA2010

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Collaborative Heuristic Evaluation: improving the effectiveness of heuristic evaluation Helen Petrie, Lucy Buykx Human Computer Interaction Research Group Department of Computer Science University of York, UK

description

Standard heuristic evaluation (SHE) continues to be very popular evaluation method in spite of serious criticisms of its validity and reliability. The paper proposes a new collaborative heuristic evaluation (CHE) and presents a study that shows the increased reliability and effectiveness of CHE in comparison to SHE. Presentation given at 9:30 on Thursday 27 May by Helen Petrie and Lucy Buykx.

Transcript of Collaborative Heuristic Evaluation, UPA2010

Page 1: Collaborative Heuristic Evaluation, UPA2010

Collaborative Heuristic Evaluation:improving the effectiveness of

heuristic evaluation

Helen Petrie, Lucy BuykxHuman Computer Interaction Research Group

Department of Computer ScienceUniversity of York, UK

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Standard heuristic evaluation (SHE)

Strengths• Independent evaluator viewpoints• High volume of potential problems

Weaknesses• Laborious, boring, frustrating• Time consuming to combine problems from individual

evaluators• High proportion of trivial problems

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Collaborative Heuristic Evaluation (CHE)

Method– Evaluators work in a group– Propose potential usability problems– Create problem list in real time– Independently rate severity

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CHE Problem rating sheet

12345

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Experiment method

• 4 websites• airline, train, tourist information sites

• 2 groups of 5 usability professionals

• 2 methods: SHE and CHE– each professional performed each method on

two websites

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Experiment design

Group 1Group 1 Group 2Group 2

CHECHENational RailVisit Britain

British TownsEasy Jet

SHESHEEasy Jet

British TownsVisit BritainNational Rail

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Analysis of data

Made master problem list for SHE– Only included problems found on pages visited

by all evaluators– Relaxed matching of problems

Master list for CHE already there

Analysed how many evaluators found each problem in each method

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Results

SHE: 22.9 usability problems per websitePool of 250 problems on pages visited by all

evaluators

CHE: 42.7 usability problems per websitePool of 153 problems

(smaller pool, because of greater overlap between evaluators …)

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Inter-evaluator agreement

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National Rail website

SHE CHE

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Any-two agreement: measure of evaluator effect

SHESHE CHECHE

Agree it’s a Agree it’s a problemproblem

8.9% 91.6%

Agree severity Agree severity ratingrating

36.0%navg = 19

37.5%navg = 38

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Conclusion

CHE ….• Exposes evaluators to each other ideas • Creates more agreement about problems• More efficient as a method

- creates master problem list in the session– larger number of problems per hour

• Generates discussion/ideas for solving problems

• More enjoyable for evaluators

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Thank you!

Questions?

Contact us: [email protected] [email protected]

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Matching process

• “don’t know what overtaking trains means”• “don’t know what ‘include overtaking trains

in journey results’ means”

• “want to be able to select any time of day but drop down only offers 4 hour segments”

• “specified times is well hidden and inflexible - want to go from any time”