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A survey of software learnability: metrics, methodologies and guidelines
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Conference on Human Factors in Computing Systems archive
Proceedings of the 27th international conference on Human factors in computing systems table of contents
Boston, MA, USA
SESSION: Metrics table of contents
Pages 649-658  
Year of Publication: 2009
ISBN:978-1-60558-246-7
Authors
Tovi Grossman  Autodesk Research, Toronto, ON, Canada
George Fitzmaurice  Autodesk Research, Toronto, ON, Canada
Ramtin Attar  Autodesk Research, Toronto, ON, Canada
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

It is well-accepted that learnability is an important aspect of usability, yet there is little agreement as to how learnability should be defined, measured, and evaluated. In this paper, we present a survey of the previous definitions, metrics, and evaluation methodologies which have been used for software learnability. Our survey of evaluation methodologies leads us to a new question-suggestion protocol, which, in a user study, was shown to expose a significantly higher number of learnability issues in comparison to a more traditional think-aloud protocol. Based on the issues identified in our study, we present a classification system of learnability issues, and demonstrate how these categories can lead to guidelines for addressing the associated challenges.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Tovi Grossman: colleagues
George Fitzmaurice: colleagues
Ramtin Attar: colleagues