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Mick McGee

dblp:49/3627 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2004
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Usability and user experience research · 77% Design research and methods · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Usability and user experience research › usability evaluation
usability measurement
0.012004
Master usability scaling: magnitude estimation and master scaling applied to usability measurement · CHI 2004

Methods — techniques the papers use, named apart from their topics

master scaling · 0.0magnitude estimation · 0.0
YearPublicationVenuePosition
2004 Master usability scaling: magnitude estimation and master scaling applied to usability measurement
abstract
Master Usability Scaling (MUS) is a measurement method for developing a universal usability continuum based on magnitude estimation and master scaling. The universal usability continuum allows true ratio comparisons, potentially between all items measurable by the construct of usability (attributes, tasks, or products -- software or hardware) that have contributed to the meta-set by following the procedures prescribed. This paper describes the background for MUS, data reduction, and cases studies in software usability assessment.MUS is based on a new measurement method of usability, Usability Magnitude Estimation (UME) [9], where users estimate usability magnitude according to an objective definition of usability. UME allows all items measured within a single usability activity to be compared across one continuum. MUS utilizes UME to assess standard reference tasks across different usability activities to construct one meta-set of data. This meta-set of data can be represented as a universal usability continuum. MUS is simple to administer, easy to comprehend, and with advanced underlying calculations, powerful to use. The MUS continuum has the potential to be a widespread, robust, universal measurement scale of usability.
Mick McGee
CHI1