User data spectrum theory: Collecting, interpreting, and implementing user data in organizations

dc.contributor.advisor Stephen Gilbert Associate Professor
dc.contributor.advisor Sree Nilakanta Associate Professor
dc.contributor.author Peer, Andrea
dc.contributor.department Theses & dissertations (College of Business)
dc.date 2018-08-11T14:03:44.000
dc.date.accessioned 2020-06-30T03:03:36Z
dc.date.available 2020-06-30T03:03:36Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.embargo 2001-01-01
dc.date.issued 2017-01-01
dc.description.abstract <p>Organizations interested in increasing their user experience (UX) capacity lack the tools they need to know how to do so. This dissertation addresses this challenge via three major research efforts: 1) the creation of User Data Spectrum theory and a User Data Spectrum survey for helping organizations better invest resources to grow their UX capacity, 2) a new UX method and model for organizations that want to capitalize on spoken words from end users called Rapid Meaningful Scenarios (RMS), and 3) a recommendation for UX education in response to the current ACM SIGCHI education Living Curriculum initiative. The User Data Spectrum work is based on 30 interviews and 110 survey responses from UX stakeholders across 120 companies. These data informed the theory as well as a factor analysis performed to identify the most relevant items in the User Data Spectrum survey. The Rapid Meaningful Scenarios methodology was developed based on iterative UX experience with a real-world organization and refined to aid UX professionals in creating structured results based on end users' words. The UX education recommendation integrates experience with the HCI curriculum at Iowa State University and curriculum discussions within the SIGCHI community over the past 5 years. The overall contribution of this research is a set of tools that will enable UX professionals and organizations to better strategize how to increase their UX capacity.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/15396/
dc.identifier.articleid 6403
dc.identifier.contextkey 11054551
dc.identifier.doi https://doi.org/10.31274/etd-180810-5020
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/15396
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/29579
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/15396/Peer_iastate_0097E_15479.pdf|||Fri Jan 14 20:40:13 UTC 2022
dc.subject.disciplines Art and Design
dc.subject.disciplines Higher Education Administration
dc.subject.disciplines Higher Education and Teaching
dc.subject.disciplines Organizational Behavior and Theory
dc.subject.keywords Human Computer Interaction
dc.subject.keywords Organizational Management
dc.subject.keywords Research Methods
dc.subject.keywords Software Development
dc.subject.keywords User-Centered Design
dc.subject.keywords User Experience
dc.title User data spectrum theory: Collecting, interpreting, and implementing user data in organizations
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
thesis.degree.discipline Human Computer Interaction
thesis.degree.level dissertation
thesis.degree.name Doctor of Philosophy
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