Other affiliations: University of Copenhagen Faculty of Science, University of Maryland, College Park
Bio: Kasper Hornbæk is an academic researcher from University of Copenhagen. The author has contributed to research in topics: Usability & Usability engineering. The author has an hindex of 44, co-authored 188 publications receiving 8264 citations. Previous affiliations of Kasper Hornbæk include University of Copenhagen Faculty of Science & University of Maryland, College Park.
Papers published on a yearly basis
01 Feb 2006-International Journal of Human-computer Studies \/ International Journal of Man-machine Studies
TL;DR: It is argued that increased attention to the problems identified and challenges discussed may strengthen studies of usability and usability research.
Abstract: How to measure usability is an important question in HCI research and user interface evaluation. We review current practice in measuring usability by categorizing and discussing usability measures from 180 studies published in core HCI journals and proceedings. The discussion distinguish several problems with the measures, including whether they actually measure usability, if they cover usability broadly, how they are reasoned about, and if they meet recommendations on how to measure usability. In many studies, the choice of and reasoning about usability measures fall short of a valid and reliable account of usability as quality-in-use of the user interface being studied. Based on the review, we discuss challenges for studies of usability and for research into how to measure usability. The challenges are to distinguish and empirically compare subjective and objective measures of usability; to focus on developing and employing measures of learning and retention; to study long-term use and usability; to extend measures of satisfaction beyond post-use questionnaires; to validate and standardize the host of subjective satisfaction questionnaires used; to study correlations between usability measures as a means for validation; and to use both micro and macro tasks and corresponding measures of usability. In conclusion, we argue that increased attention to the problems identified and challenges discussed may strengthen studies of usability and usability research.
••01 Apr 2000
TL;DR: This work presents data from an experiment where 87 subjects solved 20 information retrieval tasks concerning programming problems, and the correlation between efficiency, as indicated by task completion time, and effectiveness, as indicating by quality of solution was negligible.
Abstract: Usability comprises the aspects effectiveness, efficiency, and satisfaction. The correlations between these aspects are not well understood for complex tasks. We present data from an experiment where 87 subjects solved 20 information retrieval tasks concerning programming problems. The correlation between efficiency, as indicated by task completion time, and effectiveness, as indicated by quality of solution, was negligible. Generally, the correlations among the usability aspects depend in a complex way on the application domain, the user's experience, and the use context. Going through three years of CHI Proceedings, we find that 11 out of 19 experimental studies involving complex tasks account for only one or two aspects of usability. When these studies make claims concerning overall usability, they rely on risky assumptions about correlations between usability aspects. Unless domain specific studies suggest otherwise, effectiveness, efficiency, and satisfaction should be considered independent aspect of usability and all be included in usability testing.
07 May 2011
TL;DR: This paper reviews how empirical research on User Experience (UX) is conducted, integrating products, dimensions of experience, and methodologies across a systematically selected sample of 51 publications from 2005-2009, reporting a total of 66 empirical studies.
Abstract: This paper reviews how empirical research on User Experience (UX) is conducted. It integrates products, dimensions of experience, and methodologies across a systematically selected sample of 51 publications from 2005-2009, reporting a total of 66 empirical studies. Results show a shift in the products and use contexts that are studied, from work towards leisure, from controlled tasks towards open use situations, and from desktop computing towards consumer products and art. Context of use and anticipated use, often named key factors of UX, are rarely researched. Emotions, enjoyment and aesthetics are the most frequently assessed dimensions. The methodologies used are mostly qualitative, and known from traditional usability studies, though constructive methods with unclear validity are being developed and used. Many studies use self-developed questionnaires without providing items or statistical validations. We discuss underexplored research questions and potential improvements of UX research.
••05 May 2012
TL;DR: A sample of existing work on shape-changing interfaces is reviewed to address shortcomings and identify eight types of shape that are transformed in various ways to serve both functional and hedonic design purposes.
Abstract: Shape change is increasingly used in physical user interfaces, both as input and output. Yet, the progress made and the key research questions for shape-changing interfaces are rarely analyzed systematically. We review a sample of existing work on shape-changing interfaces to address these shortcomings. We identify eight types of shape that are transformed in various ways to serve both functional and hedonic design purposes. Interaction with shape-changing interfaces is simple and rarely merges input and output. Three questions are discussed based on the review: (a) which design purposes may shape-changing interfaces be used for, (b) which parts of the design space are not well understood, and (c) why studying user experience with shape-changing interfaces is important.
18 Apr 2015
TL;DR: This article goes beyond the focused research questions addressed so far by delineating the research area, synthesizing its open challenges and laying out a research agenda.
Abstract: Physical representations of data have existed for thousands of years. Yet it is now that advances in digital fabrication, actuated tangible interfaces, and shape-changing displays are spurring an emerging area of research that we call Data Physicalization. It aims to help people explore, understand, and communicate data using computer-supported physical data representations. We call these representations physicalizations, analogously to visualizations -- their purely visual counterpart. In this article, we go beyond the focused research questions addressed so far by delineating the research area, synthesizing its open challenges and laying out a research agenda.
TL;DR: Results from the analysis of this large number of SUS scores show that the SUS is a highly robust and versatile tool for usability professionals.
Abstract: This article presents nearly 10 year's worth of System Usability Scale (SUS) data collected on numerous products in all phases of the development lifecycle. The SUS, developed by Brooke (1996), reflected a strong need in the usability community for a tool that could quickly and easily collect a user's subjective rating of a product's usability. The data in this study indicate that the SUS fulfills that need. Results from the analysis of this large number of SUS scores show that the SUS is a highly robust and versatile tool for usability professionals. The article presents these results and discusses their implications, describes nontraditional uses of the SUS, explains a proposed modification to the SUS to provide an adjective rating that correlates with a given score, and provides details of what constitutes an acceptable SUS score.
01 Nov 2008
TL;DR: In this article, the authors present a collection of qualified narrative methods for the human sciences that has actually been composed by the authors themselves, which can be used as an excellent source for reading.
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TL;DR: In this article, applied linear regression models are used for linear regression in the context of quality control in quality control systems, and the results show that linear regression is effective in many applications.
Abstract: (1991). Applied Linear Regression Models. Journal of Quality Technology: Vol. 23, No. 1, pp. 76-77.