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Informing user understanding of smart systems through feedback

Informing user understanding of smart systems through feedback
Informing user understanding of smart systems through feedback
Recent advances in microprocessing and low power radio technologies have catalyzed the transition of smart technologies from the domain of researchers and enthusiasts to everyday consumers. This new wave of smart devices, and the systems they form, marks a significant step towards Weiser's vision of ubiquitous computing and offers users a wealth of new and exciting opportunities. However, smart technologies are inherently complex and without careful design can prove complicated and confusing for users with no specific knowledge of the underpinning technologies. A poor understanding has the potential to inhibit user experience and may result in the abandonment of technologies which otherwise could bring real benefits to users.

While a considerable body of work exists examining how confusion arising from complexity can be addressed, this work largely focuses on traditional heuristic systems. The non-deterministic nature of some smart technologies and the capacity for the sophisticated interconnected processes they employ to mask the relationship between system inputs and outcomes exacerbate the challenges examined in prior work. There is therefore a need to investigate how these challenges can be overcome for users of smart systems in particular.

This thesis reports a series of five user studies, conducted under both controlled conditions and in the field. In particular, we examine how feedback can be used to inform user understanding of sensor based smart systems. Through qualitative and quantitative analysis we observe and evaluate over 145 participants interacting with sensor based smart systems. From our findings we identify a number of design implications and highlight the pitfalls of poor and uninformed design.
HCI, Feedback, user study
University of Southampton
Kittley-Davies, Jacob
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Kittley-Davies, Jacob
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Costanza, Enrico
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Stein, Sebastian
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Rogers, Alex
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Kittley-Davies, Jacob (2020) Informing user understanding of smart systems through feedback. University of Southampton, Doctoral Thesis, 152pp.

Record type: Thesis (Doctoral)

Abstract

Recent advances in microprocessing and low power radio technologies have catalyzed the transition of smart technologies from the domain of researchers and enthusiasts to everyday consumers. This new wave of smart devices, and the systems they form, marks a significant step towards Weiser's vision of ubiquitous computing and offers users a wealth of new and exciting opportunities. However, smart technologies are inherently complex and without careful design can prove complicated and confusing for users with no specific knowledge of the underpinning technologies. A poor understanding has the potential to inhibit user experience and may result in the abandonment of technologies which otherwise could bring real benefits to users.

While a considerable body of work exists examining how confusion arising from complexity can be addressed, this work largely focuses on traditional heuristic systems. The non-deterministic nature of some smart technologies and the capacity for the sophisticated interconnected processes they employ to mask the relationship between system inputs and outcomes exacerbate the challenges examined in prior work. There is therefore a need to investigate how these challenges can be overcome for users of smart systems in particular.

This thesis reports a series of five user studies, conducted under both controlled conditions and in the field. In particular, we examine how feedback can be used to inform user understanding of sensor based smart systems. Through qualitative and quantitative analysis we observe and evaluate over 145 participants interacting with sensor based smart systems. From our findings we identify a number of design implications and highlight the pitfalls of poor and uninformed design.

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More information

Published date: March 2020
Keywords: HCI, Feedback, user study

Identifiers

Local EPrints ID: 448263
URI: http://eprints.soton.ac.uk/id/eprint/448263
PURE UUID: 64fd0741-201c-4597-aeef-ce18110bc1fa
ORCID for Sebastian Stein: ORCID iD orcid.org/0000-0003-2858-8857

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Date deposited: 16 Apr 2021 16:33
Last modified: 06 Jun 2024 01:46

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Contributors

Author: Jacob Kittley-Davies
Thesis advisor: Enrico Costanza
Thesis advisor: Sebastian Stein ORCID iD
Thesis advisor: Alex Rogers

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