Exploring the Digital Native Assessment Scale as an Indicator for Building More Effective User Experiences.pdf (286.65 kB)
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Exploring the digital native assessment scale as an indicator for building more effective user experiences

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conference contribution
posted on 03.03.2021, 13:50 by Lexy MartinLexy Martin, Steve SummerskillSteve Summerskill, Tracy RossTracy Ross, Karl Proctor, Arber Shabani
Building exceptional user experiences means designing for users of all digital skill level. An increased emphasis on personalization and, with it, adaptive interfaces exacerbates the necessity for digital inclusivity. However, how can designers ensure that they are meeting the needs of those with high and low skillsets? The research reported here employed semi-structured interviews to explore whether the Digital Native Assessment Scale (DNAS) can be used as a tool to classify users and act as a surrogate for predicting their digital profiles. Sixteen participants answered questions about their everyday technology behaviours, as well as their attitudes towards technology. Nine themes emerged through thematic analysis, however only one of these themes was associated with an even, dichotomous split between high scorers on the DNAS and low scorers on the DNAS. Therefore, the DNAS only clearly indicated digital behaviour in a limited number of issues and cannot be relied upon as a proxy for the participant characteristics to be supported in interface design.

Funding

Jaguar Land Rover

History

School

  • Design and Creative Arts

Department

  • Design

Published in

HCI International 2020 - Late Breaking Papers: User Experience Design and Case Studies

Pages

199 - 210

Source

International Conference on Human-Computer Interaction (HCII 2020)

Publisher

Springer

Version

AM (Accepted Manuscript)

Rights holder

© Springer Nature Switzerland AG

Publisher statement

The final authenticated version is available online at https://doi.org/10.1007/978-3-030-60114-0_14.

Publication date

2020-10-03

Copyright date

2020

ISBN

9783030601133; 978030601140

ISSN

0302-9743

eISSN

1611-3349

Book series

Lecture Notes in Computer Science; 12423

Language

en

Editor(s)

Constantine Stephanidis; Aaron Marcus; Elizabeth Rosenzweig; Pei-Luen Patrick Rau; Abbas Moallem; Matthias Rauterberg

Location

Copenhagen, Denmark (Virtual)

Event dates

19th July 2020 - 24th July 2020

Depositor

Miss Lexy Martin. Deposit date: 2 March 2021