Klikker: A Method and Infrastructure for Mining, Analysis, and Visualisation of User Behaviour and Usability Issues for Mobile Application Development.

Mart Wetzels; Peter Peters; Joost Liebregts

Klikker: A Method and Infrastructure for Mining, Analysis, and Visualisation of User Behaviour and Usability Issues for Mobile Application Development.

Mart Wetzels * §

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Peter Peters

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Joost Liebregts

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l.m.g.feijs

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Eindhoven University of Technology

Klikker: A Method and Infrastructure for Mining, Analysis, and Visualisation of User Behaviour and Usability Issues for Mobile Application Development.

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Abstract

In the early stages of mobile application development, mockups can be used to receive feedback from potential end-users. This richness of feedback is limited by the lack of interactivity and requires a lot of time for a more significant study population. The Klikker methodology aims to unite the designer, developers, and end-users in the initial phases of development by utilising modern web technologies and readily available -and interchangeable -design and analytic software. Klikker combines the collection of quantitative user behaviour and qualitative feedback from end-users on their own devices without additional effort from researchers. The method is intended to be deployed in the first few weeks of the development process.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mart Wetzels, Peter Peters, Joost Liebregts, l.m.g.feijs. 2018. "Klikker: A Method and Infrastructure for Mining, Analysis, and Visualisation of User Behaviour and Usability Issues for Mobile Application Development.". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 18 (GJCST Volume 18 Issue G1).

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GJCST Volume 18 Issue G1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-G Classification K.6.3

H.2.8

Submission ReceivedDecember 8, 2017
Peer Review Double Blind
Handling Editor
Accepted January 1, 2018
Published January 15, 2018

Version of record

v1.2

Issue date

April 11, 2018

Language

English

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Article Matrices

Total Score: 161

Country: Netherlands

Subject: Global Journal of Computer Science and Technology

Authors: Mart Wetzels (PhD/Dr. count: 0)

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Publish Date: 2018 01, Mon

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Total Views: 2.6K

Total Downloads: 127

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