Usability Prioritization Using Performance Metrics and Hierarchical Agglomerative Clustering in MAR-Learning Application

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F17%3A50013620" target="_blank" >RIV/62690094:18450/17:50013620 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.3233/978-1-61499-800-6-731" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-800-6-731</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/978-1-61499-800-6-731" target="_blank" >10.3233/978-1-61499-800-6-731</a>

Result language

angličtina

Original language name

Usability Prioritization Using Performance Metrics and Hierarchical Agglomerative Clustering in MAR-Learning Application

Original language description

This paper highlights the current literatures in usability studies, performance metrics and machine learning algorithm. A literature review is done in these three areas of studies to find a research gap that can be explored further. The paper will then propose a research methodology to attend to the issues of machine learning and usability. An experiment is proposed to compare the efficiency results in between data consistency, correlation between performance metrics and self-reported metrics of a Mobile Augmented Reality learning application. The methodology proposes hierarchical agglomerative clustering technique as a solution in differentiating usability issues according to priority in order to help with usability re-engineering decisions. This paper proposes two objectives through the proposed framework and present evidence on how to achieve them. Lastly, this paper will discuss the results, conclusion and future works of the proposed study.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Frontiers in Artificial Intelligence and Applications

ISBN

978-1-61499-799-3

ISSN

0922-6389

e-ISSN

neuvedeno

Number of pages

14

Pages from-to

731-744

Publisher name

IOS Press

Place of publication

Kitakyushu

Event location

Kitakyushu; Japan

Event date

Sep 26, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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