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UTAUT-QiU: Technology Acceptance Evaluation Model with Integrated Quality-in-use for Mobile User Interfaces adapted for Low- and Post-literate users

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UTAUT-QiU: Technology Acceptance Evaluation Model with Integrated Quality-in-use for Mobile User Interfaces adapted for Low- and Post-literate users

Patel, Nikhalesh (2019) UTAUT-QiU: Technology Acceptance Evaluation Model with Integrated Quality-in-use for Mobile User Interfaces adapted for Low- and Post-literate users. Masters thesis, Concordia University.

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Abstract

Mobile technology evolution has greatly affected our lives, in terms of performing our daily tasks more efficiently and effectively. It includes recent advances in voice-enabled technology empowered by artificial intelligence, machine learning and natural language processing. Then again, technology evolution has created a problem for low and post-literate population in terms of understanding and using mobile devices with complex functionality. Low- and post-literate individuals are the ones who have difficulties either reading a text or understanding a new technology.

We propose a new technology acceptance evaluation model UTAUT-QiU with the aim of assessing both user acceptance of text free mobile applications’ user interface (MUI) and MUI’s quality-in-use. We intend to increase the quality-in-use of MUI for low- and post-literate users by applying text-free approach combined with voice as a service. UTAUT-QiU is inspired by UTAUT (Unified Theory of Acceptance and Use of Technology) and integrates it with Quality-In-Use model for Mobile Applications. The UTAUT-QiU model is used to investigate empirically the effect of text free UI approach on low- and post-literate users in performing their daily tasks with the help of mobile applications.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Patel, Nikhalesh
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Software Engineering
Date:March 2019
Thesis Supervisor(s):Ormandjieva, Olga and Pitula, Kristina
ID Code:985088
Deposited By: Nikhalesh Patel
Deposited On:27 Oct 2022 13:48
Last Modified:27 Oct 2022 13:48
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