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A Quantum NeuroIS data analytics architecture for the measurement of computer anxiety: a tool for the usability evaluation of learning management systems.

Title:

A Quantum NeuroIS data analytics architecture for the measurement of computer anxiety: a tool for the usability evaluation of learning management systems.

Valverde, Raul, Torres, Beatriz and Motaghi, Hamed (2018) A Quantum NeuroIS data analytics architecture for the measurement of computer anxiety: a tool for the usability evaluation of learning management systems. In: Quantum-Inspired Intelligent Systems for Multimedia Data Analysis. IGI Global, pp. 277-300. ISBN 9781522552192

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Abstract

NeuroIS uses neurotechnology tools such as Electroencephalogram (EEG) that can be used to measure high brainwave frequencies that can be linked to human anxiety. Past research showed that computer anxiety influences how users perceive ease of use of a learning management system (LMS). Although computer anxiety has been used successfully to evaluate the usability of LMS, the main data collection mechanisms proposed for its evaluation has been questionnaires. Questionnaires suffer from possible problems such inadequate to understand some forms of information such as emotions, lacks validity, possible lack of thought and honesty in the responses. Quantum based approaches to consciousness have been very popular in the last years including the quantum model reduction in microtubules of Penrose & Hameroff, (1995), where quantum coherence occurs by exciting quasicrystalline water molecules as dipoles buried in microtubules. Quantum consciousness models measure changes in states of consciousness that can help to identify usability issues in computer systems. The objective of the chapter is to propose an architecture based on a NeuroIS that collects data by using EEG from users and then use the collected data to perform analytics by using a quantum consciousness model proposed for computer anxiety measurements that can be used for the usability testing of a LMS.

Divisions:Concordia University > John Molson School of Business > Supply Chain and Business Technology Management
Item Type:Book Section
Refereed:Yes
Authors:Valverde, Raul and Torres, Beatriz and Motaghi, Hamed
Date:1 April 2018
Digital Object Identifier (DOI):10.4018/978-1-5225-5219-2.ch009
ID Code:983955
Deposited By: RAUL VALVERDE
Deposited On:19 Jun 2018 02:23
Last Modified:19 Jun 2018 02:37
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