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A Quantum NeuroIS Data Analytics Architecture for the Usability Evaluation of Learning Management Systems
Abstract
NeuroIS uses 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 have been questionnaires. Questionnaires suffer from possible problems such as being inadequate to understand some forms of information such as emotions 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 and Hameroff (1995). 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 for the usability testing of a LMS.
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