CCE Theses and Dissertations

Date of Award

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

College of Computing and Engineering

Advisor

Ling Wang

Committee Member

Paul Souren

Committee Member

Hur Inkyoung

Abstract

Current research demonstrates that distractions while participating in online courses affect students’ performance in online tasks. Electroencephalography (EEG) devices are currently being used in education to help students maintain attention when engaged in online classes. Previous studies have focused predominantly on comparing EEG devices, EEG signal quality, and EEG effectiveness. However, there is no comprehensive study examining the usability of the portable EEG headset to monitor students' attention in online courses.

This study aimed to examine the usability of EEG devices while monitoring student attention levels during online educational tasks. Specifically, twenty (20) participants who intend to enroll in online courses were trained to use EEG devices with their smart phones and follow a checklist for EEG software installation and hardware connection. Participants wore the EEG device and ran the EEG software while they were engaged in an online learning task. While participants were engaged in the learning task, the researcher collected qualitative data based on Nielsen’s 10 heuristics evaluation method by instructing participants to utilize the think-aloud method. When participants completed their online task, the researcher collected quantitative data via the System Usability Scale (SUS) survey that was completed by all participants.

The study explored both qualitative and quantitative analyses to support the research question that examines the usability factors influencing the adoption of portable EEG headset use for students in online courses. The qualitative data showed that participants rated the portable EEG headset positively. However, the quantitative results of the SUS revealed that participants were not satisfied with using the portable EEG.

The findings of this study have implications for the field of Information Systems and are of particular interest to human-computer interaction usability researchers and professionals. Additionally, those in the usability and educational research who are interested in understanding the factors that influence the adoption of the EEG headset for educational use can benefit from this research.

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