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Use of EEG to Understand Brain Intensity in Engineering Students Using a Stem Educational Mobile Application

Hatcher, Kevin
http://orcid.org/0000-0002-7745-5498
http://rave.ohiolink.edu/etdc/view?acc_num=wright1463148705

Abstract Details

2016, Master of Science in Engineering (MSEgr), Wright State University, Biomedical Engineering.
In the first two years of undergraduate work in engineering, students are taught concepts such as physics, electronics, and most importantly calculus. It is especially important for students to get a better grasp on foundational math concepts, such as calculus in the beginning or they will be overwhelmed by the workload to come. The focus of this research was to understand how students learning calculus, could benefit from an augmented-educational mobile application. In the study students were measured with electroencephalography (EEG) measurements utilized by the Emotive EPOC ® as they attempted to solve different limit themed problems in order to determine if learning with an augmented educational mobile application had an impact on brain intensity. Results indicated that mobile learners showed increased intensity in selected brain regions when compared to non-mobile learners. This study will aid in better understanding the impact that an augmented-education mobile application can have on learning.
Subhashini Ganapathy, Ph.D. (Advisor)
Nasser Kashou, Ph.D. (Committee Member)
Xinhui Zhang, Ph.D. (Committee Member)
55 p.
Biomedical Engineering; Educational Technology
biomedical engineering; educational technology

Recommended Citations

Citations

  • Hatcher, K. (2016). Use of EEG to Understand Brain Intensity in Engineering Students Using a Stem Educational Mobile Application [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1463148705

    APA Style (7th edition)

  • Hatcher, Kevin. Use of EEG to Understand Brain Intensity in Engineering Students Using a Stem Educational Mobile Application. 2016. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1463148705.

    MLA Style (8th edition)

  • Hatcher, Kevin. "Use of EEG to Understand Brain Intensity in Engineering Students Using a Stem Educational Mobile Application." Master's thesis, Wright State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1463148705

    Chicago Manual of Style (17th edition)

wright1463148705
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© 2016, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.