Measuring Cognition in Computer-Based Instruction Using an EEG: A Review of the Literature
PROCEEDINGS
Enilda Romero, University of Tampa, United States
EdMedia + Innovate Learning, in Tampere, Finland ISBN 978-1-939797-08-7 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
Abstract
This paper discusses the use and implementation of the EEG as a measurement tool of cognitive processes during the learning experience. More specifically, the paper discusses the use of EEG to enhance analysis and understanding of the cognition during computer-based instruction. Normally, the method of monitoring the learner’s cognitive processes during the learning process commonly takes the form of behavior observation and self-reporting instruments. These measurements may be difficult to interpret and monitor. However, EEG provides an alternative method that allows online, continuous, and objective measurement of cognition at specific points in time as learners interact with computer-based instruction. This paper provides an overview of research studies that have successfully implemented EEG in education research and computer-based instruction as a measure of different cognitive processes during the learning experience.
Citation
Romero, E. (2014). Measuring Cognition in Computer-Based Instruction Using an EEG: A Review of the Literature. In J. Viteli & M. Leikomaa (Eds.), Proceedings of EdMedia 2014--World Conference on Educational Media and Technology (pp. 2487-2496). Tampere, Finland: Association for the Advancement of Computing in Education (AACE). Retrieved June 6, 2023 from https://www.learntechlib.org/primary/p/147828/.
© 2014 Association for the Advancement of Computing in Education (AACE)
Keywords
References
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Assessing the Learning Experiences of Geriatric Learners during Web-Based Instruction with Neurophysiological Methods
JoAnne Scott, Instructional Design Practitioner & Researcher, United States; Enilda Romero-Hall, University of Tampa, United States
EdMedia + Innovate Learning 2017 (Jun 20, 2017) pp. 1186–1191
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