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Predicting Java Computer Programming Task Difficulty Levels Using EEG for Educational Environments

Palaniappan, Ramaswamy and Duraisingam, Aruna and Chinnaiah, Nithyakalyani and Murugappan, Murugappan (2019) Predicting Java Computer Programming Task Difficulty Levels Using EEG for Educational Environments. In: Lecture Notes in Computer Science. Springer, Netherlands, pp. 446-460. ISBN 978-3-030-22418-9. (doi:10.1007/978-3-030-22419-6_32) (KAR id:71265)

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Official URL:
http://dx.doi.org/10.1007/978-3-030-22419-6_32

Abstract

Understanding how difficult a learning task is for a person allows teaching material to be appropriately designed to suit the person, especially for programming material. A first step for this would be to predict on the task difficulty level. While this is possible through subjective questionnaire, it could lead to misleading outcome and it would be better to do this by tapping the actual thought process in the brain while the subject is performing the task, which can be done using electroencephalogram. We set out on this objective and show that it is possible to predict easy and difficult levels of mental tasks when subjects are attempting to solve Java programming problems. Using a proposed confidence threshold, we obtained a classification performance of 87.05% thereby showing that it is possible to use brain data to determine the teaching material difficulty level which will be useful in educational environments.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-030-22419-6_32
Uncontrolled keywords: Confidence threshold Education EEG Java Mental task level NASA TLX Programming task
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Palaniappan Ramaswamy
Date Deposited: 18 Dec 2018 14:32 UTC
Last Modified: 07 Nov 2021 11:33 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/71265 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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