Armani, Federica and Daly, Ian and Vernitski, Alexei and Gillmeister, Helge and Scherer, Reinhold (2023) Maths Anxiety and cognitive state monitoring for neuroadaptive learning systems using electroencephalography. In: IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), 2023-10-25 - 2023-10-27, Milano, Italy. (In Press)
Armani, Federica and Daly, Ian and Vernitski, Alexei and Gillmeister, Helge and Scherer, Reinhold (2023) Maths Anxiety and cognitive state monitoring for neuroadaptive learning systems using electroencephalography. In: IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), 2023-10-25 - 2023-10-27, Milano, Italy. (In Press)
Armani, Federica and Daly, Ian and Vernitski, Alexei and Gillmeister, Helge and Scherer, Reinhold (2023) Maths Anxiety and cognitive state monitoring for neuroadaptive learning systems using electroencephalography. In: IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), 2023-10-25 - 2023-10-27, Milano, Italy. (In Press)
Abstract
Mathematical competence is important to acquire for everyday and professional purposes, but often represents a considerable hurdle for students, who may associate it with unpleasant experiences. Our goal is to use neuroscience and neural engineering to support students to improve their math- ematical understanding. More specifically, we are interested in the development of a non-invasive electroencephalogram (EEG)- based neuroadaptive Brain-Computer Interface (BCI) learning environment that optimizes learning outcomes by adapting the learning content provided according to the cognitive load of the learner. In this paper, we investigate what cognitive states occur when students with and without Math Anxiety learn to solve a math problem presented in the form of a novel computer puzzle. Results of an offline analysis of data recorded from 10 study participants suggest that different cognitive states occur, each with specific features that a BCI could potentially detect.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Published proceedings: _not provided_ |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of Faculty of Science and Health > Psychology, Department of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 24 Aug 2023 10:31 |
Last Modified: | 21 Sep 2024 05:38 |
URI: | http://repository.essex.ac.uk/id/eprint/36150 |
Available files
Filename: IEEE_conference_paper_Milan_2023__Copy_for_upload_.pdf