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Authors: André Pimenta 1 ; Sergio Gonçalves 2 ; Davide Carneiro 1 ; Florentino Fde-riverola 2 ; José Neves 1 and Paulo Novais 1

Affiliations: 1 University of Minho, Portugal ; 2 University of Vigo, Spain

Keyword(s): Mental Workload, Mental Fatigue, Machine Learning, e-Learning, Fatigue Management, Human Performance.

Related Ontology Subjects/Areas/Topics: Adaptive Systems ; Ambient Intelligence ; Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Context ; Context-Aware Applications ; Detection and Estimation ; Digital Signal Processing ; Embedded Communications Systems ; Enterprise Information Systems ; Human and Computer Interaction ; Human-Computer Interaction ; Mobile and Pervasive Computing ; Paradigm Trends ; Pervasive Health ; Real-Time Systems ; Software Engineering ; Telecommunications

Abstract: In our daily life, we often have a sense of being exhausted due to mental or physical work, together with a feeling of performance degradation in the accomplishment of simple tasks. This is in part due to the fact that the working capacity and the performance of an individual, either physical or mental, generally decrease as the day progresses, although factors like motivation also play a significant role. These negative effects are especially significant when carrying out long or demanding tasks, as often happens in an educational context. In order to avoid these effects, initiatives to promote a good management of the time and effort invested in each task are mandatory. Such initiatives, when effective, can have a wide range of positive effects, including on the performance, productivity, attention and even mental health. Seeking to find a viable and realistic approach to address this problem, this paper presents a non-invasive and non-intrusive way to measure mental workload, one of the aspects that affects mental fatigue the most. Specifically, we target scenarios of e-learning, in which the professor may not be present to assess the student’s state. The aim is to create a tool that enables an actual management of fatigue in such environments and thus allows for the implementation of more efficient learning processes, adapted to the abilities and state of each student. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Pimenta, A.; Gonçalves, S.; Carneiro, D.; Fde-riverola, F.; Neves, J. and Novais, P. (2015). Mental Workload Management as a Tool in e-Learning Scenarios. In Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - PECCS; ISBN 978-989-758-084-0; ISSN 2184-2817, SciTePress, pages 25-32. DOI: 10.5220/0005237700250032

@conference{peccs15,
author={André Pimenta. and Sergio Gon\c{C}alves. and Davide Carneiro. and Florentino Fde{-}riverola. and José Neves. and Paulo Novais.},
title={Mental Workload Management as a Tool in e-Learning Scenarios},
booktitle={Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - PECCS},
year={2015},
pages={25-32},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005237700250032},
isbn={978-989-758-084-0},
issn={2184-2817},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems - PECCS
TI - Mental Workload Management as a Tool in e-Learning Scenarios
SN - 978-989-758-084-0
IS - 2184-2817
AU - Pimenta, A.
AU - Gonçalves, S.
AU - Carneiro, D.
AU - Fde-riverola, F.
AU - Neves, J.
AU - Novais, P.
PY - 2015
SP - 25
EP - 32
DO - 10.5220/0005237700250032
PB - SciTePress