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Authors: Saleh Mozaffari 1 ; 2 ; 3 ; Mohammad Al-Naser 1 ; 2 ; Pascal Klein 1 ; 2 ; Stefan Küchemann 2 ; Jochen Kuhn 2 ; Thomas Widmann 3 and Andreas Dengel 1 ; 2

Affiliations: 1 German Research Center for Artificial Intelligence (DFKI GmbH), Kaiserslautern, Germany ; 2 Technische Universität Kaiserslautern, Kaiserslautern, Germany ; 3 WidasConcepts GmbH, Wimsheim, Germany

Keyword(s): Eye Tracking, Classification, Physics, Education.

Abstract: In this study, we taught 20 physics students two different visual strategies to graphically interpret the physical meaning of vector field divergence. Using eye-tracking technology, we recorded students’ eye-movement behavior of both strategies when they were engaged in graphical vector field representations. From the eye-tracking data we extracted the number of fixations and saccadic direction and proposed a linear SVM model to classify strategies of problem-solving in the vector field domain. The results show different gaze patterns for the two strategies, and the influence of vector flow orientation on gaze-patterns. A high accuracy of 81.2%(0.11%) has been achieved by testing the algorithm using cross-validation, i.e. that the algorithm is able to predict the strategy the student applies to judge the divergence of a vector field. The results provide guiding tools for learning-effective instruction design and teachers gain benefit from monitoring the students’ non-verbal level of performance and fluency using each strategy. Apart from that, students would receive the objective feedback on their progress of learning. (More)

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Paper citation in several formats:
Mozaffari, S.; Al-Naser, M.; Klein, P.; Küchemann, S.; Kuhn, J.; Widmann, T. and Dengel, A. (2020). Classification of Visual Strategies in Physics Vector Field Problem-solving. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-395-7; ISSN 2184-433X, SciTePress, pages 257-267. DOI: 10.5220/0009173902570267

@conference{icaart20,
author={Saleh Mozaffari. and Mohammad Al{-}Naser. and Pascal Klein. and Stefan Küchemann. and Jochen Kuhn. and Thomas Widmann. and Andreas Dengel.},
title={Classification of Visual Strategies in Physics Vector Field Problem-solving},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2020},
pages={257-267},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009173902570267},
isbn={978-989-758-395-7},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Classification of Visual Strategies in Physics Vector Field Problem-solving
SN - 978-989-758-395-7
IS - 2184-433X
AU - Mozaffari, S.
AU - Al-Naser, M.
AU - Klein, P.
AU - Küchemann, S.
AU - Kuhn, J.
AU - Widmann, T.
AU - Dengel, A.
PY - 2020
SP - 257
EP - 267
DO - 10.5220/0009173902570267
PB - SciTePress

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