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Evaluating similarity measures for gaze patterns in the context of representational competence in physics education

Published: 14 June 2018 Publication History

Abstract

The competent handling of representations is required for understanding physics' concepts, developing problem-solving skills, and achieving scientific expertise. Using eye-tracking methodology, we present the contributions of this paper as follows: We first investigated the preferences of students with the different levels of knowledge; experts, intermediates, and novices, in representational competence in the domain of physics problem-solving. It reveals that experts more likely prefer to use vector than other representations. Besides, a similar tendency of table representation usage was observed in all groups. Also, diagram representation has been used less than others. Secondly, we evaluated three similarity measures; Levenshtein distance, transition entropy, and Jensen-Shannon divergence. Conducting Recursive Feature Elimination technique suggests Jensen-Shannon divergence is the best discriminating feature among the three. However, investigation on mutual dependency of the features implies transition entropy mutually links between two other features where it has mutual information with Levenshtein distance (Maximal Information Coefficient = 0.44) and has a correlation with Jensen-Shannon divergence (r(18313) = 0.70, p < .001).

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  • (2024)“The way I see it makes me believe you intentionally did it”: Intentionality ascription and gaze transition entropy in violent offendersBiological Psychology10.1016/j.biopsycho.2024.108962(108962)Online publication date: Dec-2024
  • (2022)The relationship between visual confirmation bias, belief consistency, and belief polarizationComprehensive Results in Social Psychology10.1080/23743603.2022.20262146:1-3(1-38)Online publication date: 10-May-2022
  • (2020)Improving natural language processing tasks with human gaze-guided neural attentionProceedings of the 34th International Conference on Neural Information Processing Systems10.5555/3495724.3496255(6327-6341)Online publication date: 6-Dec-2020
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cover image ACM Conferences
ETRA '18: Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications
June 2018
595 pages
ISBN:9781450357067
DOI:10.1145/3204493
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 June 2018

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Author Tags

  1. eye-tracking
  2. feature selection
  3. gaze patterns
  4. physics
  5. representational competence
  6. similarity measures

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Overall Acceptance Rate 69 of 137 submissions, 50%

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Cited By

View all
  • (2024)“The way I see it makes me believe you intentionally did it”: Intentionality ascription and gaze transition entropy in violent offendersBiological Psychology10.1016/j.biopsycho.2024.108962(108962)Online publication date: Dec-2024
  • (2022)The relationship between visual confirmation bias, belief consistency, and belief polarizationComprehensive Results in Social Psychology10.1080/23743603.2022.20262146:1-3(1-38)Online publication date: 10-May-2022
  • (2020)Improving natural language processing tasks with human gaze-guided neural attentionProceedings of the 34th International Conference on Neural Information Processing Systems10.5555/3495724.3496255(6327-6341)Online publication date: 6-Dec-2020
  • (2020)Quantifying Gaze-Based Strategic Patterns in Physics Vector Field DivergenceAgents and Artificial Intelligence10.1007/978-3-030-71158-0_22(465-481)Online publication date: 22-Feb-2020

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