An Eye-Tracking Study on the Effects of Using Highlighted Multi-attribute Tables: A Preliminary Report

Masahiro Morii, Takashi Ideno, Yuki Tamari, Kazuhisa Takemura, Mitsuhiro Okada

研究成果: Conference contribution査読

抄録

Our previous research, aimed at improving the design of multi-attribute tables (such as product catalogs), found that black-and-white graphics aided decision-making more than numerical or textual formats (Ideno et al., Diagrams 2020). We extended these findings by examining how combining graphic and numerical presentation (highlighting the cells with superior values) influences decision-making. Twenty-one participants chose the most desirable digital cameras from five alternatives. Results showed faster decision-making with highlighted cells compared to non-highlighted ones. A two-stage decision strategy emerged, with more attribute-based gaze shifts initially and equal vertical and horizontal shifts later. We discussed the implications and prospects of highlighted multi-attribute tables.

本文言語English
ホスト出版物のタイトルDiagrammatic Representation and Inference - 14th International Conference, Diagrams 2024, Proceedings
編集者Jens Lemanski, Reetu Bhattacharjee, Mikkel Willum Johansen, Emmanuel Manalo, Petrucio Viana, Richard Burns
出版社Springer Science and Business Media Deutschland GmbH
ページ467-471
ページ数5
ISBN(印刷版)9783031712906
DOI
出版ステータスPublished - 2024
イベント14th International Conference on the Theory and Application of Diagrams, DIAGRAMS 2024 - Münster, Germany
継続期間: 27 9月 20241 10月 2024

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
14981 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference14th International Conference on the Theory and Application of Diagrams, DIAGRAMS 2024
国/地域Germany
CityMünster
Period27/09/241/10/24

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