Evan M. Peck, B. Yuksel, Lane Harrison, Alvitta Ottley, Remco Chang
{"title":"Towards a 3-dimensional model of individual cognitive differences: position paper","authors":"Evan M. Peck, B. Yuksel, Lane Harrison, Alvitta Ottley, Remco Chang","doi":"10.1145/2442576.2442582","DOIUrl":null,"url":null,"abstract":"The effects of individual differences on user interaction is a topic that has been explored for the last 25 years in HCI. Recently, the importance of this subject has been carried into the field of information visualization and consequently, there has been a wide range of research conducted in this area. However, there has been no consensus on which evaluation methods best answer the unique needs of information visualization. In this position paper we propose that individual differences are evaluated in three dominant dimensions: cognitive traits, cognitive states and experience/bias. We believe that this is a first step in systematically evaluating the effects of users' individual differences on information visualization and visual analytics.","PeriodicalId":235801,"journal":{"name":"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2442576.2442582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
The effects of individual differences on user interaction is a topic that has been explored for the last 25 years in HCI. Recently, the importance of this subject has been carried into the field of information visualization and consequently, there has been a wide range of research conducted in this area. However, there has been no consensus on which evaluation methods best answer the unique needs of information visualization. In this position paper we propose that individual differences are evaluated in three dominant dimensions: cognitive traits, cognitive states and experience/bias. We believe that this is a first step in systematically evaluating the effects of users' individual differences on information visualization and visual analytics.
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