Pub Date : 2022-10-01DOI: 10.1109/VIS4Good57762.2022.00006
Georges Hattab
Personalized learning, science education, and public understanding of science are linked in many ways. Studies of public understanding of science suggest that citizen science literacy is not just about reforming school science curricula. Understanding statistics is a challenge for many people, and customized learning methods are required. Statistics are useful for keeping records, calculating probabilities, and providing knowledge. Basically, they help us understand the world a little better through numbers and other quantitative information. Motivated by the overall goal of promoting understanding of statistical concepts and minimizing misinformation, thirteen gamification and data physicalization initiatives help us to offer ten challenges. They allow players to record, update, and explore the characteristics and differences between different statistical concepts. This work combines dynamic physical visualization and gamification to explain linear and exponential functions and a set of distributions using analog explicable cubes as a means of representation.
{"title":"Ten Challenges and Explainable Analogs of growth functions and distributions for statistical literacy and fluency","authors":"Georges Hattab","doi":"10.1109/VIS4Good57762.2022.00006","DOIUrl":"https://doi.org/10.1109/VIS4Good57762.2022.00006","url":null,"abstract":"Personalized learning, science education, and public understanding of science are linked in many ways. Studies of public understanding of science suggest that citizen science literacy is not just about reforming school science curricula. Understanding statistics is a challenge for many people, and customized learning methods are required. Statistics are useful for keeping records, calculating probabilities, and providing knowledge. Basically, they help us understand the world a little better through numbers and other quantitative information. Motivated by the overall goal of promoting understanding of statistical concepts and minimizing misinformation, thirteen gamification and data physicalization initiatives help us to offer ten challenges. They allow players to record, update, and explore the characteristics and differences between different statistical concepts. This work combines dynamic physical visualization and gamification to explain linear and exponential functions and a set of distributions using analog explicable cubes as a means of representation.","PeriodicalId":286704,"journal":{"name":"2022 IEEE Workshop on Visualization for Social Good (VIS4Good)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125724941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.1109/VIS4Good57762.2022.00005
D. Markant, Milad Rogha, Alireza Karduni, Ryan Wesslen, Wenwen Dou
Recent years have seen rapid growth in data-driven communication and the public availability of datasets on a broad set of social issues. Yet despite this unprecedented accessibility, the public often remains divided along partisan or ideological lines and to lack a common understanding of the issues at stake. In this paper we consider the role of data visualizations in communicating scientific evidence, and in particular, their power to persuade in the face of conflicting prior beliefs and attitudes. We describe a recent study showing that strong attitudes about politically polarized topics were associated with less belief change when interacting with statistical data visualizations. Moreover, there was little evidence for attitude change even when people updated their beliefs about specific empirical relationships. We then draw on research in cognitive science to identify elements of visualizations that may produce such attitude change because they encourage elaborative thinking when interacting with data. We argue for further research that considers how broader attitudes-which are tied to social identity, values, and worldviews-affect the power of data visualizations to persuade among communities with diverse ideological and cultural backgrounds.
{"title":"Can Data Visualizations Change Minds? Identifying Mechanisms of Elaborative Thinking and Persuasion","authors":"D. Markant, Milad Rogha, Alireza Karduni, Ryan Wesslen, Wenwen Dou","doi":"10.1109/VIS4Good57762.2022.00005","DOIUrl":"https://doi.org/10.1109/VIS4Good57762.2022.00005","url":null,"abstract":"Recent years have seen rapid growth in data-driven communication and the public availability of datasets on a broad set of social issues. Yet despite this unprecedented accessibility, the public often remains divided along partisan or ideological lines and to lack a common understanding of the issues at stake. In this paper we consider the role of data visualizations in communicating scientific evidence, and in particular, their power to persuade in the face of conflicting prior beliefs and attitudes. We describe a recent study showing that strong attitudes about politically polarized topics were associated with less belief change when interacting with statistical data visualizations. Moreover, there was little evidence for attitude change even when people updated their beliefs about specific empirical relationships. We then draw on research in cognitive science to identify elements of visualizations that may produce such attitude change because they encourage elaborative thinking when interacting with data. We argue for further research that considers how broader attitudes-which are tied to social identity, values, and worldviews-affect the power of data visualizations to persuade among communities with diverse ideological and cultural backgrounds.","PeriodicalId":286704,"journal":{"name":"2022 IEEE Workshop on Visualization for Social Good (VIS4Good)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114635925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-22DOI: 10.1109/VIS4Good57762.2022.00007
Lorenzo Ambrosini, Miriah D. Meyer
The Data Bricks Space Mission is a prototype activity based on data physicalization for teaching kids about data. The design of the activity is based on a literature review and interviews with elementary school teachers, and targets kids aged 10-12. Using Lego bricks and a fictional space adventure story, teachers can use the Data Bricks Space Mission activity to empower kids to produce data, communicate their findings, and gain a better understanding of the relationship between data and the world around them.
{"title":"Data Bricks Space Mission: Teaching Kids about Data with Physicalization","authors":"Lorenzo Ambrosini, Miriah D. Meyer","doi":"10.1109/VIS4Good57762.2022.00007","DOIUrl":"https://doi.org/10.1109/VIS4Good57762.2022.00007","url":null,"abstract":"The Data Bricks Space Mission is a prototype activity based on data physicalization for teaching kids about data. The design of the activity is based on a literature review and interviews with elementary school teachers, and targets kids aged 10-12. Using Lego bricks and a fictional space adventure story, teachers can use the Data Bricks Space Mission activity to empower kids to produce data, communicate their findings, and gain a better understanding of the relationship between data and the world around them.","PeriodicalId":286704,"journal":{"name":"2022 IEEE Workshop on Visualization for Social Good (VIS4Good)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123518056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：