Inoculating students against misleading data visualizations with perceptual training and informative feedback

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Jihyun Rho , Martina Angela Rau , Xiaojin Zhu
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引用次数: 0

Abstract

Misleading visualizations are a form of misinformation that distort data interpretation, leading to misunderstandings and poor decision-making. Despite their prevalence in both traditional and digital media, there is limited research on effective educational interventions that help students recognize and resist such deceptive visualization techniques. In this study, we developed a perceptual training intervention specifically designed to inoculate students against misleading visualizations. Unlike traditional perceptual trainings that typically involve only correct visuals, trainings for misleading visualizations require the inclusion of erroneous visual examples. While the informative feedback can help students to efficiently recognize such misleading visualizations and extract correct information, it may also disrupt the inductive learning during training, potentially reducing its overall effectiveness. To shed light into these possibilities, we investigated the role of informative feedback in a perceptual training designed for misleading visualizations. We conducted two experiments with large samples of undergraduate students (Experiment 1: N = 252, Experiment 2: N = 244). Experiment 1 tested the short-term effects of different informative feedback types during perceptual training, while Experiment 2 examined both the long-term retention (after one month) and near transfer to novel misleading visualizations. Results showed that informative feedback significantly improved students’ accuracy and efficiency in detecting misleading features within visualizations. Students also transferred these skills to novel misleading visualization types, and critically the benefits of informative feedback were sustained over a month. These results highlight the potential of perceptual trainings with informative feedback to inoculate students against misleading visualizations, offering valuable guidance for the development of educational interventions aimed at mitigating the effects of visual misinformation.
通过知觉训练和信息反馈培养学生对误导性数据可视化的认知
误导性的可视化是一种歪曲数据解释的错误信息,导致误解和糟糕的决策。尽管它们在传统媒体和数字媒体中都很流行,但关于有效教育干预的研究有限,这些干预可以帮助学生识别和抵制这种欺骗性的可视化技术。在这项研究中,我们开发了一种知觉训练干预,专门用于预防学生误解视觉。传统的感知训练通常只涉及正确的视觉效果,而误导视觉效果的训练需要包括错误的视觉例子。虽然信息反馈可以帮助学生有效地识别这种误导性的可视化并提取正确的信息,但它也可能在训练过程中破坏归纳学习,潜在地降低归纳学习的整体效果。为了阐明这些可能性,我们研究了信息反馈在设计用于误导性可视化的感知训练中的作用。我们对本科生进行了两个大样本实验(实验1:N = 252,实验2:N = 244)。实验1测试了知觉训练中不同信息反馈类型的短期效果,而实验2测试了对新的误导性视觉的长期保留(一个月后)和近迁移。结果表明,信息性反馈显著提高了学生在视觉化中发现误导性特征的准确性和效率。学生们还将这些技能转化为新颖的误导性可视化类型,关键的是,信息反馈的好处持续了一个多月。这些结果强调了具有信息反馈的感知训练的潜力,可以使学生预防误导性的视觉化,为旨在减轻视觉错误信息影响的教育干预的发展提供有价值的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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