Design failures in data visualization programming activities

Autor(es)

Fernandez, Cassia ; Blikstein, Paulo ; Lopes, Roseli de Deus

• Tipo de documento: Artigo Científico
• Fonte: PROCEEDINGS OF ACM INTERACTION DESIGN AND CHILDREN CONFERENCE, IDC 2024; v. N/A, p. 13-pg., 2024-01-01.

Resumo

As data science education becomes a topic of interest for researchers and educators, several tools and curricula have been proposed to engage pre-collegiate students in data-related activities [15,17,21,25]. Data science is a complex and interdisciplinary field, encompassing mathematics, statistics, computer science, and graphic design, besides disciplinary knowledge [10,12,17]. Data science also involves a wide array of fundamental skills, including data generation, storage, transformation, interpretation, and visualization [30], as well as concepts such as variability, aggregation, context, and inference [26]. Given the complexity of the field, the design and documentation of educational approaches that address specific knowledge and skills involved in data science are central to advancing the way children may learn with data. Data visualization stands as a core component of data literacy. Currently, educational tools predominantly rely on the selection of templates for constructing visualizations. This approach can automate the work but obscures the fundamental process of mapping data values to representational forms while also restricting the possibility of exploring novel types of visual displays [26]. Intending to provide students with opportunities to engage in data visualization tasks in more inventive and reflexive ways, over the past years we have been developing a new block-based programming tool for data visualization purposes [PlayData; 11]. Throughout this process, we conducted several studies and workshops with students of varying ages to understand how they used the tool for creating visualizations and derived meaning from them. This process involved not only refining iteratively the tool but also the activities associated with it. Despite the potential we foresaw for the tool, we observed several challenges when implementing activities with children. In this paper, we critically analyze how students engaged in data representation activities using PlayData, describing challenges that arose from either unexpected uses of the tool or shortcomings in the design of activities. We also detail how we leveraged these challenges as opportunities for enhancing the design of both the tool and the associated activities. We conclude by presenting recommendations for the design of activities where visualizations are effectively connected to reasoning with data. (AU)

• Processo FAPESP: 22/06977-5 - Estudo de implementação de inovações curriculares, estratégias pedagógicas e tecnologias emergentes para qualidade-equidade na educação básica
• Beneficiário: Mauricio Pietrocola Pinto de Oliveira
• Modalidade de apoio: Auxílio à Pesquisa - Temático