DataBasic: Design Principles, Tools and Activities for Data Literacy Learners

The growing number of tools for data novices are not designed with the goal of learning in mind. This paper proposes a set of pedagogical design principles for tool development to support data literacy learners.  We document their use in the creation of three digital tools and activities that help learners build data literacy, showing design decisions driven by our pedagogy. Sketches students created during the activities reflect their adeptness with key data literacy skills. Based on early results, we suggest that tool designers and educators should orient their work from the outset around strong pedagogical principles

Data Feminism

A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed

Data Murals: Using the Arts to Build Data Literacy

Current efforts to build data literacy focus on technology-centered approaches, overlooking creative non-digital opportunities. This case study is an example of how to implement a Popular Education-inspired approach to building participatory and impactful data literacy using a set of visual arts activities with students at an alternative school in Belo Horizonte, Brazil.  As a result of the project data literacy among participants increased, and the project initiated a sustained interest within the school community in using data to tell stories and create social change

`I make up a silly name': Understanding Children's Perception of Privacy Risks Online

Children under 11 are often regarded as too young to comprehend the implications of online privacy. Perhaps as a result, little research has focused on younger kids' risk recognition and coping. Such knowledge is, however, critical for designing efficient safeguarding mechanisms for this age group. Through 12 focus group studies with 29 children aged 6-10 from UK schools, we examined how children described privacy risks related to their use of tablet computers and what information was used by them to identify threats. We found that children could identify and articulate certain privacy risks well, such as information oversharing or revealing real identities online; however, they had less awareness with respect to other risks, such as online tracking or game promotions. Our findings offer promising directions for supporting children's awareness of cyber risks and the ability to protect themselves online.Comment: 13 pages, 1 figur

From Creating Spaces for Civic Discourse to Creating Resources for Action

In this paper, we investigate the role of technology to address the concerns of a civil society group carrying out community-level consultation on the allocation of £1 million of community funds. We explore issues of devolved decision-making through the evaluation of a sociodigital system designed to foster deliberative virtues. We describe the ways in which this group used our system in their consultation practices. Our findings highlight how they adopted our technology to privilege specific forms of expression, ascertain issues in their community, make use of and make sense of community data, and create resources for action within their existing practices. Based on related fieldwork we discuss the impacts of structuring and configuring tools for ‘talk-based’ consultation in order to turn attention to the potential pitfalls and prospects for designing civic technologies that create resources for action for civil society

Designing Tools and Activities for Data Literacy Learners

Data-centric thinking is rapidly becoming vital to the way we work, communicate and understand in the 21st century. This has led to a proliferation of tools for novices that help them operate on data to clean, process, aggregate, and visualize it. Unfortunately, these tools have been designed to support users rather than learners that are trying to develop strong data literacy. This paper outlines a basic definition of data literacy and uses it to analyze the tools in this space. Based on this analysis, we propose a set of pedagogical design principles to guide the development of tools and activities that help learners build data literacy. We outline a rationale for these tools to be strongly focused, well guided, very inviting, and highly expandable. Based on these principles, we offer an example of a tool and accompanying activity that we created. Reviewing the tool as a case study, we outline design decisions that align it with our pedagogy. Discussing the activity that we led in academic classroom settings with undergraduate and graduate students, we show how the sketches students created while using the tool reflect their adeptness with key data literacy skills based on our definition. With these early results in mind, we suggest that to better support the growing number of people learning to read and speak with data, tool de- signers and educators must design from the start with these strong pedagogical principles in mind

Teaching Data Journalism in a World of Tool and Tech Overload

The field of journalism is undergoing systemic disruption, with the subarea of data journalism transforming rapidly due to the introduction of new tools and techniques as well as the changes in reporting practices as journalists and newsrooms experiment and innovate. This paper explores the challenges for data journalism educators to teach in such a rapidly shifting landscape. Drawing from our experiences teaching journalism students in higher education, we assert that the goal of data journalism education amidst this complexity is not to teach tech, nor even to teach technical skills, but rather to model for students strategies of dealing with transformation and complexity. These include peer learning, hands-on learning activities, modeling learning and information seeking, and establishing a culture of critique. We introduce a number of activities that put those approaches into practice, drawing on learning literature to support our fellow educators shifting from the ”banking model” of education[10] to a learner-centered model[23]. Working with students to co-create knowledge, acting as a ”Guide on the Side”[15] can help better prepare students for the constantly evolving ecosystem of technologies and tools that support data journalism