The Feminist Pedagogy Project

Author: D’Ignazio, C.

Creative Data Literacy: A Constructionist Approach to Teaching Information Visualization

Author(s):	D’ignazio, C. Bhargava, R.
Date:	2018
Publication:	Digital Humanities Quarterly
Citation:	D’ignazio, C. & Bhargava, R. (2018). Creative Data Literacy: A Constructionist Approach to Teaching Information Visualization. Digital Humanities Quarterly, 12(4). https://hdl.handle.net/1721.1/123473

Section on webpage:	Critical Data Justice Literature
Tenets:	Using technology intentionally to build communities and enhance learning.
Annotation:	(Abstract) Data visualization has rapidly become a standard approach to interrogating and understanding the world around us in domains that extend beyond the technical and scientific to arts, communications and services. In business settings the Data Scientist has become a recognized and valued role [Davenport and Patil 2012]. Journalism has re-oriented itself around data-driven storytelling as a potential saviour for an industry in peril [Howard 2014]. Governments are moving to more data-driven decision making, publishing open data portals and pondering visualization as an opportunity for citizen participation [Gurstein 2011]. This journal itself has numerous examples that use visualization tools and techniques within the digital humanities as a tool for exploration [Roberts-Smith et al. 2013] [Hoyt, Ponto, and Roy 2014] [Forlini, Hinrichs, and Moynihan 2016]. This boom in attention has led large new populations of learners into the field. Formal educational settings have rushed to create new approaches and introductions to this content, but often they fall back on traditional approaches to things such as scientific charting and graphing [Webber et al. 2014] [Calzada and Marzal 2013]. Many view data visualization as a new technology, which runs the risks of replicating old approaches without acknowledging the unique affordances and domains that data visualization relies upon. Data visualization is not simply another technology to integrate into education. It is visual argument and persuasion, far more closely associated with rhetoric and writing than spreadsheets [Zer-Aviv 2014]. In this paper we present novel approaches to learning technologies and activities, focused on novice learners entering the field of data driven storytelling. We begin with a deeper dive into the problems we see with introducing new learners into a field characterized by inequality, continue with a discussion of approaches for introducing technologies to education, and summarize the inspirational pedagogies we build on. We then offer some design principles and three activities as examples of the concept of creative data literacy. We assert that creative approaches grounded in constructionist educational theories are necessary to empower non-technical learners to be able to tell stories and argue for change with data.

February 11, 2026

The Numbers Don’t Speak for Themselves

Author(s):	D’Ignazio, C. Klein, L. F.
Date:	2020
Publication:	Data Feminism
Citation:	D’Ignazio, C. & Klein, L. F. (2020). The Numbers Don’t Speak for Themselves. In Data Feminism (149-172). MIT Press. https://doi.org/10.7551/mitpress/11805.003.0008

Section on webpage:	Critical Data Justice Literature
Tenets:	Using technology intentionally to build communities and enhance learning.
Annotation:	In this chapter of Data Feminism, D’Ignazio and Klein introduce the principle of considering context, and walk through situating data on the web, viewing data as partisan, communicating context, and restoring context. Data feminism asserts that data are not neutral or objective. They are the products of unequal social relations, and this context is essential for conducting accurate, ethical analysis. The authors begin the chapter with an error made by media sources referencing the Global Database of Events, Language and Tone (GDELT), a database that, like many others, is characterized by a totalizing and dominating framework as enacted through data capture and analysis. They state that the contextualization of data is just as important as its availability, and provide the United States’s and Brazil’s apparent data transparency as examples; although the data is in theory available to the public, a lack of metadata and understanding of the government systems from which the data originate make it practically inaccessible to possible users. In this light, the authors advocate for a viewing of all data as “cooked” – that is, already a product of numerous social relations and data sorting methods.

February 11, 2026

Data visualization literacy: A feminist starting point

Author(s):	D’Ignazio, C. & Bhargava, R.
Date:	2020
Publication:	Data Visualization in Society
Citation:	D’Ignazio, C., & Bhargava, R. (2020). Data visualization literacy: A feminist starting point. In M. Engebretsen & H. Kennedy (Eds.), Data Visualization in Society (pp. 207–222). Amsterdam University Press. https://doi.org/10.2307/j.ctvzgb8c7.19

Section on webpage:	Critical Data Justice Literature
Tenets:	Using technology intentionally to build communities and enhance learning.
Annotation:	(Abstract) We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point that the human relations and impacts currently produced and reproduced through data are unequal. Likewise, white men remain overrepresented in data-related fields, even as other STEM (Science, Technology, Engineering and Medicine) fields have managed to narrow their gender gap. To address these inequalities, we introduce teaching methods that are grounded in feminist theory, process, and design. Through three case studies, we examine what feminism may have to offer visualization literacy, with the goals of cultivating self-efficacy for women and underrepresented groups to work with data, and creating learning spaces were, as Philip et al. (2016) state, ‘groups influence, resist, and transform everyday and formal processes of power that impact their lives.’

February 11, 2026

Creative Data Literacy: A Constructionist Approach to Teaching Information Visualization

Author(s):	D’ignazio, C. Bhargava, R.
Date:	2018
Publication:	Digital Humanities Quarterly
Citation:	D’ignazio, C. & Bhargava, R. (2018). Creative Data Literacy: A Constructionist Approach to Teaching Information Visualization. Digital Humanities Quarterly, 12(4). https://hdl.handle.net/1721.1/123473

Section on webpage:	Critical Data Justice Literature
Tenets:	Using technology intentionally to build communities and enhance learning.
Annotation:	(Abstract) Data visualization has rapidly become a standard approach to interrogating and understanding the world around us in domains that extend beyond the technical and scientific to arts, communications and services. In business settings the Data Scientist has become a recognized and valued role [Davenport and Patil 2012]. Journalism has re-oriented itself around data-driven storytelling as a potential saviour for an industry in peril [Howard 2014]. Governments are moving to more data-driven decision making, publishing open data portals and pondering visualization as an opportunity for citizen participation [Gurstein 2011]. This journal itself has numerous examples that use visualization tools and techniques within the digital humanities as a tool for exploration [Roberts-Smith et al. 2013] [Hoyt, Ponto, and Roy 2014] [Forlini, Hinrichs, and Moynihan 2016]. This boom in attention has led large new populations of learners into the field. Formal educational settings have rushed to create new approaches and introductions to this content, but often they fall back on traditional approaches to things such as scientific charting and graphing [Webber et al. 2014] [Calzada and Marzal 2013]. Many view data visualization as a new technology, which runs the risks of replicating old approaches without acknowledging the unique affordances and domains that data visualization relies upon. Data visualization is not simply another technology to integrate into education. It is visual argument and persuasion, far more closely associated with rhetoric and writing than spreadsheets [Zer-Aviv 2014]. In this paper we present novel approaches to learning technologies and activities, focused on novice learners entering the field of data driven storytelling. We begin with a deeper dive into the problems we see with introducing new learners into a field characterized by inequality, continue with a discussion of approaches for introducing technologies to education, and summarize the inspirational pedagogies we build on. We then offer some design principles and three activities as examples of the concept of creative data literacy. We assert that creative approaches grounded in constructionist educational theories are necessary to empower non-technical learners to be able to tell stories and argue for change with data.

The Numbers Don’t Speak for Themselves

Author(s):	D’Ignazio, C. Klein, L. F.
Date:	2020
Publication:	Data Feminism
Citation:	D’Ignazio, C. & Klein, L. F. (2020). The Numbers Don’t Speak for Themselves. In Data Feminism (149-172). MIT Press. https://doi.org/10.7551/mitpress/11805.003.0008

Section on webpage:	Critical Data Justice Literature
Tenets:	Using technology intentionally to build communities and enhance learning.
Annotation:	In this chapter of Data Feminism, D’Ignazio and Klein introduce the principle of considering context, and walk through situating data on the web, viewing data as partisan, communicating context, and restoring context. Data feminism asserts that data are not neutral or objective. They are the products of unequal social relations, and this context is essential for conducting accurate, ethical analysis. The authors begin the chapter with an error made by media sources referencing the Global Database of Events, Language and Tone (GDELT), a database that, like many others, is characterized by a totalizing and dominating framework as enacted through data capture and analysis. They state that the contextualization of data is just as important as its availability, and provide the United States’s and Brazil’s apparent data transparency as examples; although the data is in theory available to the public, a lack of metadata and understanding of the government systems from which the data originate make it practically inaccessible to possible users. In this light, the authors advocate for a viewing of all data as “cooked” – that is, already a product of numerous social relations and data sorting methods.

Data visualization literacy: A feminist starting point

Author(s):	D’Ignazio, C. & Bhargava, R.
Date:	2020
Publication:	Data Visualization in Society
Citation:	D’Ignazio, C., & Bhargava, R. (2020). Data visualization literacy: A feminist starting point. In M. Engebretsen & H. Kennedy (Eds.), Data Visualization in Society (pp. 207–222). Amsterdam University Press. https://doi.org/10.2307/j.ctvzgb8c7.19

Section on webpage:	Critical Data Justice Literature
Tenets:	Using technology intentionally to build communities and enhance learning.
Annotation:	(Abstract) We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point that the human relations and impacts currently produced and reproduced through data are unequal. Likewise, white men remain overrepresented in data-related fields, even as other STEM (Science, Technology, Engineering and Medicine) fields have managed to narrow their gender gap. To address these inequalities, we introduce teaching methods that are grounded in feminist theory, process, and design. Through three case studies, we examine what feminism may have to offer visualization literacy, with the goals of cultivating self-efficacy for women and underrepresented groups to work with data, and creating learning spaces were, as Philip et al. (2016) state, ‘groups influence, resist, and transform everyday and formal processes of power that impact their lives.’