Co-Editors:
Amelia Acker (University of Texas Austin)
Leanne Bowler (Pratt Institute)
Luci Pangrazio (Deakin University)
For this Special Issue, we invite papers exploring current perspectives in learning and information research and teaching on data literacies among learners, addressing the growing need for a data literate society. Future job prospects hinge on the ability to participate and use datafied systems and processes, which requires the ability to read, analyze, reason with, and argue with multiple forms of data. But equally, people are themselves subjects of data, being thoroughly measured, tracked, and analyzed through their personal digital data created with everyday information and communication technologies. Contemporary data subjectivity, built on data traces and their near constant collection, affects people’s most basic sense of autonomy and agency in life. As well, there is a wide disconnect between the data practices of government and corporations and the data skills, knowledge, and level of awareness of the general public (Deahl, 2014; Qlik, 2019).
Many people, whether young or old, have difficulty transferring an awareness of data into critical practice. For example, data literacies research with teens has shown that they have limited “data imaginations” when it comes to critical thinking about data (Pangrazio & Selwyn, 2021) and they find it difficult to connect with data at a concrete and personal level (Bowler et al, 2017). Educators may face the same issue as teens. In work that looked at library-based learning about data, the library staff, although armed with a general awareness of datafication, used a confusing array of interpretations for data and data skills to describe data literacy (Bowler et al, 2019). The multiple approaches to data literacy (i.e., data literacies) highlight the need for more research that more clearly establishes data literacy definitions, frameworks and models, and collaborates with teachers to develop responsive teacher training and “training the trainer” models.
A consideration of the socio-technical environment can contribute to contextualizing the scope and affordances of technologies used to make and meaningfully interact with data. For example, ubiquity of mobile computing suggests that more inclusive and robust frameworks are needed for explaining the networked, distributed, and multiple device and upgrade cycle into present-day understandings of data management skills (Acker & Bowler, 2018). We might also consider what data literacies education should look like in a world where algorithmic interventions are up-ending notions of human agency (Sefton-Green & Pangrazio, 2021).
Competence and deep engagement with data is a complex array of socio-technical skills, knowledge, humanistic reasoning, as well as a set of dispositions that facilitate the ability to critique data practices, to contextualize data within platforms, cyberinfrastructure, and society, and to find meaning in data beyond statistical and mathematical arguments. This special issue challenges researchers to shift the frame from a one-size fits all account of literacy to literacies of data. We are in the early days of building a body of research and practical models on data literacies in pedagogy, design, and use. (Pangrazio & Sefton-Green, 2020; Wolff, Wermelinger, & Petre, 2019). We need a clearer picture as to what theoretic approaches, pedagogy, and curriculum best supports knowledge and understanding about data. Also needed are nuanced discussions about how the social, cultural, political, and technical contexts of data, data justice, and the datafication of everyday life inform data literacies pedagogy.
Scope:
The guest editors invite research addressing teaching and learning related to data literacies in primary and secondary school (K-12) and at the undergraduate level, as well as informal spaces of learning such as libraries and after-school programs, and among learners and publics of all ages.
Submissions from a broad range of disciplines, including information science, the learning sciences, and science and technology studies, among others are welcome.
We welcome work offering new data literacy theory / frameworks / definitions, design and implementation research, practice theories, and well-contextualized cross-sectional research exploring data literacy levels among groups / publics / contexts, perhaps addressing inequality. Justice-oriented frameworks, sociotechnical lenses, and other approaches appropriate to the topic of data literacies in varying information and learning contexts are invited.
Sample topics (just to name a few):
- Definitions, evidence-based examples, practical guidance, and critiques of existing practices in the field of data literacy.
- Challenges and opportunities of critical data education. Educational approaches that apply critical pedagogy and analyses that account for the power and politics of data.
- Teaching about data in ways that account for algorithmic interventions, associated socio-technical arrangements, and technology contexts that are data driven.
- Data literacy as civics education (i.e., educating the public in the use of open data).
- Data literacy as cybersecurity education (i.e., personal data management and privacy);
- Reports and critiques of school-based data literacy instruction in relation to learning outcomes and state standards.
- Informal, community-based learning and data literacy.
Submission deadline: May 31, 2023
For inquiries we invite you to email the guest editors by way of Dr. Bowler at: [email protected]
References:
Acker, A. & Bowler, L. (2018). Youth Data Literacy: Teen Perspectives on Data Created with Social Media and Mobile Device Ownership. Hawaii International Conference on System Sciences 2018 (HICCS). January 3-6, 2018.
Bowler, L., Acker, A., & Chi, Y. (2019). Perspectives on Youth Data Literacy at the Public Library: Teen Services Staff Speak Out. The Journal of Research on Libraries and Young Adults, 10(2), July 2019.
Bowler, L., Acker, A., Jeng, W. and Chi, Y. (2017). “It lives all around us”: Aspects of data literacy in teen's lives. In S. Erdelez & N.K. Agarwal (Eds.), Proceedings of the Association for Information Science and Technology (pp. 27– 35.) Hoboken, NJ: Wiley. Available at https://doi.org/10.1002/pra2.2017.14505401004
Deahl, E. (2014). Better the data you know: Developing youth data literacy in schools and informal learning environments. Available at SSRN 2445621.
Pangrazio, L., & Sefton-Green, J. (2020). The social utility of ‘data literacy’. Learning, Media and Technology, 45(2), 208-220.
Pangrazio, L., & Selwyn, N. (2021). Towards a school-based ‘critical data education’. Pedagogy, Culture & Society, 29(3), 431-448.
Qlik. Lead with Data: How to Drive Data Literacy in the Enterprise. White paper. (2019). Retrieved from, https://tdwi.org/whitepapers/2019/04/bi-all-lead-with-data-how-to-drive-data-literacy-in-the-enterprise.aspx
Sefton-Green, J., & Pangrazio, L. (2021). The death of the educative subject? The limits of criticality under datafication. Educational Philosophy and Theory, 1-10.
Wolff, A., Wermelinger, M., & Petre, M. (2019). Exploring design principles for data literacy activities to support children’s inquiries from complex data. International Journal of Human-Computer Studies, 129, 41-54.