Adventures in data literacy: When the gap you were trying to identify turns out to be a chasm.
DOI:
https://doi.org/10.29173/iq1138Keywords:
Data Literacy, Data Visualization, GIS, Knowledge Mobilization, Academic LibrariesAbstract
In an era where post-secondary students are seen as digital natives and novel knowledge mobilization is becoming an expected part of scholarly discourse, this paper synthesizes insights from multiple surveys about this topic. This research was conducted in 2020 and 2022 with participants from programs across the University of Manitoba (a Canadian public research university of around 30,000 students). This paper aims to illuminate the campus landscape and assess library support and resources for research visualization; additionally, the authors also explore challenges and potential pathways for improvement.
References
Acosta, M. L., Sisley, A., Ross, J., Brailsford, I., Bhargava, A., Jacobs, R., & Anstice, N. (2018). Student acceptance of e-learning methods in the laboratory class in Optometry. PLOS ONE, 13(12), e0209004. https://doi.org/10.1371/journal.pone.0209004
Ain, Q., Aslam, M., Muhammad, S., Awan, S., Pervez, M. T., Naveed, N., Basit, A., & Qadri, S. (2016). A technique to increase the usability of e-learning websites. Pakistan Journal of Science, 68(2), 164-169.
Al Hashlamoun, N., & Daouk, L. (2020). Information technology teachers’ perceptions of the benefits and efficacy of using online communities of practice when teaching computer skills classes. Education and Information Technologies, 25(6), 5753–5770. https://doi.org/10.1007/s10639-020-10242-z
Burton, M., & Lyon, L. (2017). Data science in libraries. Bulletin of the American Society for Information Science and Technology, 43(4), 33-35. https://doi.org/10.1002/bul2.2017.1720430409
Charmaz, K. (2014). Constructing grounded theory (2nd ed.). Sage.
Chin Roemer, R., & Kern, V. (Eds.). (2019). The culture of digital scholarship in academic libraries American Library Association.
Diaz, C. (2018, June 7). Jekyll and institutional repositories. Northwestern University Research and Data Repository. https://arch.library.northwestern.edu/concern/generic_works/6q182k274
Dykes, B. (2016). Data storytelling: The essential data science skill everyone needs. Forbes. https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/
Fouh, E., Akbar, M., & Shaffer, C. A. (2012). The role of visualization in computer science education. Computers in the Schools, 29(1–2), 95–117. https://doi.org/10.1080/07380569.2012.651422
Harding, A., & Engelbrecht, J. (2015). Personal learning network clusters: A comparison between mathematics and computer science students. Educational Technology & Society, 18(3), 173–184. https://www.jstor.org/stable/jeductechsoci.18.3.173
Harmon, J. E., & Gross, A. G. (2010). The craft of scientific communication. University of Chicago Press.
Henshaw, A. L., & Meinke, S. R. (2018). Data analysis and data visualization as active learning in Political Science. Journal of Political Science Education, 14(4), 423–439. https://doi.org/10.1080/15512169.2017.1419875
Herther, N. K. (2019). Library Carpentry: A toolkit for researchers. Information Today, 36(3), 16–18.
Neville, T., & Crampsie, C. (2019). From journal selection to open access: Practices among academic librarian scholars. portal: Libraries and the Academy, 19(4), 591–613. https://doi.org/10.1353/pla.2019.0037
Newson, K. (2017). Tools and workflows for collaborating on static website projects. The Code4Lib Journal, 38. https://journal.code4lib.org/articles/12779
Pagowsky, N., & McElroy, K. (2016). Critical library pedagogy handbook: Essays and workbook activities Association of College and Research Libraries.
Pugachev, S. (2019). What Are “The Carpentries” and what are they doing in the library? portal: Libraries and the Academy, 19(2), 209–214. https://doi.org/10.1353/pla.2019.0011
Rickles, P., Ellul, C., & Haklay, M. (2017). A suggested framework and guidelines for learning GIS in interdisciplinary research. Geo: Geography and Environment, 4(2), e00046. https://doi.org/10.1002/geo2.46
Saba, F., & Shearer, R. L. (2018). Transactional distance and adaptive learning: Planning for the future of higher education. Routledge. https://doi.org/10.4324/9780203731819
Stevens, H. (2016). [Review of the book Big data, little data, no data: Scholarship in the networked world, by Christine L. Borgman]. Technology and Culture, 57(3), 706–708. https://doi.org/10.1353/tech.2016.0099
Weller, M. (2011). The Digital scholar: How technology is transforming scholarly practice. Bloomsbury Academic. https://doi.org/10.5040/9781849666275
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