Literature review on the competencies of data literacy for middle-grade learners
DOI:
https://doi.org/10.29173/iq1123Keywords:
data literacy, K-12 school settings, systematic review, middle-grade learnersAbstract
In today’s data-driven world, it is crucial for students to be data literate; able to view, understand, and reason with data in multimodal forms representing real-world phenomena. Despite its importance, data literacy is rarely integrated into K-12 curricula, and its definition remains unclear for this age group. This paper reviews existing literature to define the competencies relevant to adolescent learners and highlights those crucial for middle-grade students. A literature review of theoretical and empirical discussions on data literacy concepts, instructional practices, and assessments revealed eight key competencies. Among these, two were identified as most critical for middle-grade students: interpreting data representations and evaluating claims based on data representations. This paper aims to serve as a conceptual and practical guide to enhance data literacy in educational settings, providing a foundation for educators and researchers to collaboratively support middle-grade learners.
References
Aillerie, K., & McNicol, S. (2016). Information literacy and social networking sites: Challenges and stakes regarding teenagers’ uses. ESSACHESS–Journal for Communication Studies, 9(2-18), 89–100.
Ben-Zvi, D., & Arcavi, A. (2001). Junior high school students’ construction of global views of data and data representations. Educational Studies in Mathematics, 45, 35–65. https://doi.org/10.1023/A:1013809201228
Bowler, L., & Shaw, C. (2024). Trends in data literacy, 2018-2023: A review of the literature. Information Research an international electronic journal, 29(2), 198-205. https://doi.org/10.47989/ir292822
Büscher, C. (2022). Design principles for developing statistical literacy in middle schools. Statistics Education Research Journal, 21(1), 1–16. https://doi.org/10.52041/serj.v21i1.80
Bussert-Webb, K., & Henry, L. (2017). Promising digital practices for nondominant learners. International Journal of Educational Technology, 4(2), 43–55.
Callingham, R & Watson, J.M. (2017) The development of statistical literacy at school. Statistics Education Research Journal, 16(1), 181–201.
Calzada Prado, J. C., & Marzal, M. Á. (2013). Incorporating data literacy into information literacy programs: Core competencies and contents. Libri, 63(2), 123–134. https://doi.org/10.1515/libri-2013-0010
Chin, D. B., Blair, K. P., & Schwartz, D. L. (2016). Got game? A choice-based learning assessment of data literacy and visualization skills. Technology, Knowledge and Learning, 21(2), 195–210. https://doi.org/10.1007/s10758-016-9279-7
Cohen, J. D., Renken, M., & Calandra, B. (2017). Urban middle school students, twenty-first century skills, and STEM-ICT careers: Selected findings from a front-end analysis. TechTrends, 61, 380-385. https://doi.org/10.1007/s11528-017-0170-8
Cubarrubia, A. P. (2019, October 18). We all need to be data people. The Chronicle of Higher Education, 66(7). https://www.chronicle.com/article/we-all-need-to-be-data-people/
Cuervo Sánchez, S. L., Foronda Rojo, A., Rodriguez Martinez, A., & Medrano Samaniego, C. (2021)Media and information literacy: A measurement instrument for adolescents. Educational Review, 73(4), 487-502. https://doi.org/10.1080/00131911.2019.1646708
Cunningham, V., & Williams, D. (2018). The seven voices of information literacy (IL). Journal of information literacy, 12(2). http://dx.doi.org/10.11645/12.2.2332
Deahl, E. S. (2014). Better the data you know: Developing youth data literacy in schools and informal learning environments. [Master’s Thesis, the Massachusetts Institute of Technology]. https://doi.org/10.2139/ssrn.2445621
English, L. D., & Watson, J. (2018). Modelling with authentic data in sixth grade. ZDM Mathematics Education, 50(1–2), 103–115. https://doi.org/10.1007/s11858-017-0896-y
Ercegovac, Z. (2015). Data-driven society begins with data-savvy youth. Bulletin of the Association for Information Science & Technology, 42(1), 42–48. https://doi.org/10.1002/bul2.2015.1720420111
Erwin, R. W., Jr. (2015). Data literacy: Real-world learning through problem-solving with data sets. American Secondary Education, 43(2), 18–26. https://www.jstor.org/stable/43694208
Fontichiaro, K., & Oehrli, J. A. (2016). Why data literacy matters. Knowledge Quest, 44(5), 21–27. https://eric.ed.gov/?id=EJ1099487
Forzani, E. (2018). How well can students evaluate online science information? Contributions of prior knowledge, gender, socioeconomic status, and offline reading ability. Reading Research Quarterly, 53(4), 385–390. https://doi.org/10.1002/rrq.218
Gebre, E. (2022). Conceptions and perspectives of data literacy in secondary education. British Journal of Educational Technology, 53(5), 1080–1095. https://doi.org/10.1111/bjet.13246
Godaert, E., Aesaert, K., Voogt, J., & van Braak, J. (2022). Assessment of students’ digital competences in primary school: A systematic review. Education and Information Technologies, 27, 9953–10011. https://doi.org/10.1007/s10639-022-11020-9
Gordon, E., Elwood, S., & Mitchell, K. (2016). Critical spatial learning: Participatory mapping, spatial histories, and youth civic engagement. Children’s Geographies, 14, 1–15. https://doi.org/10.1080/14733285.2015.1136736
Gould, R. (2017). Data literacy is statistical literacy. Statistics Education Research Journal, 16(1), 22–25. https://doi.org/10.52041/serj.v16i1.209
Guler, M., Gursoy, K., & Guven, B. (2016). Critical views of 8th grade students toward statistical data in newspaper articles: Analysis in light of statistical literacy. Cogent Education, 3(1), http://dx.doi.org/10.1080/2331186X.2016.1268773
Gunter, G. A. (2007). Building student data literacy: An essential critical-thinking skill for the 21st Century. MultiMedia & Internet @ Schools, 14(3), 24–28.
Hullman, J., & Diakopoulos, N. (2011). Visualization rhetoric: Framing effects in narrative visualization. IEEE Transactions on Visualization and Computer Graphics, 17(12), 2231–2240. https://doi.org/10.1109/TVCG.2011.255
Hunter-Thomson, K. (2019). Data literacy 101: How do we set up graphs in science? Science Scope, 42(2), 78–82.
Kim, E. M., & Yang, S. (2016). Internet literacy and digital natives’ civic engagement: Internet skill literacy or Internet information literacy? Journal of Youth Studies, 19(4), 438–456. https://doi.org/10.1080/13676261.2015.1083961
Kostelnick, C. (2004). Melting-pot ideology, modernist aesthetics, and the emergence of graphical conventions: The statistical atlases of the United States, 1874–1925. In C. A. Hill & M. Helmers (Eds.), Defining visual rhetorics (pp. 215–242). Routledge.
Leu, D. J., Forzani, E., Burlingame, C., Kulikowich, J., Sedransk, N., Coiro, J., & Kennedy, C. (2013). The New Literacies of online research and comprehension: Assessing and preparing students for the 21st century with Common Core State Standards. In S. Neuman (Ed.), Quality Reading Instruction in the Age of Common Core Standards (pp. 219–236). International Reading Association.
Lipton, L., & Wellman, B. (2012). Got data? Now what? Creating and leading cultures of inquiry. Solution Tree Press.
Love, N. (2004). Taking data to new depths. Journal of Staff Development, 25(4), 22–26. https://all4ed.org/wp-content/uploads/2013/09/lovejsdarticle1.pdf
Mandinach, E. B., & Gummer, E. S. (2012). Navigating the landscape of data literacy: It IS complex. WestEd. https://eric.ed.gov/?id=ED582807
Manduca, C. A., & Mogk, D. W. (2002). Using data in undergraduate science classrooms: Final report on an interdisciplinary workshop held at Carleton College. https://d32ogoqmya1dw8.cloudfront.net/files/usingdata/UsingData.pdf
Oceans of Data Institute (ODI) (2015). Building global interest in data literacy: A dialogue. Educational Development Center. https://oceansofdata.org/our-work/building-global-interest-data-literacy-dialogue-workshop-report
Philip, T. M., Olivares-Pasillas, M. C., & Rocha, J. (2016). Becoming racially literate about data and data-literate about race: Data visualizations in the classroom as a site of racial-ideological micro-contestations. Cognition and Instruction, 34(4), 361–388. https://doi.org/10.1080/07370008.2016.1210418
Ridsdale, C., Rothwell, J., Smit, M., Ali-Hassan, H., Bliemel, M., Irvine, D., Kelley, D., Matwin, S., & Wuetherick, B. (2015). Strategies and best practices for data literacy education: Knowledge synthesis report. Dalhousie University. https://dalspaceb.library.dal.ca/server/api/core/bitstreams/7c0db868-79ac-4c3c-9ad0-f2a93cf2ccc6/content
Shields, M. (2005). Information literacy, statistical literacy, data literacy. IASSIST Quarterly, 28(2-3), 6–11. https://doi.org/10.29173/iq790
Seroff, J. (2017). Using data in the research process. In K. Fontichiaro, J. A. Oehrli, & A. Lennex (Eds.), Creating data literate students. Michigan Publishing.
Sorapure, M. (2019). Text, image, data, interaction: Understanding information visualization. Computers and Composition, 54, 1–16. https://doi.org/10.1016/j.compcom.2019.102519
Statewide Longitudinal Data Systems Grant Program. (2015). SLDS data use standards: Knowledge, skills, and professional behaviors for effective data use, version 2. U.S. Department of Education National Center for Education Statistics. https://eric.ed.gov/?id=ED595040
Surrain, S., & Luk, G. (2019). Describing bilinguals: A systematic review of labels and descriptions used in the literature between 2005–2015. Bilingualism: Language and Cognition, 22(2), 401-415. https://doi.org/10.1017/S1366728917000682
Turton, W., & Martin, A. (2020, January 5). How deepfakes make disinformation more real than ever. Bloomberg. https://www.bloomberg.com/news/articles/2024-02-09/fighting-deepfakes-whats-being-done-biden-robocalls-to-taylor-swift-ai-images
Twidale, M. B., Blake, C., & Gant, J. (2013). Towards a data literate citizenry. In Proceedings of iConference 2013 (pp. 247–257). https://hdl.handle.net/2142/38385
Vahey, P., Rafanan, K., Patton, C., Swan, K., Hooft, M., Kratcoski, A., & Stanford, T. (2012). A cross-disciplinary approach to teaching data literacy and proportionality. Educational Studies in Mathematics, 81(2), 179–205. https://doi.org/10.1007/s10649-012-9392-z
Vahey, P., Yarnall, L., Patton, C., Zalles, D., & Swan, K. (2006, April). Mathematizing middle school: Results from a cross-disciplinary study of data literacy. Presented at the American Educational Research Association Annual Conference, San Francisco, CA.
van’t Hooft, M., Swan, K., Cook, D., Stanford, T., Vahey, P., Kratcoski, A., Rafanan, K., & Yarnall, L. (2012). A cross-curricular approach to the development of data literacy in the middle grades: The Thinking with Data Project. Middle Grades Research Journal, 7(3), 19–33.
Viegas, F. B., & Wattenberg, M. (2006). Communication-minded visualization: A call to action. IBM Systems Journal, 45(4), 801–812. https://doi.org/10.1147/sj.454.0801
WestEd. (n.d.). Developing Assessments of Data Literacy. WestEd. https://www.wested.org/project/data-literacy-assessment-development/
Wolff, A., Gooch, D., Cavero Montaner, J. J, Rashid, U., Kortuem, G., (2016). Creating an understanding of data literacy for a data-driven society. The Journal of Community Informatics, 12(3), 9–26. https://doi.org/10.15353/joci.v12i3.3275
Womack, R. (2015). Data visualization and information literacy. IASSIST Quarterly, 38(1), 12–17. https://doi.org/10.29173/iq619
Wu, D., Yu, L., Yang, H. H., Zhu, S., & Tsai, C. C. (2020). Parents’ profiles concerning ICT proficiency and their relation to adolescents’ information literacy: A latent profile analysis approach. British Journal of Educational Technology, 51(6), 2268-2285. https://doi.org/10.1111/bjet.12899
Yates, S., Carmi, E., Lockley, E., Wessels, B. & Pawluczuk, A. (2021). Me and My Big Data: Understanding citizens data literacies. Nuffield Foundation. https://openaccess.city.ac.uk/id/eprint/26756/
Yolcu, A. (2014) Middle school students’ statistical literacy: Role of grade level and gender. Statistics Education Research Journal, 13(2), 118–131. https://doi.org/10.52041/serj.v13i2.285
Zalles, D. (2005). Designs for assessing foundational data literacy. https://serc.carleton.edu/files/NAGTWorkshops/assess/ZallesEssay3.pdf
Zoellick, B., Schauffler, M., Flubacher, M., Weatherbee, R., & Webber, H. (2016, April). Data literacy: Assessing student understanding of variability in data. Paper presented at the Annual Meeting of the National Association for Research in Science Teaching. Baltimore, MD.
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