Bop or Flop?: Integrating Music and Data Science in an Elementary Classroom

References

• Alper, B., Riche, N. H., Chevalier, F., Boy, J., & Sezgin, M. (2017). Visualization literacy at elementary school. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 5485–5497). https://doi.org/10.1145/3025453.3025877
   Google Scholar
• Arastoopour Irgens, G., & Herro, D. (2023). GROOVA: A data visualization tool for elementary school students co-designed by teachers and researchers. In Proceedings of the 17th International Society of the Learning Sciences Conference (ISLS). International Society of the Learning Sciences Conference (ISLS).
   Google Scholar
• Arastoopour Irgens, G., Hirsch, S., Herro, D., & Madison, M. (2023). Analyzing a teacher and researcher co-design partnership through the lens of communities of practice. Teaching and Teacher Education, 121, 103952. https://doi.org/10.1016/j.tate.2022.103952
   Web of Science ®Google Scholar
• Arce-Trigatti, P. (2021, October 28). The evolving world of education research-practice partnerships [Brookings]. Brown Center Chalkboard. https://www.brookings.edu/blog/brown-center-chalkboard/2021/10/28/the-evolving-world-of-education-research-practice-partnerships/
   Google Scholar
• Bae, S., Yang, R., Gyory, P., Uhr, J., Szafir, D. A., & Do, E. Y.-L. (2021). Touching information with diy paper charts & ar markers [Paper presentation]. Interaction Design and Children (pp. 433–438). https://doi.org/10.1145/3459990.3465191
   Google Scholar
• Bargagliotti, A., Arnold, P., & Franklin, C. (2021). GAISE II: Bringing data into classrooms. Mathematics Teacher: Learning and Teaching PK-12, 114(6), 424–435. https://doi.org/10.5951/MTLT.2020.0343
   Google Scholar
• Bishop, F., Zagermann, J., Pfeil, U., Sanderson, G., Reiterer, H., & Hinrichs, U. (2020). Construct-A-Vis: Exploring the free-form visualization processes of children. IEEE Transactions on Visualization and Computer Graphics, 26(1), 451–460. https://doi.org/10.1109/TVCG.2019.2934804
   PubMed Web of Science ®Google Scholar
• Boaler, J., Levitt, S. D. (2019, October 23). Opinion: Modern high school math should be about data science—not Algebra 2. Los Angeles Times. https://www.latimes.com/opinion/story/2019-10-23/math-high-school-algebra-data-statistics
   Google Scholar
• Boaler, J., Munson, J., & Williams, C. (2019). Mindset mathematics: visualizing and investigating big ideas, grade 7. John Wiley & Sons.
   Google Scholar
• Bowen, G. M., & Bartley, A. (2020). Helping students make sense of the “real world” data mess. Science Activities, 57(4), 143–153. https://doi.org/10.1080/00368121.2020.1843387
   Web of Science ®Google Scholar
• Coburn, C. E., Penuel, W. R., & Farrell, C. C. (2021). Fostering educational improvement with research-practice partnerships. Phi Delta Kappan, 102(7), 14–19. https://doi.org/10.1177/00317217211007332
   Web of Science ®Google Scholar
• Coburn, C. E., & Penuel, W. R. (2016). Research–Practice Partnerships in education: Outcomes, dynamics, and open questions. Educational Researcher, 45(1), 48–54. https://doi.org/10.3102/0013189X16631750
   Web of Science ®Google Scholar
• Connelly, F. M., & Clandinin, D. J. (1990). Stories of experience and narrative inquiry. Educational Researcher, 19(5), 2–14. https://doi.org/10.3102/0013189X019005002
   Google Scholar
• Clandinin, D. J. (2006). Narrative inquiry: A methodology for studying lived experience. Research Studies in Music Education, 27(1), 44–54. https://doi.org/10.1177/1321103X060270010301
   Google Scholar
• Creswell, J. W. (2007). Qualitative enquiry and research design: Choosing among five approaches. Sage Publications.
   Google Scholar
• Cromartie, J. (2019). USDA ERS - What is Rural? U.S. Department of Agriculture. https://www.ers.usda.gov/topics/rural-economy-population/rural-classifications/what-is-rural/au
   Google Scholar
• Dahms, M., Geonnotti, K., Passalacqua, J. N., Schilk, J. N., Wetzel, A., & Zulkowsky, M. (2007). The educational theory of Lev Vygotsky: An analysis. New Foundations Press.
   Google Scholar
• Davenport, T. (2013, January 31). Telling a story with data: Communicating effectively with analytics. Deloitte Insights. https://www2.deloitte.com/us/en/insights/deloitte-review/issue-12/telling-a-story-with-data.html
   Google Scholar
• Derry, S. J., Pea, R. D., Barron, B., Engle, R. A., Erickson, F., Goldman, R., Hall, R., Koschmann, T., Lemke, J. L., Sherin, M. G., & Sherin, B. L. (2010). Conducting video research in the learning sciences: Guidance on selection, analysis, technology, and ethics. Journal of the Learning Sciences, 19(1), 3–53. https://doi.org/10.1080/10508400903452884
   Web of Science ®Google Scholar
• Donovan, M. S., Snow, C. E., & Huyghe, A. (2021). Differentiating research-practice partnerships: Affordances, constraints, criteria, and strategies for achieving success. Studies in Educational Evaluation, 71, 101083. https://doi.org/10.1016/j.stueduc.2021.101083
   Web of Science ®Google Scholar
• Drozda, Z., Johnstone, D., & Van Horne, B. (2022). Previewing the National Landscape of K-12 Data Science Implementation [Workshop on Foundations of Data Science for Students in Grades K-12]. National Academies. https://www.nationalacademies.org/documents/embed/link/LF2255DA3DD1C41C0A42D3BEF0989ACAECE3053A6A9B/file/D688ED916E82498DA0E2171A109936D679FD5DE26556?noSaveAs=1
   Google Scholar
• Farrell, C. C., Penuel, W. R., Coburn, C. E. Daniel, J. & Steup, L. (2021). Research-Practice Partnerships in Education: The State of the Field. William T. Grant Foundation.
   Google Scholar
• Gutiérrez, K. D., Morales, P. Z., & Martinez, D. C. (2009). Re-mediating literacy: Culture, difference, and learning for students from nondominant communities. Review of Research in Education, 33(1), 212–245. https://doi.org/10.3102/0091732X08328267
   Web of Science ®Google Scholar
• Gutiérrez, K., & Rogoff, B. (2003). Cultural ways of learning: Individual traits or repertoires of practice. Educational Researcher, 32(5), 19–25. https://doi.org/10.3102/0013189X032005019
   Google Scholar
• Harvey, L. (2015). Beyond member-checking: A dialogic approach to the research interview. International Journal of Research & Method in Education, 38(1), 23–38. https://doi.org/10.1080/1743727X.2014.914487
   Web of Science ®Google Scholar
• Henrique, L. (2020). Top Spotify songs from 2010-2019 - BY YEAR. (Version 1) [dataset]. Kaggle. https://www.kaggle.com/datasets/leonardopena/top-spotify-songs-from-20102019-by-year
   Google Scholar
• Herro, D., Madison, M., Arastoopour Irgens, G., Hirsch, S., Abimbade, O., & Adisa, O. (2022). Exploring elementary teachers’ perceptions of data science and curriculum co-design through professional development. Journal of Technology and Teacher Education, 30(4), 493–525.
   Google Scholar
• Kahn, J. B., & Jiang, S. (2021). Examining how youth build comparative models in storytelling with large, complex data and visualization tools. In E. de Vries, Y. Hod, & J. Ahn (Eds.), Proceedings of the 15th International Conference of the Learning Sciences - ICLS 2021 (pp. 677–680). International Society of the Learning Sciences. https://repository.isls.org//handle/1/7555
   Google Scholar
• Kahn, J. (2020). Learning at the intersection of self and society: The family geobiography as a context for data science education. Journal of the Learning Sciences, 29(1), 57–80. https://doi.org/10.1080/10508406.2019.1693377
   Web of Science ®Google Scholar
• Kjelvik, M. K., & Schultheis, E. H. (2019). Getting messy with authentic data: Exploring the potential of using data from scientific research to support student data literacy. CBE—Life Sciences Education, 18(2), es2. https://doi.org/10.1187/cbe.18-02-0023
   PubMed Web of Science ®Google Scholar
• Klar, H. W., Huggins, K. S., Buskey, F. C., Desmangles, J. K., & Phelps-Ward, R. J. (2018). Developing social capital for collaboration in a research-practice partnership. Journal of Professional Capital and Community, 3(4), 287–305. https://doi.org/10.1108/JPCC-01-2018-0005
   Web of Science ®Google Scholar
• Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals. Wiley.
   Google Scholar
• LaMar, T., & Boaler, J. (2021). The importance and emergence of K-12 data science. Phi Delta Kappan, 103(1), 49–53. https://doi.org/10.1177/00317217211043627
   Web of Science ®Google Scholar
• Leary, H., & Severance, S. (2018). Research-practice partnerships: Addressing K-12 educational problems through active collaborations. In R. M. Branch (Ed.), Educational media and technology yearbook (Vol. 41, pp. 73–81) Springer International Publishing. https://doi.org/10.1007/978-3-319-67301-1_6
   Google Scholar
• Lee, V. R., & Drake, J. (2013). Quantified recess: Design of an activity for elementary students involving analyses of their own movement data. In Proceedings of the 12th International Conference on Interaction Design and Children (pp. 273–276).
   Google Scholar
• Lee, V. R., & Thomas, J. M. (2011). Integrating physical activity data technologies into elementary school classrooms. Educational Technology Research and Development, 59(6), 865–884. https://doi.org/10.1007/s11423-011-9210-9
   Web of Science ®Google Scholar
• Lee, V. R., & Wilkerson, M. (2018). Data Use by Middle and Secondary Students in the Digital Age: A Status Report and Future Prospects (Commissioned Paper for the National Academies of Sciences, Engineering, and Medicine, Board on Science Education). Committee on Science Investigations and Engineering Design for Grades 6-12, p. 43.
   Google Scholar
• Lee, V. R., Drake, J. R., & Thayne, J. L. (2016). Appropriating quantified self technologies to support elementary statistical teaching and learning. IEEE Transactions on Learning Technologies, 9(4), 354–365. https://doi.org/10.1109/TLT.2016.2597142
   Web of Science ®Google Scholar
• Lee, V. R., Wilkerson, M. H., & Lanouette, K. (2021). A call for a humanistic stance toward K–12 data science education. Educational Researcher, 50(9), 664–672. https://doi.org/10.3102/0013189X211048810
   Google Scholar
• Lehrer, R., & Schauble, L. (2000). Inventing Data Structures for Representational Purposes: Elementary Grade Students’ Classification Models. Mathematical Thinking and Learning, 2(1-2), 51–74. https://doi.org/10.1207/S15327833MTL0202_3
   Google Scholar
• Martinez, W., & LaLonde, D. (2020). Data science for everyone starts in kindergarten: Strategies and initiatives from the American statistical association. Harvard Data Science Review, 2(3). https://doi.org/10.1162/99608f92.7a9f2f4d
   Google Scholar
• Matei, S. A., & Hunter, L. (2021). Data storytelling is not storytelling with data: A framework for storytelling in science communication and data journalism. The Information Society, 37(5), 312–322. https://doi.org/10.1080/01972243.2021.1951415
   Web of Science ®Google Scholar
• Merriam, S. (2009). Qualitative research: A guide to design and implementation. John-Wiley & Sons.
   Google Scholar
• Mike, K. (2020). Data science education: Curriculum and pedagogy. In Proceedings of the 2020 ACM Conference on International Computing Education Research (pp. 324–325). https://doi.org/10.1145/3372782.3407110
   Google Scholar
• Nasir, N., Rosebery, A., Warren, B., & Lee, C. (2005). Learning as a cultural process: Achieving equity through diversity. In R. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 489–504). Cambridge University Press.
   Google Scholar
• National Science & Technology Council. (2018). Charting a course for success: America’s strategy for STEM education. https://www.energy.gov/sites/default/files/2019/05/f62/STEM-Education-Strategic-Plan-2018.pdf
   Google Scholar
• Potter, D., Baumgartner, E., & Turley, R. N. L. (2021). Reducing educational inequality through research-practice partnerships. Phi Delta Kappan, 102(7), 26–29. https://doi.org/10.1177/00317217211007334
   Web of Science ®Google Scholar
• Rorrer, A., Pugalee, D., Edwards, C., Boulden, D., Maher, M. L., Cao, L., Dorodchi, M., Catete, V., Frye, D., Barnes, T., & Wiebe, E. (2021). The design and implementation of a method for evaluating and building research-practice partnerships. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 753–759). https://doi.org/10.1145/3408877.3432532
   Google Scholar
• Rosebery, A. S., Ogonowski, M., DiSchino, M., & Warren, B. (2010). “The Coat Traps All Your Body Heat”: Heterogeneity as fundamental to learning. Journal of the Learning Sciences, 19(3), 322–357. https://doi.org/10.1080/10508406.2010.491752
   Web of Science ®Google Scholar
• Rubin, A. (2020). Learning to reason with data: How did we get here and what do we know? Journal of the Learning Sciences, 29(1), 154–164. https://doi.org/10.1080/10508406.2019.1705665
   Web of Science ®Google Scholar
• Segel, E., & Heer, J. (2010). Narrative visualization: Telling stories with data. IEEE Transactions on Visualization and Computer Graphics, 16(6), 1139–1148. https://doi.org/10.1109/TVCG.2010.179
   PubMed Web of Science ®Google Scholar
• Shreiner, T. L. (2018). Data literacy for social studies: Examining the role of data visualizations in K–12 textbooks. Theory & Research in Social Education, 46(2), 194–231. https://doi.org/10.1080/00933104.2017.1400483
   Web of Science ®Google Scholar
• Tranquillo, J., & Matthew, V. (2015, September 8). So you want to offer a pop-up class? Epicenter. http://epicenter.stanford.edu/resource/so-you-want-to-offer-a-pop-up-class.html
   Google Scholar
• Vora, S. (2019). The power of data storytelling. SAGE Publications.
   Google Scholar
• Vygotsky, L. S., & Cole, M. (1978). Mind in society: Development of higher psychological processes. Harvard University Press.
   Google Scholar
• Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5
   Web of Science ®Google Scholar
• Wilkerson, M. H., & Laina, V. (2018). Middle school students’ reasoning about data and context through storytelling with repurposed local data. ZDM, 50(7), 1223–1235. https://doi.org/10.1007/s11858-018-0974-9
   Google Scholar
• Wilkerson, M., Finzer, W., Erickson, T., & Hernandez, D. (2021). Reflective data storytelling for youth: The CODAP Story Builder. Interaction Design and Children (pp. 503–507). https://doi.org/10.1145/3459990.3465177
   Google Scholar
• Yin, R. K. (2017). Case study research and applications: design and methods (6th ed.). SAGE Publications, Inc.
   Google Scholar