Opportunities for K-8 Students to Learn Statistics Created by States’ Standards in the United States

References

• Achieve. (2017), Strong Standards: A Review of Changes to State Standards since the Common Core. Washington, DC: Achieve.
   Google Scholar
• Apple, M. W. (1992), “Do the Standards Go far Enough? Power, Policy, and Practice in Mathematics Education,” Journal for Research in Mathematics Education, 23, 412. DOI: https://doi.org/10.2307/749562.
   Web of Science ®Google Scholar
• Barclay, E., Scott, D., and Animashaun, C. (2020). “Coronavirus USA Chart: Flattening the Curve and “Raising the Line” of Hospital Capacity.” Vox, April 7. https://www.vox.com/2020/4/7/21201260/coronavirus-usa-chart-mask-shortage-ventilators-flatten-the-curve
   Google Scholar
• Bargagliotti, A., Franklin, C., Arnold, P., Gould, R., Johnson, S., Perez, L., and Spangler, D. (2020), Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II) (2nd ed.). American Statistical Association, https://www.amstat.org/education/guidelines-for-assessment-and-instruction-in-statistics-education-(gaise)-reports.
   Google Scholar
• Bargagliotti, A. E. (2012), “How Well do the NSF Funded Elementary Mathematics Curricula Align with the GAISE Report Recommendations,” Journal of Statistics Education, 20, 1–26.
   Google Scholar
• Ben-Zvi, D., and Garfield, J. (2008), “Introducing the Emerging Discipline of Statistics Education,” School Science and Mathematics, 108, 355–361. DOI: https://doi.org/10.1111/j.1949-8594.2008.tb17850.x.
   Google Scholar
• Carver, R., Everson, M., Gabrosek, J., Horton, N., Lock, R., Mocko, M., … and Wood, B. (2016). Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report 2016. American Statistical Association. https://www.amstat.org/docs/default-source/amstat-documents/gaisecollege_full.pdf
   Google Scholar
• Cobb, G. W., and Moore, D. S. (1997), “Mathematics, Statistics, and Teaching,” The American Mathematical Monthly, 104, 801–823. DOI: https://doi.org/10.1080/00029890.1997.11990723.
   Web of Science ®Google Scholar
• Confrey, J. (2010), “‘Both and’—Equity and Mathematics: A Response to Martin, Gholson, and Leonard,” Journal of Urban Mathematics Education, 3, 25–33.
   Google Scholar
• Dingman, S., Teuscher, D., Newton, J. A., and Kasmer, L. (2013), “Common Mathematics Standards in the United States: A Comparison of K–8 State and Common Core Standards,” The Elementary School Journal, 113, 541–564. DOI: https://doi.org/10.1086/669939.
   Web of Science ®Google Scholar
• Franklin, C., Kader, G., Mewborn, D., Moreno, J., Peck, R., Perry, M., and Scheaffer, R. (2007), Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report: A Pre-K–12 Curriculum Framework. American Statistical Association, https://www.amstat.org/education/guidelines-for-assessment-and-instruction-in-statistics-education-(gaise)-reports.
   Google Scholar
• Goertz, M. E. (2010), “National Standards: Lessons from the Past, Directions for the Future.” In Mathematics Curriculum: Issues, Trends, and Future Direction, 72nd Yearbook, eds. B. Reys, R. Reys, and R. Rheta, pp. 51–64. Reston, VA: National Council of Teachers of Mathematics.
   Google Scholar
• Groth, R. E. (2013), “Characterizing Key Developmental Understandings and Pedagogically Powerful Ideas within a Statistical Knowledge for Teaching Framework,” Mathematical Thinking and Learning, 15, 121–145. DOI: https://doi.org/10.1080/10986065.2013.770718.
   Web of Science ®Google Scholar
• Jones, D. L., and Jacobbe, T. (2014), “An Analysis of the Statistical Content in Textbooks for Prospective Elementary Teachers,” Journal of Statistics Education, 22, 1–18.
   Google Scholar
• Jones, D. L., Brown, M., Dunkle, A., Hixon, L., Yoder, N., and Silbernick, Z. (2015), “The Statistical Content of Elementary School Mathematics Textbooks,” Journal of Statistics Education, 23, 1–22.
   Google Scholar
• Los Angeles Unified School District. (n.d.), MOBILIZE. Available at https://achieve.lausd.net/Page/6764. Accessed July 8, 2021
   Google Scholar
• Martin, D. B., Gholson, M. L., and Leonard, J. (2010), “Mathematics as Gatekeeper: Power and Privilege in the Production of Knowledge,” Journal of Urban Mathematics Education, 3, 12–24.
   Google Scholar
• Martinez, W., and LaLonde, D. (2020), “Data Science for Everyone Starts in Kindergarten: Strategies and Initiatives from the American Statistical Association,” Harvard Data Science Review, 2. DOI: https://doi.org/10.1162/99608f92.7a9f2f4d.
   Google Scholar
• McClure, P. (2005). “Where Standards Come From,” Theory Into Practice, 44(1), 4–10. DOI: https://doi.org/10.1207/s15430421tip4401_2.
   Web of Science ®Google Scholar
• Montana Department of Public Instruction. (2011), Montana Content Standards for Mathematics. http://opi.mt.gov/LinkClick.aspx?fileticket=5YWhUY9cbKU%3d&portalid=182
   Google Scholar
• National Council of Teachers of Mathematics (NCTM). (2000), Principles and Standards for School Mathematics. Reston, VA: National Council of Teachers of Mathematics, Inc.
   Google Scholar
• National Council of Teachers of Mathematics (NCTM). (2020a), Catalyzing Change in Early Childhood and Elementary Mathematics: Initiating Critical Conversations. Reston, VA: National Council of Teachers of Mathematics.
   Google Scholar
• National Council of Teachers of Mathematics (NCTM). (2020b), Catalyzing Change in Middle School Mathematics: Initiating Critical Conversations. Reston, VA: National Council of Teachers of Mathematics.
   Google Scholar
• National Governors Association Center for Best Practices [NGA Center] and Council of Chief State School Officers [CCSSO]. (2010), Common Core State Standards for Mathematics. Authors. http://www.corestandards.org/assets/CCSSI_Math%20Standards.pdf
   Google Scholar
• Newton, J., Horvath, A., and Dietiker, L. (2011), “The Statistical Process: A View Across the K-8 State Standards.” In Variability is the Rule: A Companion Analysis of K-8 State Mathematics Standards, pp. 119–159. Charlotte, NC: Information Age Publishing.
   Google Scholar
• NGSS Lead States. (2013), Next Generation Science Standards: For States, by States. Washington DC: The National Academies Press.
   Google Scholar
• Orrill, C. H. (2016), “The Process Is Just Messy: A Historical Perspective on Adoption of Innovations,” The Mathematics Educator, 25, 71–94.
   Google Scholar
• Remillard, J. (2000), “Can Curriculum Materials Support Teachers’ Learning? Two Fourth-Grade Teachers’ Use of a New Mathematics Text,” The Elementary School Journal, 100, 331–350. DOI: https://doi.org/10.1086/499645.
   Web of Science ®Google Scholar
• Remillard, J., and Heck, D. J. (2014), “Conceptualizing the Curriculum Enactment Process in Mathematics Education,” ZDM, 46, 705–718. DOI: https://doi.org/10.1007/s11858-014-0600-4.
   Google Scholar
• Robson, D. (2020). “Exponential Growth Bias: The Numerical Error Behind Covid-19.” BBC, August 12. https://www.bbc.com/future/article/20200812-exponential-growth-bias-the-numerical-error-behind-covid-19
   Google Scholar
• Scheaffer, R. L., and Jacobbe, T. (2014), “Statistics Education in the K-12 Schools of the United States: A Brief History,” Journal of Statistics Education, 22. https://doi.org/https://doi.org/10.1080/10691898.2014.11889705
   Google Scholar
• Schmidt, W. H., and McKnight, C. C. (2012), Inequality for All: The Challenge of Unequal Opportunity in American Schools. New York, NY: Teachers College Press.
   Google Scholar
• Schmidt, W. H., Wang, H. C., and McKnight, C. C. (2005), “Curriculum Coherence: An Examination of US Mathematics and Science Content Standards from an International Perspective,” Journal of Curriculum Studies, 37, 525–559. DOI: https://doi.org/10.1080/0022027042000294682.
   Web of Science ®Google Scholar
• Stein, M., and Smith, M. (2010), “The Influence of Curriculum on Students’ Learning.” In Mathematics Curriculum: Issues, Trends, and Future Direction, 72nd Yearbook, eds. B. Reys, R. Reys, and R. Rubenstien, pp. 351–362). Reston, VA: National Council of Teachers of Mathematics.
   Google Scholar
• Stein, M., Remillard, J., and Smith, M. (2007), “How Curriculum Influences Student Learning.” In Second Handbook of Research on Mathematics Teaching and Learning, eds. F. K. Lester, pp. 319–369. Charlotte, NC: Information Age Publishing.
   Google Scholar
• Tarr, J. E., Reys, R. E., Reys, B. J., Chávez, Ó., Shih, J., and Osterlind, S. J. (2008), “The Impact of Middle-Grades Mathematics Curricula and the Classroom Learning Environment on Student Achievement,” Journal for Research in Mathematics Education, 39, 247–280.
   Web of Science ®Google Scholar
• The Common Core Standards Writing Team. (2011), Progressions for the Common Core State Standards in Mathematics (Draft): 6–8 Statistics and Probability.
   Google Scholar
• United Nations. (2003), Literacy Prerequisite for Reaching Global Anti-Poverty Goals Says Secretary-General in Literacy Day Message [Press Release], May 9. https://www.un.org/press/en/2003/sgsm8849.doc.htm
   Google Scholar
• Usiskin, Z. (2014), “On the Relationships Between Statistics and Other Subjects in the K-12 Curriculum.” Sustainability in Statistics Education. CHANGE, Flagstaff, AZ, https://doi.org/10.1080/09332480.2015.1099361.
   Google Scholar
• Weiland, T. (2017), “Problematizing Statistical Literacy: An Intersection of Critical and Statistical Literacies,” Educational Studies in Mathematics, 96, 33–47. DOI: https://doi.org/10.1007/s10649-017-9764-5.
   Web of Science ®Google Scholar
• Weiland, T. (2019), “The Contextualized Situations Constructed as Appropriate for the Use of Statistics by School Mathematics Texts,” Statistics Education Research Journal, 18, 18–38. https://iase-web.org/documents/SERJ/SERJ18(2)_Weiland.pdf?1576862349 DOI: https://doi.org/10.52041/serj.v18i2.138.
   Google Scholar
• Westheimer, J., and Kahne, J. (2004), “What Kind of Citizen? The Politics of Educating for Democracy,” American Educational Research Journal, 41, 237–269. DOI: https://doi.org/10.3102/00028312041002237.
   Web of Science ®Google Scholar
• Wild, C. J., and Pfannkuch, M. (1999), “Statistical Thinking in Empirical Enquiry,” International Statistical Review, 67, 223–248. DOI: https://doi.org/10.1111/j.1751-5823.1999.tb00442.x.
   Web of Science ®Google Scholar