With the identification of the Science and Engineering Practice “Using Mathematics and Computational Thinking,” the Next Generation Science Standards links math and computational thinking. This is a crucial connection, given that science practices have changed drastically over the years as a result of digital tools at the disposal of scientists. As a result, the sheer volume of data available necessitates an understanding of data management and analytics. To prepare middle school students to meet this challenge, the standards call for students to employ digital tools to analyze very large data sets for patterns and trends, use mathematical representations to describe and/or support scientific conclusions and design solutions, and create algorithms to solve a problem (NRC 2012). These expectations prepare students for possible STEM careers, careers that are undergoing rapid change as a result of the ability to use computer simulations and interactive visualizations in their work (Weintrop et al. 2015).

The importance of math and computational thinking cannot be understated. Math underpins the sciences and allows us to represent ideas with variables that can be manipulated and tested, and enables us to ask and answer questions related to how and why. Computational thinking allows us to generate and examine data through models and simulations that can predict phenomena. Ultimately, the more we embed mathematics and computational thinking into our teaching, the better prepared our students will be for their future. Many of us, however, have not trained to be math or computer science teachers. As research has found, one of the pivotal factors impacting student success in math is attributable to a student belief in the teacher’s efficacy when it comes to teaching (Kearney and Garfield 2019). It therefore becomes critical that we lobby for the professional development necessary to instill a level of comfort when it comes to implementing computation-based lessons. Ultimately, our efficacy will be tied to preparing our students for possible STEM careers in an era where understanding data management is crucial.

Patty McGinnis
Editor, Science Scope

Patty McGinnis is an instructional coach and veteran middle school teacher. You can contact her at pattymcginnis1@gmail.com or on Twitter: @patty_mcginnis.

References

Kearney, S., and T. Garfield. 2019. Student readiness to learn and teacher effectiveness: Two key factors in middle grades mathematics achievement. Research in Middle Level Education Online 42 (5): 1–12. https://doi.org/10.1080/19404476.2019.1607138

National Research Council (NRC). 2012. A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Washington, DC: National Academies Press.

Weintrop, D., E. Beheshti, M. Horn, K. Orton, K. Jona, L. Trouille, U. Wilensky. 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