I am a learning scientist whose work explores computational literacy, with special focus on how young people learn about scientific computing tools such as computer simulation, data visualization, or statistical analysis packages. Tools like these have transformed how science and mathematics are done, and there are growing calls to incorporate them into K-12 education. However, while there is growing commitment among educators to teach science and mathematics “as practice,” scientific computing is still often presented simplistically in curriculum as a conceptual aid or accurate reproduction of the natural world. In fact, like other scientific tools, scientific computing requires careful interpretation and negotiation of its strengths, limits, and biases. And in order to truly support learner agency, students should be empowered to construct and adapt scientific computing tools themselves in order to advance their own explorations. My research addresses these issues by contributing theoretical development, design principles, and pedagogical strategies to more meaningfully introduce scientific computing to middle and high school learners.
As part of this, I conduct research and design software that allows youth to author simulations and visualizations by building on familiar expressive activities such as storytelling or sketching. I am especially interested in giving learners experience with these tools in ways that are tightly connected to, and therefore feasible within, the existing K-12 curriculum. This means I consult with teachers, learners, and after-school professionals at every stage of design to make sure the tools we create are usable, and focus not only on the design of practical materials but also of learning theory that can inform pedagogy and research more broadly. My designs, research and analyses are informed by theories of learning that illuminate (1) the rich and dynamic nature of knowledge, (2) the importance of empowering learners to share their own ideas using the languages of science and mathematics, and (3) the critical role that community, culture, and students' relationships to content play in the development of productive learning environments. You can learn more about me and my work at this link.
Wilkerson, M. H., Lanouette, K., & Shareff, R. L. (2021). Exploring variability during data preparation: A way to connect data, chance, and context when working with complex public datasets. Mathematical Thinking and Learning. doi: 10.1080/10986065.2021.1922838
Wilkerson, M. H. & Polman, J. L. (2020). Situating data science: Exploring how relationships to data shape learning [Special Issue]. Journal of the Learning Sciences, 29(1), 1-10. doi: 10.1080/10508406.2019.1705664
Wilkerson, M. H., D’Angelo, C. M., & Litts, B. K. (2020). Stories from the field: Locating and cultivating computational thinking in spaces of learning [Special Issue]. Interactive Learning Environments, 28(3), 264-271. doi: 10.1080/10494820.2020.1711326
Erickson, T., Wilkerson, M. H., Finzer, W., & Reichsman, F. (2019). Data moves. Technology Innovations in Statistics Education, 12(1).
Wilkerson, M. H. & Laina, V.* (2018). Middle school students’ reasoning about data and context through storytelling with repurposed local data. ZDM Mathematics Education, 50(7), 1223-1235. doi: 10.1007/s11858-018-0974-9
Wilkerson, M. H., Shareff, R.*, Laina, V.*, & Gravel, B. E. (2018). Epistemic gameplay and discovery in computational model-based inquiry activities. Instructional Science, 46(1), 35-60. doi: 10.1007/s11251-017-9430-4
Wilkerson, M. H. (2017). Teachers, students, and after-school professionals as designers of digital tools for learning. In C. DiSalvo, B. DiSalvo, J. Yip, & E. Bonsignore (Eds.), Participatory Design for Learning. Taylor & Francis. pp. 127-140.
Wilkerson, M. H., Andrews, C., Shaban, Y., Laina, V., & Gravel, B. E. (2016). What's the technology for? Teacher attention and pedagogical goals in a modeling-focused professional development workshop. Journal of Science Teacher Education, 27(1), 1-27. doi: 10.1007/s10972-016-9453-8 [Springer]
Wilkerson-Jerde, M. H. & Wilensky, U. (2015). Patterns, probabilities, and people: Making sense of quantitative change in complex systems. Journal of the Learning Sciences, 24(2), 204-251. doi: 10.1080/10508406.2014.976647 [PDF][Taylor & Francis]
Wilkerson-Jerde, M. H., Gravel, B. E., & Macrander, C. A. (2015). Exploring shifts in middle school learners’ modeling activity while generating drawings, animations, and simulations of molecular diffusion. Journal of Science Education and Technology, 24(2-3), 204-251. doi: 10.1007/s10956-014-9497-5. [PDF][Springer]
Interests and Professional Affiliations
Simulation Learning Environments
Technology and Schools
Classroom Learning Environments