CoRE Lab

Berkeley School of EducatioN

Author: Michelle

Michelle

  • Learning from “Interpretations of Innovation”

    Wilkerson, M. H., Shareff, R. L., & Laina, V. (2022). Learning from “interpretations of innovation” in the codesign of digital tools. In M-C. Shanahan, B. Kim, M. A. Takeuchi, K. Koh, A. P. Preciado-Babb, & P. Sengupta (Eds.), The Learning Sciences in Conversation: Theories, Methodologies, and Boundary Spaces. Routledge.

  • Erin wins Best Student Paper Award!

    Erin Foley was awarded a Best Student Paper award by the Special Interest Group in Learning Sciences and Advanced Technologies for Learning at AERA 2022! Foley, E. & Wilkerson, M. H. (2022). Accessible DataLIT: Discovering the role teachers of the visually impaired play in data literacy development. Paper presented at the 2022 Annual Meeting of […]

  • Computer Science for Racial Justice (CS4RJ)

    The Computer Science for Racial Justice (CS4RJ) project aims to support just and sustainable engagements in CS learning alongside Black, Indigenous, People of Color (BIPOC) communities. It seeks to support historical reauthoring, a version of computational “remixing” that encourages students to engage with the ethical and political dimensions of computing.

    Funded by: Google CS-ER

  • Computing+ Reading Group

    A standing group of researchers working at the intersection of computing, data, and science education. We curate and synthesize relevant work across literatures and domains, and consider implications for K12 educators and researchers.

  • Humanistic Stance in K-12 Data Science Ed

    Lee, V., Wilkerson, M. H., & Lanouette, K. (2021). A call for a humanistic stance toward K-12 data science education. Educational Researcher, 50(9), 664-672. doi: 10.3102/0013189X211048810

  • DataBytes in Bite-Sized Lesson Plan Competition

    Our DataByte What is Healthy: Making Sense of Graphs and Data Reported in Media received an Honorable Mention in the Data Science 4 Everyone’s first annual Lesson Plan Competition! The What is Healthy? unit builds on our DataBytes discussion structure, which asks students to interpret graphs and data from media sources using not only in […]

  • DataSketch

    The DataSketch project explored how middle school students think and learn about data visualization. It involved two interrelated strands of work: (1) research on grade 5-8 students’ existing competencies and practices related to data visualization; and (2) the development and study of a tablet based toolkit for students to create digital ink programmable visualizations that respond to archival or live data stream input.

    Funded by: National Science Foundation IIS-1350282