J. Malyn-Smith

Computational thinking (CT) or “thinking like a computer scientist” is defined as formulating problems and their solutions in a way that a machine (computer) can be used to represent the problem and carry out a solution. Increasingly CT is considered to be a foundational STEM skill needed for success in our world driven by technology and essential for success in future work at the human-technology frontier. Educational policy makers responsible for preparing students for future success are including CT in “compulsory” education in countries around the world. At the same time education practitioners are challenged to find ways to integrate CT into their curricula.

Though computer science educators may believe CT is best taught through programming, how can teaches of science, mathematics and the humanities integrate CT in the service of their disciplines, and what are its advantages? Funded by the U.S. National Science Foundation, Education Development Center convened two workshops to develop a framework for computational thinking from a disciplinary perspective. Workshop participants included 54 of the foremost U.S. researchers and practitioners focused on computational thinking education. The goals of the workshop were to draft a framework for defining computational thinking from a disciplinary perspective and to develop assessment recommendations or new research questions to close the gap between when CT assessments are already developed or in progress, and assessments needed to measure CT from a disciplinary perspective.

Participants provided examples of their work in the form of curriculum and activities that illustrated CT in action in their classrooms. Researchers shared their lessons learned through research on various aspects of CT skill development and integration. Ten common elements emerged from a review of these examples. CT practices in scientific work environments at the Human-Technology frontier were used to refine these elements so that they better defined what students could do more effectively/efficiently with CT that without. Five elements with corresponding examples in grade spans K-2, 3-5, 6-8 and 9-12. These five elements form an initial framework for CT within disciplines. They connect what students do using CT within disciplines and what CT enabled scientists/engineers do in practice in scientific workplaces.

This research concluded that through the use of computational thinking, both students and practicing scientists better:
1. Understand (complex) systems
2. Innovate with computational representations
3. Design solutions that leverage computational power/resources
4. Engage in collective sense making around data, and
5. Understand potential consequences of actions.

This presentation will share these elements and examples of what CT looks like in practice from a disciplinary perspective.