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The Value of Computational Thinking across Grade Levels 9-12 (VCTAL)

VCTAL is developing a set of instructional modules, mini-modules, and (ultimately) a book for use in high school classrooms. The modules will cultivate a facility with computational thinking in students across different grade levels and subject areas.

What is computational thinking?

Computational thinking is a high level thought process that considers the world in computational terms. It begins with learning to see opportunities to compute something and relates to mathematical thinking in its use of abstraction, decomposition, measurement and modeling, but is more directly cognizant of the need to compute and the potential benefits of doing so. Read more about computational thinking.

VCTAL Project Activities:
  • Developing, testing, and implementing an innovative mix of short (roughly one week) instructional modules for grades 9-12, with student and teacher versions and short “teasers” or mini-modules associated with each module.

  • Hosting Student Prototyping Workshops during the summer to assist authors in writing the modules, teachers in teaching them, and everyone in understanding the connection between the materials and students.

  • Evaluating the influence of VCTAL materials on diverse students’ awareness of computational thinking opportunities and interest in related technical fields.

  • Contributing these modules, mini-modules, book, and related resources to repositories for effective materials and practices in computational thinking and broadening participation in technical fields.

VCTAL Project Goals:

Broadening participation in computer science and other computational disciplines by:

  • Producing materials that teachers can use to engage students and stimulate awareness of opportunities to think computationally.

  • Making computational thinking relevant to students by offering examples that show its use woven throughout daily life.

  • Widely disseminating VCTAL modules.

Download  VCTAL flyer
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This material is based in part upon work supported by the National Science Foundation under Grant Number DRL 1020201. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.