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K-12 Initiative

computational thinking tasks  |  videos to prepare teachers

 

The power of understanding computational thinking lies in its insight into how the builders of computing tools approach making them.

Understanding how computing tools are made helps students know how to use them effectively and responsibly.


What is computational thinking (CT)? Computational thinking is the thought processes involved in formulating problems so that the solutions can effectively be carried out by a computer.*

The concepts of CT we teach to K-8 students:

Algorithms: designing step-by-step processes
Algorithms: designing step-by-step processes
Abstraction: deciding what matters and what doesn’t
Abstraction: deciding what matters and what doesn’t

 

 

 

 

 

 

 

 

Decomposition: breaking problems into parts
Decomposition: breaking problems into parts
Pattern Recognition: identifying trends in data
Pattern Recognition: identifying trends in data

Why does CT matter in the age of AI? AI is built from the same foundational ideas we teach in computational thinking. Machine learning is essentially pattern recognition at scale. Neural networks are layered algorithms. Training data is structured abstraction. Without CT, AI feels magical. With CT, AI becomes understandable — and can therefore be critiqued. Generative AI is too biased and unreliable to be accepted without informed scrutiny.

AI can generate code, draft text, and predict outcomes. But humans must frame the problems, decide constraints, evaluate outputs, debug errors, and align solutions with values. Those are CT moves. In the AI era, the advantage shifts from “Can you code?” to “Can you think computationally about complex systems?”

CT is developmentally appropriate before AI, especially in K-5. Cornell Tech’s CT (unplugged) tasks build the foundational understanding of computing needed to understand AI – and whatever comes next.

  • Unplugged CT builds logic and reasoning.
  • Pattern recognition develops mathematical thinking.
  • Abstraction strengthens literacy comprehension.
  • Algorithmic thinking improves writing structure.

 

Cornell Tech has been teaching CT in classrooms since 2019 as part of the Robin Hood Foundation’s Learning + Tech Fund. We introduce a series of rich, productive, collaborative unplugged tasks that encourage students to think creatively using CT – the basic concepts of computing. All this work is free and open source.

We created a series of short professional learning videos that explain CT and how it can be integrated into English language arts. Access them here. These should give any teacher, administrator, or parent a good understanding of CT, and how to use our tasks with students.

We are currently in the process of collecting the tasks of the past seven years to make them all available (watch this site for updates!). For now, you can find some of the ELA and math tasks in this public Google folder. The READ ME FIRST document in this folder credits the many authors and editors of our tasks, and will be kept updated as formatted tasks get added to the folder.

 

* From Jeannette Wing, Communications of the ACM March 2006/Vol. 49, No. 3