Why is Computational Thinking so important? In order to be productive we need methods for problem-solving that allow for both creativity and efficiency.
Computational Thinking provides for both. Whether a student’s career path involves biology, transportation, or sales doesn’t matter--
careers in these and many other fields often involve solving big problems, dealing with big data sets and creating solutions.
A skill set in problem solving using Computational Thinking opens doors for anyone in any area.
Computational Thinking is important because it: provides a framework to develop critically thinking problem solvers across different fields
--many STEM (Science, Technology, Engineering and Math) problems are solved by the methods of Computational Thinking.
Computational Thinking requires you to develop a way to DO, not just think.
incorporates both creativity and efficiency into problem solving
allows students to interact with content-specific models and simulations to support learning and research.
leads to IT fluency as opposed to IT Literacy—moving students beyond being a user of tools and information to becoming a creator of tools and information a 21st Century Skills.
develops job skills, which lead to income
Helps non-computer science people learn how to take advantage of the power and understand limitations of computers
Applies to all subject areas—and allows them to advance
and doesn’t require changing curriculum or new technologies
Throughout this course, we will break down the skills involved in Computational Thinking
to help you better understand the parts of the whole as well as how each component is executed.
These are just introduced briefly here as there is an entire video devoted to each.
The four main areas on which this training will focus include:
Decomposition--When analyzing a problem, logically breaking it down into smaller, more manageable subproblems.
Pattern Recognition--When analyzing a problem, recognizing patterns and/or trends within problems or among subproblems.
Abstraction/Pattern Generalization--generalizing variables and determining their relationships,
which may allow for modeling and automation.
Algorithm Design--Carefully defining logical instructions to carry out solving part or all of the problem.
These steps may seem abstract at present, but throughout the course several example problems
from outstanding existing resources will be shared that will help solidify how each part of the process works
and how all the parts come together to solve different kinds of problems.
Throughout this professional development, resources to help you further understand the skills involved in Computational Thinking
and implementation of Computational Thinking in your classroom will be recommended, linked, referenced and tied in.
As mentioned earlier in relation to problem solving in general, the steps involved in Computational Thinking
do not always occur in a nice, neat sequence. In reality, a problem may be decomposed, patterns identified,
abstracted and an algorithm tested and failed. At that point it is back to the drawing board in rethinking parts of the problem.
In general, decomposition, pattern recognition and abstraction can be thought of as steps in setting up the problem (or modeling)
while algorithm design can be thought about as the operation to solve the problem.
However, sometimes the modeling and operation steps are revisited
and repeated multiple times in order to refine and find a workable solution.
Problem solving through Computational Thinking is such a critically important skill
it is directly or indirectly addressed by several sets of educational standards including:
Computer Science Teachers Association K-12 Computer Science Standards
Next Generation Science Standards and Common Core English/Language Arts and Mathematics
We hope that this Online Professional Development Course will provide you as a teacher an understanding of what
Computational Thinking is and why it is important, as well as concrete methods
for tying this powerful problem-solving tool into your classroom to help your
students excel at critical thinking and problem solving.
When you have finished watching this video, don’t forget to complete the quick
self evaluation to check your understanding.