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Computational thinking gives students much-needed skills to carry into the real world, and educators can use research-backed tools to teach it

What should educators teach? Computational thinking

Computational thinking gives students much-needed skills to carry into the real world

The way we approach problems in the workplace has changed drastically because of technology.  Therefore, it is imperative that we set students up for future success by teaching relevant skills and modernizing the curriculum. 

As we work to realign K-12 education to better meet the needs of today’s Information Age society, I implore my fellow educators to embrace teaching research-backed skills like computational thinking across curriculum. By doing so, we will benefit our students and our world.

Why computational thinking?

Today’s employers are seeking problem solvers. Computational thinking is an appropriate way to teach students quantitative and qualitative thinking. Computational thinking practices equip students with problem-solving skills, such as analyzing data, in order to make inferences and break problems down into manageable pieces. This transdisciplinary mode of instruction ensures learners can pair critical thinking with creativity to think through challenges and identify potential solutions.

There are many no-cost resources available to help educators implement computational thinking in the classroom. I recommend checking out the professional development opportunities and classroom resources available through Ignite My Future In School, a program from Tata Consultancy Services (TCS) and Discovery Education. Specifically, the Master Class Series offers educators peer-based best practices for implementing computational thinking in any learning environment.

Computational thinking includes the following core strategies:

  • Collect Data: Determine sources from which you will collect data and decide which qualitative and quantitative data to collect.
  • Analyze Data: Produce and evaluate charts and use appropriate statistical methods to test a hypothesis.
  • Find Patterns: Identify patterns to make predictions, create rules and solve other problems.
  • Decompose Problems: Take large, complicated problems, and break them down into manageable pieces.
  • Abstract: Identify similarities and remove details to create a solution that works for many different problems.
  • Build Models: Test, tweak, and refine an object before building it in real life using design software to predict outcomes.
  • Develop Algorithms: Create solutions using step-by-step instructions that operate like a road map for performing a task.

A new kind of problem solving

The way we teach STEM is evolving. Where in the past STEM instruction often focused on rote memorization, we’re making a shift to ensure that what students learn in class is similar to what they’ll experience in the real world. 

Whether students pursue a career in related fields or not, including STEM across subjects ensures they’ll be able to navigate our digital world with ease, and use the tools available to them to work through challenges. 

Leave the calculating to computers

We live in a time where quick calculations can be made with our phone, computer, or other device–so assessing students’ ability to memorize and perform calculations by hand just isn’t as relevant as it used to be. 

Instead, we should be teaching students how to leverage technology to solve complex problems, using computational thinking practices as a foundation. 

No time to waste

The COVID-19 pandemic has worsened the skills gap in our labor market. Technology is evolving rapidly but keeping up has been a historical challenge for education institutions. Embracing modern practices in the classroom, like computational thinking, is necessary to ensure that students are prepared to excel in the future careers.

Teachers are tasked with the crucial job of encouraging, supporting and shaping our students. It is our duty to advocate for changes that will better their academic experience, and education as a whole. 

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