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From work to school to home, digital technology is everywhere. Given its growing influence, students must be equipped with computational thinking skills to genuinely connect and contribute to our digital world.

Public school students’ computer use must move beyond consuming information and performing routine tasks like reading, writing and presenting. They need opportunities to create, decode, analyze, customize and otherwise manipulate programs, datasets and predictive models to solve problems in support of their learning goals.

There is a growing need to reframe computing in classrooms as an inherently social and learned set of skills. The end goal is not to just provide access to digital devices — it’s to develop the skills to use these tools for heightened learning, critical thinking and self-expression.

We suggest that computational thinking — which applies concepts from computer science — provides a framework for pre-K-12 educators to integrate and apply computational methods to solve interdisciplinary, complex and/or everyday problems.

These methods include an interrelated set of skills, such as pattern recognition, abstraction and decomposition, applied to solve complex problems using, for example, automation, data analysis or computational modeling. These skills and practices can be used to learn topics in many disciplines.

It’s time for all educators to integrate computational thinking into disciplinary learning across K-12 education, and equip students with the skills they need to participate in our increasingly technological world — and to promote justice for students and society at large.

In the early grades (pre-K-3), students should engage in foundational computational skill building, such as pattern recognition. In the middle grades (4-8), they should connect and apply computational skills to solve problems, such as using models to make predictions. In the older grades (9-12), students should leverage computing to address problems of higher rigor and complexity, such as analyzing data to critically examine bias in society.

Yet, as we expand computing opportunities in schools and encourage students to be creators and critical users of digital media rather than simply end consumers, we must recognize that our evolving world of technological innovation is still (deliberately or inadvertently) reinforcing systemic injustice.

These injustices are caused by biases within our technical systems and are perpetuated by the digital learning and inclusion gap. This gap contributes to the lack of diversity in many parts of the workforce, especially in the science, technology, engineering and mathematics fields.

While jobs increasingly require the processing power of computers along with human creativity and expertise, our education system is preparing only some students with these skills, while systematically excluding others. Marginalized students — Black, Native American and Latino students; students with disabilities; girls and nonbinary students — have unequal access to the classrooms, equipment and learning opportunities needed to build computational skills.

Related: Digital divide: Gap is narrowing, but how will schools maintain progress?

All students need opportunities to consider the ways that technological systems and the biases designed into them affect their lives. For example, students could discuss the implications of gender bias in a natural language processing system, such as Gmail Smart Compose, or of higher error rates for marginalized groups in the facial and speech recognition programs in home assistants and smart speakers.

These opportunities to develop skills and design technology to solve problems are important for all students — not just the ones who will eventually study computer science and enter the information technology industry.

To make computational thinking learning opportunities more inclusive in K–12 systems and districts, schools, teachers and other stakeholders must integrate computational thinking into English Language Arts, social studies, math, science and the arts. Educators in New York City, for example, have integrated computational modeling into middle school science and are using computational skills in technical writing. City University of New York has developed robust professional learning experiences for educators, such as integrating computational thinking into the coursework and field experience of teacher education programs.

Integrating computational thinking into every classroom is not something that can be left to individual educators. Education leaders must also find ways to help teachers address challenges to inclusivity and equity. This is a big change and must be prioritized by district leaders.

It’s time for all educators to integrate computational thinking into disciplinary learning across K-12 education and equip students with the skills they need to participate in our increasingly technological world — and to promote justice for students and society at large.

Jean-Claude Brizard is president and CEO of Digital Promise; Kelly Mills is project director of computational thinking.

This story about computational thinking was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for Hechinger’s newsletter.

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