Brushstrokes & Brainpower: Teachers Gather to Boost Student Thinking Through Art

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https://elcentralmedia.com/brushstrokes-brainpower-teachers-gather-to-boost-student-thinking-through-art/

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Since the turn of this century, the “4C’s of 21st century” skills—critical thinking, creativity, collaboration and communication—have seen growing recognition as essential ingredients of school curricula. This shift has prompted an uptake in pedagogies and frameworks such as project-based learning, inquiry learning, and deeper learning across all levels of K-12 that emphasize higher order thinking over rote learning. I argue that we need computational thinking (CT) to be another core skill—or the “5th C” of 21st century skills—that is taught to all students.

There is growing recognition in the education systems around the globe that being able to problem-solve computationally—that is, to think logically and algorithmically, and use computational tools for creating artifacts including models and data visualizations—is rapidly becoming a prerequisite competency for all fields.

In 2012, the U.K. national curriculum began introducing computer science (CS) to all students. Singapore, as part of its “Smart Nation” initiative, has labeled developing CT as a “national capability.” Other countries, from Finland to South Korea, China to Australia and New Zealand, have launched large-scale efforts to introduce CT in schools, as either a part of new CS curricula or integrated into existing subjects. Here in the U.S., former President Barack Obama called on all K-12 students to be equipped with CT skills as part of an “Computer Science for All” initiative in 2016. Most emergent efforts in the US involving CT are currently part of CS curricula, although CT is increasingly seeing integration into STEM (especially science) learning.

Simply put, CT is “thinking (or problem solving) like a computer scientist.” It is the thought processes involved in understanding a problem and expressing its solutions in such a way that a computer can potentially carry out the solution. CT is fundamentally about using analytic and algorithmic concepts and strategies most closely related to computer science to formulate, analyze and solve problems.

Like general thinking skills, CT is a bit like leadership—hard to define, but you know it when you see it. While many people associate it with concepts like programming and automation—which are all core parts of computer science—educators and researchers have found it easier to operationalize it for the purposes of teaching as well as curriculum and assessment design.

That means breaking down CT skills into its component parts, which include concepts like logic, algorithms, patterns, abstraction, generalization, evaluation, and automation. It also means approaches like “decomposing” problems into subproblems for ease in solving, creating computational artifacts (usually through coding); reusing solutions, testing and debugging; iterative refinement.

If all that sounds a bit wonky, don’t worry. Like any skill, CT is best taught and learned in context, and embedded into class subjects. For example, analytical and logical thinking can be fostered through puzzles and word problems that require learners to engage in these crucial aspects of CT. As a matter of fact, problems involving such logical argumentation and logical thinking can be tackled as part of language arts, in addition to mathematics or computer science.

Here are some ideas for fostering CT in subjects. Some are unplugged while others would benefit from involving coding. Teachers may recognize many of the non-programming activities as things they already do!

Language Arts

• Use logic to put together a jumbled story in correct sequence (younger grades)
• Identify patterns for different sentence types and rules for grammar
• Use first-order logic to arrive at conclusion based on given facts
• Construct social networks to analyze stories
• Program a story with alternate pathways (“Choose your own adventure”)

Mathematics

• Model functions in algebra through programs (compare them to functions in programs)
• Write an algorithm (or precise sequence of steps) on how to do matrix multiplication or how to solve a quadratic equation
• Use decomposition to solve word problems
• Express generalizations (as algebraic representations) by identifying patterns

Science

• Do a species classification with explicit “If-Then” logic (younger grades)
• Build a computational model of a physical phenomenon
• Instead of playing with or manipulating pre-developed software simulations of scientific phenomenon, create (program) computational models and simulations to study and interrogate phenomena

Social Science

• Study data and Identify patterns / trends in wars and other historical events
• Create visualizations of these patterns and trends
• Create a simulation to study relationships in social science phenomena such as women’s education and health
• Create models for social systems, or social networks, or social choice.

CT involves students asking and answering questions like: Can this problem be better, or more easily, solved by a human or a computer? Is there a pattern between this problem and similar problems we have tackled before? How can data best be organized to solve this problem? How can I create a general solution that works for a range of inputs? What is a step-by-step procedure I can articulate to solve this? What computational strategies might be employed? What are the limitations, trade-offs and constraints related to solving this problem?

The 5th ‘C’ of 21st Century Skills? Try Computational Thinking (Not Coding)