Bridging the digital divide with computational thinking

By Terry Toy

Google, Apple and Facebook recently published diversity data about its workforce, and the results are clear: Technology has a diversity problem!

At Google, for example, only 17 percent, 2 percent and 1 percent of its technology employees, respectively, are women, Hispanic and black. These statistics reveal a sobering fact. Groups that have historically struggled to gain equality in the workforce are not being represented in the jobs of the future.
The roots of this problem are complex, but begin in our educational system. On one hand, we have an equality and access issue. The Computer Science Teachers Association estimates that only 10 percent of high schools offer any form of computer science. Of those that do, most are in affluent areas. So students in socioeconomically poor communities have no access to these new skills.

On the other hand, we have a cultural problem. Girls avoid computer science. In 2013, 58 percent of students taking the Advanced Placement biology exam were girls, 48 percent of students taking the AP calculus (AB) were girls, but, for computer science, the drop-off was stark — only 18 percent of the students taking the AP computer science exam were girls. We need to find ways to keep high school girls engaged with computer science.
There are many obstacles to teaching computer science in our high schools. Finding qualified teachers is difficult given 1) high demand for computer science graduates; 2) lack of a computer science teaching credential program; and 3) the fact that high school computer science teacher jobs are usually only part-time.

In addition, most high schools are not prepared for the complexity and nuances of teaching computer science. Schools must invest in professional development, curriculum and hardware. Then, CS curriculums become obsolete in a few years.

Changing cultural attitudes about computer science may be even a greater challenge. Until we view computational thinking as a core discipline, part of a rounded education, rather than a niche field, we will not make the changes needed to modernize our educational system.

Consider the accelerating impact of technology on our economy:

* Software, still in its infancy, represents three out of four of the most valued companies in the world. We use these products and services every day.

* Technology companies are lobbying to increase the number of H-1B visas for foreign technology workers allowed in the United States. Advocates for more foreign workers contend that the U.S. workforce lacks the skills needed for today’s technology jobs, despite a prolonged period of high U.S. unemployment.

* Digital data is doubling in size every two years. Today, businesses, research centers and organizations, both big and small, in all industries need people who can analyze and process digital data. The only way to process digital data is with computational methods.

* Learning to code is a valued skill that can lead to well-paying jobs. Contrarily, a college degree no longer guarantees a middle-class job, and is leading to unprecedented student debt.

Technology is transforming our economy. This is not to suggest that everyone needs to be a programmer, but rather, learning basic computational thinking skills makes one a better economist, scientist, artist or whatever one’s final career choice.
“For computational skill to become a true literacy, integrating it with the teaching of other disciplines would probably be ideal,” says professor Bruce Sherin of Northwestern University.
One method of expanding computational thinking in high school is integrating it with math. Since all schools have a math department, integrating computational thinking into math classes, while still challenging, is far easier than starting a computer science curriculum from scratch.

Similarly, math and computer science are closely related fields and even share a common vocabulary: variables, abstraction, functions. By integrating these two subjects, students learn new computational methods to solve familiar math problems.

Another goal is to teach computational thinking in a familiar context. One example is web pages. By teaching JavaScript (the language of the web) instead of traditional command prompt languages (usually taught in introductory college courses), we make computational thinking more relevant.

Creating interactive web pages that solve familiar math problems has an element of creativity, which might attract students, who otherwise would avoid a traditional computer science course. (See samples of interactive web pages that solve math problems at http://mathcode.net/video.html.)

If technology companies are a harbinger of the future workforce, we need to ensure that everyone has equal access to the skills that will drive the digital economy. The only way to do this is to make computational thinking an appealing and integral component of K-12 education.

— Terry Toy of Davis is the founder of MathCode, whose goal is to help schools start code clubs and computational math courses. MathCode is supported by Davis Roots, a local business accelerator. Reach Toy and interact with actual student projects at http://mathcode.net

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