When is it right to include computational thinking into a general education program in higher education? When we all fully understand it? No. When we can most afford it? No. When it does not cause academic turf warfare? Not really. It’s only when we are ready to graduate students who are better prepared to succeed through an understanding of and the facility with abstraction, information and processes, which have come to define and influence their personal and professional lives.
Conversations are happening over computational thinking (Jannette Wing 2006) on college and high school campuses. Some traction is developing, but there is still a chasm of ignorance between the computing community, which can get excited over problem solving through computational thinking, and colleagues in other disciplines who still view computing today as if it were 1990…you know, the if-only-my-students-knew-formulas-in-Excel faculty members.
Looking at the College of Charleston’s General Education program, reading, writing and math stand prominently, echoing the traditional educational triad well into the 21st century. While the three Rs remain foundational, I argue that computational thinking, represented by a fourth R, algorithms, is a new leg upon which liberally educated people must stand in this century. (Tony Hey, Microsoft Research 2009) Or is it simply asking too much of universities?
In the mean time, computer scientists, a group that already studies reading, writing, math, history, language, philosophy, and the arts, will continue to be singularly well educated. We have already emerged as a population (Richard Florida 2004) who are best positioned to succeed in a world in which we increasingly draw value and power from information and processes. And we are progressing at speeds that boggle human understanding and may soon exceed it.
In the short term, we have much to gain by keeping the traditionally educated population ignorant. When people get hungry for managing complexity, for understanding how to solve problems computationally, and for digitally implementing ideas that can transform scientific, social, political and economic spaces in time frames with shorter and shorter half-lives, let them run Excel. In the mean time, let’s relax. Let’s keep the computational key until someone is keen to notice.