I recently had a chance to sit out and observe students during their lunch break at a Sacramento-area high school. Over the span of 30 minutes, I jotted down notes on the number of students using smart phones, tablets, laptops and one student interacting with her Apple Watch. The students at this school truly represented Marc Prensky's idea of "digital natives" - students are proficient at using advanced technologies, but our educational systems are often outdated and limit the opportunities for students to think and process information in new, innovative and creative ways. It appears that the use of technology may be the ultimate opportunity to spark student curiosity.
In a number of the schools in the Sacramento region, with whom I work to grow their Information and Communication Technologies (ICT) course offerings, I have observed two camps of educators teaching and computer concepts in their classrooms: academic teachers teaching digital literacy skills and (far too often) Career and Technical Education (CTE) teachers teaching computer science (often in the form of programming). My observation mirrors the results of a recent report developed by the folks at Google and Gallup. The report concluded that school administrators underestimate parental demand for computer science courses at their schools and, instead of offering a computer science course, focus resources on core academic classes that directly impact school testing scores. For that reason, the challenge is to find ways to meet the digital natives in their core classes, and challenge them to use their computational tools for more than just digital literacy - to use the tools to solve problems and represent solutions - as they would in computer science classes!
Enter computational thinking: an approach that introduces students to computing ideas and principles in the context of the subject areas in the classes in which they are currently enrolled. As stated in an additional, forthcoming report from Google, computational thinking "involves breaking down complex problems into more familiar/manageable sub-problems (problem decomposition), using a sequence of steps (algorithms) to solve problems, reviewing how the solution transfers to similar problems (abstraction), and finally determining if a computer can help us more efficiently solve those problems (automation). Imagine a core academic classroom in which students are able to tackle complex problems that are of interest, create sequential solutions that can be replicated in other subject areas, and execute those solutions using technology that a student uses every day ... an amazing opportunity for students and teachers alike!
Through this collaborative sprint, I hope that a core academic teacher is inspired to infuse computational thinking into his curriculum. Of course, that teacher may be wondering where to start. Since this post is a bit theoretical, I want to give an additional shout out to our friends at Google for the Computational Thinking for Educators Course (https://computationalthinkingcourse.withgoogle.com) they have built (and will be launching tomorrow, October 15, 2015). This amazing course, which yields a certificate to teachers that complete all of the lessons and design one of their own, is an excellent professional development opportunity for in-service teachers.