Why do educators and computer scientists differ in their acceptance of computational thinking?
I have been researching computational thinking (CT) professional development for K-5 educators for just over a year now, which is nearly as long as I have been a graduate student in educational technology. Anecdotally, educators seem far more excited about CT than my peers in Computer Science Education (CSE). At a recent conference for CSE graduate students, the joke was that if you put twenty computer scientists in a Zoom room together, you’ll have twenty different definitions of CT to debate. This frustration is not surprising: computer scientists have spent the last decade struggling to define CT, and that uncertainty seems to have led to skepticism in the field about its legitimacy. Educators, on the other hand, appear less concerned about an exact full definition of CT, but are more focused on identifying specific parts of it that can be useful in the classroom. It’s a classic theory vs. practice dichotomy.
But is there more to the discrepancy? My 7th grade daughter has been studying Mendelian genetics, which reminded me that genes could be expressed differently depending on environmental factors. Could it be that computational thinking—even it if is defined in a single coherent way—might end up being understood or used in different ways, depending on outside factors like context, prior experience, and personality traits?
To answer this question, I developed a preliminary survey, which was a frustrating but rewarding experience in leaving questions on the cutting room floor. To keep the survey short and quantifiable, I only asked multiple choice questions; for the purposes of improving the survey, I included short answer “Other” options. Eventually, a better survey and a better understanding of the outside influences on CT might help clarify what is inherent to CT.