Last Tuesday I had the pleasure of speaking with Anthony Salcito, Vice President of Worldwide Education at Microsoft. We discussed computational thinking and our vision here at Excel, as well as my path from former Microsoft employee to my role as Computational Thinking Program Manager at a public charter school. Read highlights from our conversation and watch the video interview over at DailyEdventures here: http://dailyedventures.com/index.php/2015/10/27/eli-sheldon/
This post dives into some of the technical nitty-gritty powering our lesson on analyzing a basketball play using decomposition and motion graphs. If you haven’t had a chance to check out that post, definitely start there. As stated in that post, 95% of the credit belongs to Savvas Tjortjoglou and his incredibly helpful blog post describing how to access and manipulate NBA movement data.
Our students have spent the last couple of weeks mastering one of their favorite topics – basketball. I can safely say that despite their height disadvantage and general unfamiliarity with their rapidly growing limbs, most of them could probably school me in a game of one-on-one. I needed a way to bring the ball back into my court.
Fortunately, students have also been working on basic graphing in their math and science classes, and I’ve been itching for a lesson with which to introduce the computational thinking concept of decomposition. Throwing all of these ingredients in a cauldron and giving it a good stir, the following lesson began to emerge.
Take a look at this spectacular play by the Cleveland Cavaliers during Game 3 of the 2015 NBA Finals, highlighted here as the fourth best dunk of the series. There’s a lot going on! LeBron James snags a rebound and takes off across the court, slinging it to Matthew Dellavedova and crumpling the defensive attempt from Klay Thompson and Stephen Curry. It’s a four-way race down the court – but was this play really a contest of speed? Who ran the fastest? How fast was he running? And how can we possibly find out?