I'm continuing to develop curriculum for a tiny elite college prep school smack in the center of the Silicon Forest, a place called Bethany Village, which specializes in offering after school elective time activities (e.g. martial arts, foreign language learning). [0] Nearby: Intel, Tektronix, ESI... [1]
The Sunshine Elite School runs both after school enrichment and for-credit day school programs. I call myself "a developer" or even a "dev", but if people ask what I develop, I say "curriculum". I teach four times a week and look for ways to include student work in ways they permit. The school already has a Hall of Fame for competitive tournament winners. Doing a stellar project around Wordle or Chess would be another way to develop one's portfolio, through lasting links in the text itself. I wonder what other educators here think of the following proposition: === Most of the wood pulp published Algorithms and Data Structures (ADS) textbooks inherit from a day before "array based computing" and therefore have no "DataFrame" to integrate. Not as such. Of course they have 2D arrays (Python: lists of lists), i.e. row and column data, but not anything as sophisticated as a DataFrame in R or pandas. So let's include the DataFrame in a next iteration of ADS! That's certainly what I'm doing.[2] That puts machine learning algorithms within the reach of a pre-college student. We needn't dive deep into deep learning. We're free to dabble. We're still young and carefree (student attitude). "Buckle down data science" comes later, for those who so choose. === I see Jupyter Notebooks (Colab, Kaggle Notebooks etc.) as an extension of the desktop publishing revolution of the 1980s (PageMaker + Apple LaserWritier == professional quality publications). I remember working with nonprofits and NGOs and those days (at a place called CUE), and how excited these organizations were to be able to upgrade the look and feel of their literature. The web itself held a similar promise: the little guys wouldn't be trounced by the big guys, just because the big guys were big. Jupyter Notebooks, with embedded videos and data visualizations etc., put more of a level playing field under all would-be publishers. Our content is potentially as high quality as the content in professional papers and magazines. As long as we study our Tufte... Look how Jake VanderPlas goes back and forth between Notebooks and a wood pulp (non-interactive, yet standard setting) O'Reilly book. [3] As a curriculum dev, I'm able to bypass the wood pulp publishers entirely, using open source tools to create open source assets available to fellow faculty. To me, this looks like a quiet revolution against the hegemony of "those with enough money to dress up" (i.e. make their stuff look pro). Kirby Cc: Wwwanders (Silicon Forest, Doug Strain affiliate) Citations: [0] https://flic.kr/s/aHBqjzJdXN [1] https://www.oregonencyclopedia.org/articles/silicon_forest/ (mentions Doug Strain) [2] https://nbviewer.org/github/4dsolutions/elite_school/blob/master/ADS_sandbox_2.ipynb [3] https://github.com/jakevdp/PythonDataScienceHandbook
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