Data Computation Fundamentals by Daniel Kaplan and Libby Shoop.
From the first lesson:
Teaching the Grammar of Data
Twenty years ago, science students could get by with a working knowledge of a spreadsheet program. Those days are long gone, says Danny Kaplan, DeWitt Wallace Professor of Mathematics and Computer Science. “Excel isn’t going to cut it,” he says. “In today’s world, students can’t escape big data. Though it won’t be easy to teach it, it will only get harder as they move into their professional training.”
To that end, Kaplan and computer science professor Libby Shoop have developed a one-credit class called Data Computation Fundamentals, which is being offered beginning this semester. Though Kaplan doesn’t pretend the course can address all the complexities of specific software packages, he does hope it will provide a framework that students can apply when they come across databases or data-reliant programs in biology, chemistry, and physics. “We believe we can give students that grammar of data that they need to use these modern capabilities,” he says.
Not quite “have developed.” Should say, “are developing, in conjunction with a group of about 20 students.”
Data literacy impacts the acceptance and use of data and tools for using data.
Teaching people to read and write is not a threat to commercial authors.
By the same token, teaching people to use data is not a threat to competent data analysts.
Help the authors and yourself by reviewing the course and offering comments for its improvement.
I first saw this at: A Course in Data and Computing Fundamentals.