They do need, however, to understand the transformations that algorithms attempt to bring about.It then moves into one case study; the Jockers-Swafford debate of 2015, large parts of which hung on whether the Fourier transform was a black box and how it its use as a smoothing device might be understood. It's like a lot of what's on this blog, only better thought and edited.
The transformation/algorithm distinction is not a completely firm one, but I have found it extremely useful in a lot of research and teaching problems I've approached over the last year. So in addition to advertising that article for your consumption/fall syllabi production, I wanted to take the occasion to put on github a tiny little germ of a project to provide one-page, transformation-oriented introductions to basic text-analysis concepts that came out of using this thinking for a workshop on text analysis at the NIH in Bethesda, and describe what's in it. I'd love for anyone else to use it, fork it, whatever.