How Big Data Is Taking Teachers Out of the Lecturing Business

The widespread availability of mass produced books should have taken teachers out of the lecturing business. I'm not sure if it's true that lecturing started because books were so expensive that one person read out the one chained to the lectern and everyone made their own copies, but it feels about right. It certainly makes much more sense than the modern spectacle of someone reading bad powerpoint slides badly. But books didn't supplant lecturers, nor did radio, television, VHS video tapes, computer aided-learning, nor the internet.

Yet they should have. Ask anyone who actually wants to learn stuff and you'll find they, naturally, use all these tools and reserve the precious time they spend with an actual expert to mentoring, hands-on skills, subjective evaluation, asking clarifying questions etc. Imagine how stupid you'd feel to hire a world class expert in something and get them to read you a summary of a chapter of their book.

But in Higher Education, having someone, who doesn't really want to teach, has no real aptitude for it and who probably isn't hired, paid or promoted on the basis of how good they are at it, stand in front of a large room of students is basically their equivalent of Homeopathy. A logically preposterous notion, contradicted by all available evidence of efficacy, that mind-bogglingly survives into the 21st century.

No matter how bad this stuff is, and any bit of software being sold to higher education is basically terrible for much the same reasons that nearly all enterprise software sucks, it can't really be any worse than the status quo.

We have this same type of thing for a select few number of courses on our campus. Don't let the PR spin get you, these courses are adopted to save money for the college, anything else is a fortunate side-effect.

They seem, in theory, to work quite well. In reality, though, the 'adaptive learning' algorithms are simply "answer x correctly, go to y; answer x incorrectly, go to w" sort of things. They have fancy charts and graphics showing 'knowledge clusters' and 'though pattern analyses', but really, it boils down to my original statement. I've tested, re-tested and counter-tested these programs using various skill levels and completely random answers.

X is right, proceed to y. X is wrong, proceed to w.

From the 2-3000 students I've seen run through these courses in the last four years, there are three types of interaction with this model: those that love it and do well (but would also love and do well in a structured classroom), those that hate it and do poorly (but would also hate and do poorly in a structured classroom), and those that have absolutely no idea why they're being forced to work with a computer that doesn't allow you to answer questions.

I may be a bit old fashioned in my pedagogy and educational theory (yet I'm only in my 20's), but there really do seem to be students that simply respond better to being able to ask questions and receive answers from a living-breathing human being.

Really, the only benefit outside of cost savings to employees and administration of universities and colleges is that these programs allow us to find the exact point at which a particular student's understanding begins to break down. That's new, and fascinating (and brings up whole new concerns on privacy in my opinion).

I'm not employed as a teacher, but one thing that I learned in a traditional classroom setting was how to teach. I observed fifty teaching styles, and the subtleties of adapting to those being taught. I use those skills every day. If anything, an economy that expects more of us to become entrepreneurs, teaching skill will become more valuable, not less.

I'm betting my career on some things never going obsolete, such as the laws of physics and being able to explain a concept to a non expert or skeptic.

For one semester, I taught the "terminal" freshman math course. The syllabus that I was required to follow was obsolete by thirty years. The switch to online course should really be accompanied by a vigorous debate over the content that is being taught.

I thought "big data" meant huge volumes that can't fit in a traditional db (despite that those can scale to several terabytes), or sometimes data collected from multiple unrelated detailed sources (such as correlating local weather, the stock market, and recent cricket scores with how much time your employees spend on HN). This doesn't sound like either.

Previous post discussion - http://news.ycombinator.com/item?id=6120548