I’ve recently become old enough to qualify for senior discounts in many countries, but I’m relatively (10-12 years) young in my profession as a teacher librarian. Believe me when I say bringing a beginner’s mind to a new area of endeavour is not a bad thing.
I’ve been a long time fan of Mike Caulfield and his SIFT model and an equally long antagonist of the short-handed way we tend to look at source credibility through tools like CRAAP – something that should have died around the birth of smart-phones. I also thought we vastly under-estimate our students when we use CRAAP instead of SIFT in teaching information literacy.
And why do I like Mike Caulfield? Because he evolves. I think a version of James Dean’s “Live fast and die young and leave a good looking corpse” is important in education – to the extent of “try new stuff, listen a lot and let 13 year olds tramp over the corpses of what doesn’t work”
Kids are really good at short cuts, short attention spans and disdain for anything older than themselves. Any teacher / librarian who has spent 5 minutes teaching research has probably spent 100% of that time trying to teach key words and unteach students typing what they want to find in a search bar. I just have to laugh at this post that I wrote nearly 10 years ago!
Well, hallelujah – the kids were right all along. In this brave new AI world we find ourselves in, a typical teenager is probably more likely to hit on the right AI generated search result than the typical adult – including librarians with all their years of training. Unless of course they’re in the dreaded database environment (I’ve ranted enough about those in the past and will continue to do so in the future).
Key words are out and context is in. Relevance is built into a natural language search and the real work starts with getting the machine to refine results through prompts including “academic” or “reputable medical” or “journal article” etc, telling it to make comparative tables and do the first reading for you.
The way traditional search works is it knows your keywords but has a difficult time guess your search intent or need…
Mike Caulfield – Look before you Leap
AI Allows You to Refine Source Relevance Before You Make the Jump, and That Changes Everything
So now I’m giving you something to read, hop out of this blog and have a look at Mike Caulfield’s two latest posts in substack. “Look before you leap: How AI changes source verification and how SIFT will respond” and “A SIFT Rebuild (in progress)“
But bigger than all that is the question of why we persisted so long in thinking of young people’s academic search as being “wrong” and forcing them into the “key word” funnel instead of shouting louder that the way that databases are set up are wrong – and keeping on paying huge amounts for the privilege of being screwed?
Yes I know the answer – kind of – is content that has not been AI generated. But the “publish or perish” academic environment coupled with the reluctance to go back and redo / prove or disprove research should give anyone pause. And if you want some very intelligent, largely irreverent background on this, please go to the “Everything Hertz” podcast .
Things that are going to have to change – Britannica, Google Scholar, Gale, Infobase, JStor, Proquest – just to mention the ones in the G6-12 environment. Take your sales and development people out of their offices and put them in some schools, libraries and classrooms and take note. Of the frustrations, of the tiny 12 point font you’re using, of the clumsy design, user experience and interfaces. And stop increasing your prices until you’ve done so and done something about it.
Informative Flights - Musings of a Teacher Librarian 