The rise of AI doesn’t mean we should forget about memorisation

I het what you are saying, and I am less hostile to memorisation than I used to be, but I still think to emphasis in university is on thinking, not remembering. I'm a moderately successful molecular geneticist, but I still don't remember which base is a purine, and which a pryrimidine, nor which amino acid belongs to which category. That said, 8 do have a lot of knowledge at my fingertips. But this is not because I learnt it at university, but that the things I have repeated used in 20 years of professional practice have imprinted themselves. It's a set of facts that is almost entirely mutually exclusive from those my university teachers thought were important. Perhaps it is the fast moving nature of my field, but any fact we teach our students now will be irrelevant in 5 years time. Better to equip them to be able to move rapidly with the times than to excel at practices and with knowledge that will be deprecated almost before they've even graduated.

Thank you very much for your comment, Ian. I fully agree that (critical) thinking prevails over remembering. one of the points I wanted to emphasize in the paper is that the imbalance between both has become (too) huge and should be reconsidered, because thinking requires learning and memorizing first. I know this is obvious, but it really feels like it has been somewhat put aside. Mastering and memorizing the bases (and even a bit more) is essential to keep building on them and developing new knowledge and skills. I am not a molecular geneticist, but I would guess that you would struggle to master the new practices and knowledge without being able to build on the old ones (even though I also guess that some of the old ones may sometimes hinder the development of new ones). Once again, the point was really about re-establishing some balance ;)