todoELE

The pace of progress in learning sciences, learning analytics, educational data mining, and AI in education is advancing. We are launching this new publication, Learning Letters, to accelerate the pace at which science in learning moves from the lab to dissemination. The traditional publication process often takes 12 to18 months to move from article submission through to publication. We are interested in developing a new approach to publishing research in the “educational technology, learning analytics, and AI in learning” space. In particular, we want to reduce time to publication and put a sharper focus on results and outputs of studies. Learning Letters features innovative discoveries and advanced conceptual papers at the intersection of technology, learning sciences, design, psychology, computer science, and AI. Our commitment is a two week turn-around from submission to notification. Once revisions have been made, the article will be published within a week of final editing. As a result, an article could move from submission to publication in less than four weeks, while having undergone rigorous peer review.

There are a lot of AI-powered “summariser” tools on the market. These tools allow us to paste in unstructured text and have AI identify important sentences, extract key phrases and summarise the main points of the document. My research shows that lots of us are using AI summariser tools to help us to learn more from notes that we take in class, in work, while reading documents, watching videos and listening to podcasts etc. But, while summarising and giving structure to information can help to manage cognitive load and support basic recall, it doesn’t in itself help us to learn

The narrative around cheating students doesn’t tell the whole story. Meet the teachers who think generative AI could actually make learning better.

We're all somewhat grappling with questions about the unique human attributes that remain untouched by the growing incursions of AI. I've positioned this partially as a move from "epistemology to ontology" (knowing to being).