todoELE

Stanford education scholars Victor Lee and Denise Pope discuss ongoing research into why and how often students cheat. The launch of ChatGPT and other artificial intelligence (AI) chatbots has triggered an alarm for many educators, who worry about students using the technology to cheat by passing its writing off as their own. But two Stanford researchers say that concern is misdirected, based on their ongoing research into cheating among U.S. high school students before and after the release of ChatGPT.  

This week, I attended a round table discussion at the House of Commons with politicians and experts from across the education sector to feed into UK policy on AI in Higher Education. Unsurprisingly, one of the key areas of concern and discussion was the impact of AI on academic integrity: in a world where AI can write an essay, what does AI mean for what we assess and how we assess it? And how do we respond in the short term? In this week’s blog post I’ll summarise the discussion and share what we agreed would be the most likely new model of assessment in HE in the post-AI world.

I wanted a place to translate research into advice, or commentary, in a way that was short and useful - covering One Useful Thing in each post. Due to timing and circumstance, I have very much come to focus on AI, and its impacts on work and education. So that is now the One Useful Thing of this blog.

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.