Ed/Tech must-reads

Enhancing digital equity – a shift in learning and teaching perspectives - Webinar Weds 19/7 12 noon AEST ASCILITE TELedvisors Network

Everyone talks about the weather but nobody ever does anything about it. The same can be said for digital/AI literacies in Higher Ed. While developing these capabilities in students (and staff) has been widely identified as a key priority as we grapple with the AIpocalypse, practical examples of this happening on the ground have been scarce. This webinar explores timely work by Justine Maldon, Michelle Pedlow and Daniel Gilogley at Edith Cowan Uni to enable students to self-evaluate their skills and needs and find appropriate support. (Recordings will be available later on the TELedvisors YouTube channel)

Generative AI: what do researchers need to know? - Webinar Tues 18/7 11am AEST TEQSA and CRADLE (Deakin)

The excellent TEQSA/CRADLE webinar series about all things AI continues this morning with Matt Kuperholz (Deakin), Nitya Phillipson (ARMS), Simon Knight (UTS) and Justin Zobel (UniMelb) discussing all things AI from a researcher standpoint. With recent concerns arising about possible AI assessment of research funding applications fresh in the mind, this seems more timely than ever.

Coping with Imposter syndrome - Twitter

The prevalence of imposter syndrome in HE tells us that there is work to be done on changing the culture of the academy for the better. This thoughtful Twitter thread on the matter from Petra Boynton brings some kindness into the mix with a combination of exploring where these feelings come from and strategies for mitigating them.

Future Trends Forum recordings - Bryan Alexander

Bryan Alexander looks like a wizard and brings his ed/tech futurism magic to engaging weekly discussions of all manner of things in the sector. It is North American based but the concerns and concepts are largely global. This is the complete set of hour long recordings going back to 2016

Testing of Detection Tools for AI-Generated Text - ARXIV (Pre-press)

A common response to the rapid rise of GenAI has been the question of detection. A mixture of established EdTech players desperate to hold their market share and newcomers panning for gold have rushed to make wild sounding promises with scant meaningful evidence. This not-yet peer reviewed paper evaluates 14 products against GPT 3.5 outputs and finds them largely wanting, particularly when submitted text is a mixture of human and GenAI text.