Editors’ Summary: In this post, Ben Williamson examines the growing quality control and methodological rigor crisis within the field of Artificial Intelligence in Education (AIED) research. By highlighting the recent retraction of a high-profile paper on ChatGPT and analyzing two new critical literature reviews, Williamson demonstrates how the pressure to quickly produce statistical evidence has […]
Editors’ Summary: In this post, Alex Reid critiques the reliance on instructional design and “design thinking” to counter the frictionless nature of AI in higher education. Challenging the popular notion of “engineering friction” into curriculum, he argues that reducing learning to predictable outcomes merely creates automated “work” that AI easily replicates. Reid contends that AI […]
Editors’ Summary: Paul Taylor, professor of health informatics at UCL, reflects on his lifelong relationship with programming and the rapid displacement of software engineers by AI coding tools. Drawing on personal experience using Claude Code and the fictional Mythos model, he traces how AI has moved from writing code snippets to autonomously developing, testing, and […]
Editors’ Summary: In this post, the author shows how the rise of AI has made the critical thinking component of using code in DH even more essential. He details his initial explorations using Claude Code to build DH web apps for use in the classroom. This post argues that the old tools of Digital Humanities […]
