Lixian Yan and Monash U colleagues are keen on the capacity of Generative AI in education, for delivering personalised tutoring services, generating instructional materials, making lectures accessible and nurturing creativity.
As long, that is, as people know how to use it, technically, ethically, critically.
There are, they acknowledge, already subject based AI literacy scales, including, for medical students, EFL teachers, AI workers and general university students but most assessments are heavy on self-reporting and light on assessing understanding.
Which is why they have created, and piloted, a GenAI Literacy Assessment Test that they report can capture user literacy and predict learning performance. Their paper includes details, very detailed details, on the construction, testing and assessment process used to create the GLAT, using “established standards for psychological and educational measurement.”
Their take-out is: “by incorporating the GLAT into curriculum development, educators can better align teaching strategies with the specific competencies required for effective GenAI engagement, thereby preparing students for an AI-driven future.”
Most important, they state that the model could be used across, “diverse educational levels and contexts, addressing the complex and evolving landscape of GenAI technologies.”
