Keeping up to date with Gen-AI
Photo by D koi on Unsplash
“The generation of young people that are starting primary school this year […]—with their new school bag and their new school shoes and their shiny new lunchbox—[…] is the first generation in history to not experience education without ChatGPT.”
Professor Cath Ellis (UNSW) a leading expert in Academic Integrity joins Stephen Matchett to discuss Gen-AI, the effect it is having on teaching, whether it will end contract cheating, and how educators may respond.
Professor Cath Ellis & Stephen Matchett on Gen-AI (00:36:18s)
Ask the question, what are we assessing in terms of the student learning? When we ask students to write an essay or a report, we are asking them to produce an artefact that represents their learning. Is there another way of doing this?
- Can we leverage oral assessments, having conversations with students about their learning? It may take a lecturer 30 mins to read, grade and administer a 3000-word essay, it could take 15 mins to have a conversation with a student to assess their learning.
- Paradigm shift – change focus from the technologies and focus on what we are asking students to learn. What is the value in asking students to learn or do something that a bot can do?
- Programmatic assessment – what do students need to know to graduate, enter the workforce and contribute to their profession? Offer more formative and low stakes learning throughout the programme with one or a few higher stakes assessments at the end.
- Remember, humans are curious and creative, the more bots do, the more we value what humans do and the more creative we become.
“What we need to be doing now is shifting our emphasis on helping our students learn how to learn, and specifically learning the evaluative judgement skills […] to understand the difference between
- good enough and not yet good enough
- good enough and good
- great, and (ideally) excellent.
And that’s where, still, the realm of human skills, human expertise […] is dominating.”
Backward mapping assessments in a programme-level approach. Nicholas Charlton and Richard Newsham-West unpack the term ‘program-level assessment planning’ and the advantages of planning a holistic assessment journey for students, rather than the more common siloed-subject, modular approach.
In this blog AI disrupts assessment overload, David Carless (University of Hong Kong) discusses how we can use the opportunity of Gen-AI to look at the design of our assessments and the issue of assessment overload.
Amir Ghapanchi (Victoria University), in the article How generative AI like ChatGPT is pushing assessment reform, suggests a list of assessment types to mitigate AI use such as staged assignments, personal reflections and class discussions
Danny Liu (University of Sydney) gives extensive and practical examples of how Gen-AI like ChatGPT can be used in teaching. Prompt engineering for educators – making generative AI work for you.
Dragan Gasevic, George Siemens, and Shazia Sadiq, in Empowering Learners for the age of artificial intelligence, discuss 7 themes and the findings of studies related to these.
- Intersection between AI and humans and the space of coordination.
- Assessment exploring the challenges and opportunities of AI.
- Explainability in AI and the need for educators to understand and trust it.
- Design for learning that offers principles for designing AI-driven systems.
- Conceptual AI and learning and the development of new theories of learning.
- Accurate predictions and their role in future education.
- Applications of AI in classrooms.
UNESCO – a quick start guide and asynchronous seminar. This guide provides an overview of how ChatGPT works and raises some of the ethical challenges we are facing in higher education. The guide suggests some practical steps that institutions can take.