Experimenting with micro-credentials to enhance AI literacy

AI use is increasing in life, education and at work. According to McKinsey’s latest AI survey, 88% of businesses are now using AI in at least one business function, and ChatGPT is now estimated to the fifth most visited website in the world.  

AI literacy is now a fundamental skill for the future, and while the full impact of AI technologies on jobs and the labour market is yet to be understood, we can say with some certainty that employees will need to become skilled users of AI.  This also means that higher education institutions need to prepare current students for a future of work that will inevitably involve the use of Artificial Intelligence (AI).    

There are many different definitions of AI literacy. Microsoft talk about AI aptitude which they define as a new core competence - the ability to work alongside AI.  The term is generally considered to include knowing and understanding AI tools, but also developing the accompanying soft skills required to use them well, such as critical thinking, evaluation and analytical judgement.  Universities are taking a variety of approaches to build AI literacy in their undergraduates.  In this blog post, we share one of our latest learning experiments – the development of an online, asynchronous AI micro-credential for business students.   

Why a micro-credential? 

Whilst there is no agreed definition and they can vary considerably in practice, micro-credentials are typically short learning programmes that focus on specific themes, competencies, knowledge or skills.  They are often self-directed and delivered digitally and many result in the provision of a digital badge to demonstrate learning. They are considered innovative, capable of supporting employability and adapting to changing labour market demands.  They have been suggested* as a potential solution to the forthcoming disruption to the world of work, and the rapid upskilling that will be required to address it.  We considered that using a micro-credential could be an effective way to teach AI to undergraduate students. They are flexible and allow for quick content updates, thereby providing students with the most relevant and up-to-date learning. Students can take them at a time that works for them, and they can complement learning and assessment in their degree studies – learning which is increasingly taking into account AI tools and technologies.     

Design philosophy 

The micro-credential ran over six weeks and was hosted on Canvas. Weekly topics included an introduction to AI, AI applications in business, generative AI and AI and the bigger picture - exploring risks, challenges and the potential future of AI technologies. Participation in the course was voluntary, with students undertaking a total of approximately ten learning hours.  Each topic consisted of an online lecture hosted on YouTube, scaffolded with personal reading, watching or listening to curated learning materials and followed by a task or activity, submitted weekly. Assessments were formative through weekly quizzes and reflection.  The micro-credential concluded with a skills activity requiring students to create content via generative AI tools to a given brief, redefining that content and critically analysing it.  On completion, students are issued with a digital badge. 

What we have learned so far  

In our first cycle, 50 students successfully completed the programme. We are now applying our learning and their feedback to develop the credential further. Initial feedback from participants has indicated that students found the course valuable, stimulating and challenging. They like the online format and found the credential easy to undertake alongside their other studies. Some students chose to undertake the whole course over a short period rather than over several weeks. They think that they have learned useful skills and many were able to identify key learnings from the course. It was clear from student feedback that many of them are already very familiar with generative AI tools - key to the AI literacy is moving from use to critical analysis. This was achieved in the course through asking students to reflect critically on output. Feedback also suggests that this familiarity with generative AI does not always extend to broader discussion about AI and its benefits, challenges and risks. This is a key part of AI literacy and one of these important employment related competencies.   

While still at an early stage, this work highlights the potential of micro-credentials as a scalable and flexible approach to developing AI literacy in undergraduates. As AI technologies and their uses (including in education) are still at an emerging stage, higher education institutions must continue to experiment with different approaches to teaching with and about AI. As technology evolves, so can our approach as educators.   

Some selected quotes from our students:  

• Through this course, I’ve learned …. the real skill lies in knowing when to use it, how to question its results, and how to apply it responsibly in the real world. 

• Completing this curse has definitely strengthen my understanding of AI and how quick it is developing.  

• Overall, this course was a valuable experience and motivated me to keep developing and learning the rise of AI to develop my abilities further. 

• I feel as though my AI skills have been developed greatly! 

References:  

Making-micro-credentials-work-Oliver-Deakin-2019-full-report.pdf  Emeritus Professor Beverley Oliver, Deakin University