Preparing Students for an AI Future

Michael Sankey, Adjunct Professor, Charles Darwin University

Michael Sankey, Adjunct Professor, Charles Darwin University

Recent technological disruptions in education have significantly changed how education is conducted. The rise of Generative AI (GenAI) has widened the digital divide for the general population, education and industry. Although tempting to ignore this existential threat, we cannot, for as technology continues to evolve, it also provides new opportunities for us.

In recent focus, GenAI’s impact on academic integrity has demanded higher levels of AI literacy. Developing this literacy encompasses the affordances these new technologies provide. Notwithstanding, many national regulators are started to tighten the screws on institutions, requiring them to evidence that their student are not cheating. However, as AI skills are now fundamental in graduate employability, a greater emphasis on discipline-based AI literacy is required.

There remains a clear digital divide in society, posing a challenge to education. This is highlighted in the ASEAN ‘Digital Masterplan 2025’. In Australia, 25 percent of people are still digitally excluded, with limited access to social, educational and economic opportunities. It is getting easier, though, with AI enhancements in everyday devices. For example, Apple Intelligence is there by default for some 1.3 billion users in Apple iPhones. We have Copilot in the Microsoft suite of tools and Google's Gemini for those using these tools. This is a massive game changer for those with only basic computer skills, particularly as most people now have a smart device.

The first challenge is academic integrity, which has led us to re-examine our curriculum to ensure it is the best fit for purpose. This was recognized well before the advent of Gen AI by Rundle et al. (2020, p. 111), who suggested we apply a ‘Swiss cheese model’ to the assessment, using multiple checkpoints across our assessments. This encourages students to engage, as they see their work joined across a program, giving them a Meta understanding of how what they have done fits into their future. The University of New South Wales has developed some great resources to support a programmatic or systemic approach to assessment.

“Being more flexible means learners from various backgrounds can access education, regardless of socio-economic barriers, as technology now follows them and knows where they’re at”

Further strategies, such as peer assessments, are student-centric and emphasize partnering with students on their learning journey. Third-party providers, such as FeedbackFruits, have introduced peer interactions and this approach has gained significant traction in both formative and new summative assessment strategies. Interactive oral assessments and vivas, which focus on authentic scenarios, can also provide a secure and scalable method of surfacing learning. This takes many forms and links back to the Socratic traditions of education that today are seen in objective structured clinical examination, viva voce and interactive oral assessments that offer opportunities to develop adaptability, problem-solving skills, industry-specific knowledge, active listening and communication skills. This enhances employability skills and fosters critical thinking, communication and collaboration. Institutions can better prepare their students for post-university life by focusing on authentic assessments, such as oral assessments.

Gen AI has forever changed the way we will teach. However, it also provides new possibilities for multimodal GenAI capability building. We have new ways to produce text, code and create and manipulate images, speech, audio, video and spatial outputs. As a result, we see a new vibrant diversity of outputs that will become more profound. We will see new agentic AI systems (agents) emerging, moving us from knowledge to action. These systems autonomously interact with other applications to execute functions. This holds great hope for student support, streamlining many time-consuming functions around managing and monitoring learner records.

Economic, social and political issues running tangentially to education (informing what is taught) are driving demand for flexible and just-in-time learning, with learners wanting engagement when they want it. As the sector grapples with these demands, we look to new models of flexible learning that utilize AI. Being more flexible means learners from various backgrounds can access education, regardless of socio-economic barriers, as technology now follows them and knows where they are. This suggests a truly learner-centered approach to education.

As staff create AI-generated learning objects, build AI-powered agents and use AI to help them teach, assess and provide personalized learning experiences and feedback, this requires a significant upskilling of staff in newer pedagogies to engage with these new learning technologies. However, one must first consider that the pedagogical house needs to pull the technological cart.

As the sector faces these challenges, educators will develop new skills as they always have. Thus, the quest has begun to reshape the educational environment. So, to quote Frodo from The Lord of the Rings, “the road goes ever on and on down from the door where it began. Now far ahead the road has.