Adapt or perish: a call for academics to embrace artificial intelligence
If academics do not embrace artificial intelligence (AI), they will soon find themselves having to teach students who grew up and studied in AI enabled environments and will be ill-equipped to fulfil their teaching roles.
This was a warning call by Professor Langa Khumalo (right), Executive Director of the South African Centre for Digital Language Resources (SADiLaR) at the North-West University. Professor Khumalo was among the participants at the 3rd Higher Education Conference hosted by Universities South Africa (USAf) in Pretoria from 9 to 11 October 2024.
Speaking during the question-and-answer session of the panel discussion titled: ‘AI and Teaching and Learning in the Future University,’ Professor Khumalo said academics have no choice but to embrace AI if they want to be fit-for-purpose.
“I don’t think it’s a question of whether or not we have a choice to embrace AI. It is about how we look at the systems that we have and explore how these can assist us in driving this forward.
“The question is, are we adaptive enough? Do we have the ability to unlearn and relearn very quickly? If we don’t do that, the next generation of our students are going to be AI driven… They are already using the infrastructure that we are looking to harness in our teaching and learning. So, if we don’t prepare, we will have a generation of students that is going to enter the higher education system and be way ahead of us and we are going to be underprepared,” he said.
How AI can enhance teaching and learning
Professor Heather Nel (left), Senior Director for Institutional Strategy at the Nelson Mandela University, provided insights on how AI can enhance teaching and learning while saving academics time on administrative tasks that would ordinarily take up hours of their time.
“Some of the benefits of AI are improved efficiencies. As a professor, you can save a lot of time on tasks like grading, processing your marks and doing all the academic administration that so often takes up a lot of your time. AI also allows for personalised and adaptive learning; it actually learns from the student as it interacts with the student. It assesses what the strengths and weaknesses of the individual are and can respond with the most appropriate learning strategies to assist that student to master their learning.
“It can allow for enhanced engagement… Student engagement can be facilitated because they become actively involved in the learning experience through immersive experiential learning that AI tools can provide. AI also allows for intelligent tutoring and virtual assistance. The chatbot is one example with can virtually tutor the student and allow for interaction. Where the professor might not be available, AI can assist the student and the individual level by answering some frequently asked questions and so forth.
“As an academic, AI can help you with content creation and curation. You can generate immense sets of learning materials, very rich readings, and a lot of it is generated incredibly quickly whereas we used to sit and labour over literature studies. AI can also help with curation, where over time you collect materials, you add to them and you improve them and as a result, the materials that you’re using to teach and for students to learn remain up-to-date, relevant and cutting-edge.”
The AI and Teaching and Learning in the Future University breakaway session of the 3rd Higher Education Conference drew a large following and ignited a healthy debate among the delegates.
Professor Nel said another area where AI is particularly useful is its ability to allow for data-driven analytics. “This is where the power of AI is quite significant, in terms of student success,” she said.
“If you have a large group of students in your class and you need to see what they’re struggling with, what they’re grasping and you need to adapt your teaching, you can use a lot of the analytics relating to student performance to help you to not only see retrospectively how students are doing, but to also use predictive analytics to anticipate where students might struggle and customise your teaching accordingly, based on those data driven insights.”
Levelling the playing field
While the possibilities seem endless, academics and institutions must consider potential barriers to accessibility, particularly in the South African context. Professor Nel cautioned that in South Africa, where the students come from and study within different socio-economic environments and conditions, the use of AI needs to be sensitive and suitable for these different dynamics.
“While AI can enhance accessibility and allow for collaboration that was previously not possible, it can also pose a risk in that very same area. It’s been seen with disabled learners, particularly those with visual or learning impairments, that it can be tricky for them to navigate AI. We’re also seeing that students living in rural areas or areas which are historically underprivileged and don’t have access to electricity, let alone connectivity, it can also be an issue. So we need to be mindful of that.”
Dr Sianne Alves (left), Director at the University of Cape Town’s Inclusivity and Change Office, also spoke on the need for universities to be mindful of the students’ varied socio-economic conditions when it comes to using AI for teaching and learning. She emphasised the disparities in access to digital tools and connectivity, underscoring the need for inclusivity in the implementation of AI-driven education solutions.
“As we know, the socio-economic realities of South Africa do currently affect teaching and learning. So if we think about AI and access to devices… we know that only 10% of households have fibre connection in the country. Only 1% of rural households have connection to possibly mobile data and the usage gap persists across income level, across gender and location. This is problematic if you look at what our staff and student profile is, and how they’re managing to grapple with the higher education programme in their homes and in university residences.”
The future is now
Professor Simon Gifford (right), CEO and co-founder of Mashauri, an online platform designed to enable universities to offer experiential entrepreneurial education to students, shared freely available resources that academics and institutions can use to dramatically enhance the teaching and learning experience.
“The world of work has changed, and as we sit here, it’s changing more and more. New skills are required and we have to give our students the skills to be ready for market. We need to think about our teaching methods and really start harnessing some of the benefits that AI can give. We don’t have to wait for years and years; those benefits and tools are there now and are available to our graduates, and to ourselves to use. There are massive opportunities already.”
Discussion
During the question-and-answer session Professor Francois Strydom (left), Senior Director of the University of the Free State’s Centre for Teaching and Learning, said universities must create varied, alternative forms of assessments because old and traditional assessment models – such as lockdown online assessments where web browsers are blocked – are not a holistic measure of a student’s aptitude and how they’ll fare in specific professional disciplines.
“I think it’s about navigating this transition, and in our conversations, this becomes a very important question around academic identity. I asked an academic with years of experience whether we are training good graduates/professionals, and there was just two seconds too long of hesitation. Which for me raised the question, how are we thinking around academic identity here? … Are our professors becoming so anxious about AI that they’re starting to doubt whether they know how to produce a good accountant, doctor or whatever? I think that’s another side of the conversation which we must bring in,” he said.
Professor Vivienne Lawack (above), Deputy Vice-Chancellor: Academic at the University of the Western Cape, who chaired the session, posed a question for the academics to mull over.
“In regulation, there’s a difference between principles-based regulation and rules-based regulation. Our initial reaction is always to opt for the rules-based regulation before jumping to policy. When I initiated this at our university, my question was: shouldn’t we first look at the principles of how we can embrace AI without separating it from learning and teaching, research and all the other aspects?
“My question to USAf is: Just like we did with the World of Work and Teaching and Learning, isn’t it time to start thinking about a technology strategy group, where we look at what kind of principles can guide universities?”
She concluded the session with these words: “AI will not only change how, but why we teach”.
Nontobeko Mtshali is a contract writer for Universities South Africa.
