Immersive AI technologies can boost Africa’s higher education sector

With the current state of technological advancement and AI automation, investments in scaling up AI models need to also be put into human learning, to allow the continuous reskilling of young people to take up new roles in the ever-changing future of work. This blog assesses how students requiring tertiary education in developing countries can utilize AI and immersive technologies to gain access to a structured and comprehensive form of online education. It highlights the need for the intentional conversion of vast internet resources into learning resources and how self-directed learning can be better facilitated with the use of AI and immersive technologies.

Higher education can have direct effects on the economic growth of countries [1]. Access to higher education in developing countries remains limited due to the growing young population and a limited number of higher education institutions. In the early to mid-1800’s, the Prussian model of education was introduced to provide universal education through a factory system of mass production of knowledge for students, all who went through the system at the same pace according to age. This traditional system of education which sought to develop compliance for factory employment rather than critical thinkers, is seemingly out of date for promoting 21st century skills such as creative thinking, emotional intelligence and collaboration [2]. The internet has revolutionized the learning process. As is commonly known, the internet provides a vast resource of educational content from Wikipedia to YouTube as well as podcasts, online books and a plethora of articles from open access academic journals to blog posts from experts. In addition, the COVID-19 pandemic and accompanying lockdowns resulted in the need for quasi-homeschooling with parents taking on instructor roles to fill in the gaps of remote online learning. For university students, this often resulted in their need for self-directed learning.

Though the internet provides access to resources, these need some conversion into learning resources. These swaths of information require personalized learning goals that enable the curation of learning content. Students can also access Massive Open Online Courses (MOOC’s) from the best universities in the world and be taught online by the best lecturers in the field.

Self-directed online learning involves students being able to be independent learners and take ownership of their own learning experiences by developing their own learning goals [3]. The significant role AI plays is that it can enable learners to diagnose their own learning needs, select their own online resources, consume the information, and reflect on the content to ensure complete understanding of the material. Generative learning involves learners' actively engaging with learning material to construct meaningful mental representations through comparison to previous experiences, to enable integration into their existing knowledge structure [4]. Through self-awareness of learning achievement, students identify gaps in knowledge and repeat the process. Self-directed learners possess metacognitive skills of being able to reflect on their own learning process and are therefore able to learn how they learn and manage their own online learning experiences.

With the release of Chat GPT at the end of 2022, large language models (LLMs) and AI chatbots have seen increasing use in education by teachers for developing learning materials, lesson plans and assessments as well as grading assistance. Students have been using LLMs for summarizing literature and writing essays resulting in skills like writing, forming an argument and critical-thinking being outsourced to these language models over the long -term. However, LLMs have also enabled personalized micro-learning and content recommendation in line with specific learning styles. They have served as homeschool support for parents, and most importantly served as personal AI tutors for students as a point of reflection and for conversational learning that is available on demand [5]. AI tutors can provide personalized feedback, allow students to bounce ideas and offer step-by-step interactive guidance, simplify concepts and enhanced communication skills through role playing social interactions [6].  

Simultaneously, the pandemic saw Facebook change its name to Meta to double down on the Metaverse as the next computing platform. While Augmented Reality/Virtual Reality (AR/VR) remains a niche medium, as evidenced by the recent failure of the Apple Vision Pro, immersive technologies such as AR/VR have steadily gained ground in educational and training use cases. AR/VR hold promises to provide contextual learning by immersing learners in relevant environments to enable presence, interactivity and real-life experiences. Rather than physical field trips or access to physical university equipment like laboratories, students can access virtual versions and virtual work experiences to enable practical learning from home. Furthermore, convergence of advancements in AI to automate 3D content creation could potentially launch the proliferation of immersive technologies in education.

Conclusively, and recollecting the lessons learnt from the COVID-19 pandemic, there remain various challenges of online learning including excessive screen time, disengagement and absence of the social aspects attached to an in-person learning environment. These can be overcome by encouraging peer learner meetups for learners who are studying the same topic and learning online as well as bridging offline learning through real world projects and site visits. In addition, in the context of learners in rural areas, investments in high-speed internet, hardware and electricity access may boost their use of these forms of learning. From a policy perspective, the need for certification for self-directed learning traditionally provided by higher education institutions engendering trust in their brand, would need to be reassessed. Opportunities exist for higher education accreditation authorities in Africa to rethink their methods of assessment and re-invent these processes.

References

1. Bloom, D., Canning, D. & Chan, K. (2006). Higher Education and Economic Development. Harvard University.

2. World Economic Forum (2023). Future of Jobs Report.

3. Wu, D. ET AL (2024). Unlocking Potential: Key Factors Shaping Undergraduate Self-Directed Learning in AI-Enhanced Educational Environments. Systems, 12(332).

4. Fiorella, L. (2023). Making Sense of Generative Learning. Educational Psychology Review, 35 (50).

5. Mogavi, R. ET AL (2024). ChatGPT in education: A blessing or a curse? A qualitative study exploring early adopters’ utilization and perceptions. Computers in Human Behaviour: Artificial Humans, 2(1), January-July 2024.

6. Wang, C., Zixi, L. & Bonk, C. (2024). Understanding self-directed learning in AI-Assisted writing: A mixed methods study of postsecondary learners. Computers in Education: Artificial Intelligence.

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Author's bio

Dr. Praneschen (Che) Govender, an immersive technologies practitioner born in South Africa and based in Amsterdam. He holds a PhD in Psychology from the University of KwaZulu-Natal. Praneschen currently works on integrating VR/AR into the curriculum at Hotelschool the Hague. He has experience in the research, design and facilitation of VR/AR experiences in tertiary institutions and has been involved in managing immersive technology research projects for integrating within higher education and the private sector. He is currently part of various research projects within the hotel industry on using AR/VR to improve the performance of new hires as well using AI and self-directed learning to enhance education.