Professor Anass Bayaga has investigated how Artificial Intelligence can assist with pedagogical innovations in higher education. Image: Shelley Christians/UWCAI is increasingly becoming a transformative tool at South African universities, and a recent study by UWC Professor Anass Bayaga highlighted the barriers to making the most of AI.
Prof Bayaga is a distinguished academic specialising in neuro-cognitive enhancement of STEAM (Science, Technology, Engineering, the Arts, and Mathematics) and human-computer interaction. His latest research explores factors influencing artificial intelligence adoption among students and academic staff, providing insights that could lead to significant advancements in higher education.
The study, entitled Leveraging AI-enhanced and emerging technologies for pedagogical innovations in higher education, gathered data through comprehensive surveys, capturing perspectives from students and academic staff across South African institutions. Using established theoretical frameworks, Prof Bayaga examined how individuals perceive artificial intelligence technologies and their intentions to adopt these tools.
Prof Bayaga said: “Artificial Intelligence is not just a tool for efficiency; it has the potential to democratise knowledge; it is a catalyst for transformation in education, bridging gaps and creating opportunities for inclusive innovation.”
The study highlights these challenges faced by South African universities in the AI revolution:
Technological Readiness: Many SA universities lack the advanced technological infrastructure to support AI applications. This includes high-performance computing resources, reliable internet connectivity and modern software tools.
Maintenance and Upgrades: Existing infrastructure at SA universities often requires significant upgrades and ongoing maintenance to be compatible with AI technologies, which can be costly and time-consuming.
Integration Challenges: Integrating AI systems with existing educational platforms and databases can be complex. SA universities now face difficulties in ensuring seamless interoperability between new AI tools and legacy systems.
Resource Allocation: Limited financial and human resources can hinder the development and deployment of necessary infrastructure. SA universities may struggle to prioritise AI infrastructure amidst other pressing needs.
Scalability Issues: Ensuring that the infrastructure at SA universities can scale to accommodate growing numbers of users and increasing data volumes is a challenge. This is particularly important for large institutions with diverse and extensive needs.
Technological Readiness: Many SA universities lack the advanced technological infrastructure to support AI applications. This includes high-performance computing resources, reliable internet connectivity and modern software tools.
Maintenance and Upgrades: Existing infrastructure at SA universities often requires significant upgrades and ongoing maintenance to be compatible with AI technologies, which can be costly and time-consuming.
Integration Challenges: Integrating AI systems with existing educational platforms and databases can be complex. SA universities now face difficulties in ensuring seamless interoperability between new AI tools and legacy systems.
Resource Allocation: Limited financial and human resources can hinder the development and deployment of necessary infrastructure. SA universities may struggle to prioritise AI infrastructure amidst other pressing needs.
Scalability Issues: Ensuring that the infrastructure at SA universities can scale to accommodate growing numbers of users and increasing data volumes is a challenge. This is particularly important for large institutions with diverse and extensive needs.
Prof Bayaga said: “By addressing barriers to AI adoption, we can ensure that technology empowers rather than excludes, paving the way for equitable and impactful educational advancements.”
While universities must overcome these and other obstacles to make the most of AI, the study’s findings also highlight attitudes towards AI in Higher Education. And there are further disparities between men and women when adopting AI.
Findings of gender differences in the adoption of AI technologies in higher education:
Behavioural Intention: Both men and women showed a positive Behavioral Intention to use AI, but the factors influencing this intention can differ.
Performance Expectancy: Men tend to place more emphasis on Performance Expectancy, meaning they are more likely to adopt AI if they believe it will enhance their performance.
Effort Expectancy: Women are more influenced by Effort Expectancy, indicating they are more likely to adopt AI if they perceive it as easy to use.
Facilitating Conditions: Both genders consider Facilitating Conditions, such as available resources and support, but these have a minimal impact on their overall intention to use AI.
Behavioural Intention: Both men and women showed a positive Behavioral Intention to use AI, but the factors influencing this intention can differ.
Performance Expectancy: Men tend to place more emphasis on Performance Expectancy, meaning they are more likely to adopt AI if they believe it will enhance their performance.
Effort Expectancy: Women are more influenced by Effort Expectancy, indicating they are more likely to adopt AI if they perceive it as easy to use.
Facilitating Conditions: Both genders consider Facilitating Conditions, such as available resources and support, but these have a minimal impact on their overall intention to use AI.
The study suggests that tailored strategies addressing these gender-specific factors could enhance AI adoption rates among both men and women in higher education.
At UWC, AI is already being used effectively as a teaching and learning tool. One example is how UWC Law uses generative AI in legal education.
AI is increasingly playing a critical role in research at South African universities, especially in fields like healthcare, engineering and data science. Many researchers use AI for predictive modelling, big data analysis and simulations, advancing studies that address local challenges such as climate change, public health and infrastructure development.
