Artificial intelligence (AI) in the educational system is a hot topic all around the world right now. The use of AI algorithms and systems in higher education is increasing year on year and as education progresses, researchers are employing advanced AI techniques to address complex learning issues and tailor teaching methods to individual students.
AI is clearly adding value to the higher education sector. However, adopting AI can be daunting for institutions lacking the time, expertise, and resources to explore its many applications. So, how will AI help higher education in the future? And what might be the issues we need to start looking into?
AI shaping education
The brilliance of AI is not in its ability to replace human interaction or creation. Instead, it can be a useful supplement for sorting through large amounts of data and making mundane tasks more efficient. In addition to automated administrative tasks, AI offers various technologies for submitting papers, checking quizzes or, for example, periodic progress reports. Because of the significant impact of AI on learning, smart content, such as digitised guides, video lectures and video conferencing, is very popular among students and teachers. It has grown in importance because it greatly facilitates the learning process and opens up new opportunities for students.
AI can also be incredibly helpful for students by guiding them through the process of school selection, thereby speeding up their career path. An example of this is the Unimy Match tool which uses AI to match potential candidates with universities that best fit their profile, background and goals.
Advantages and challenges of AI
AI can boost student engagement, ease the workload for teachers and help with many other aspects. But what about potential negative effects? Let’s address the most common concerns about AI such as fairness and bias. And is it possible that AI will eventually replace human teachers?
Inclusivity and accessibility
AI-powered education technology has the potential to improve access and inclusivity for students with disabilities or other learning needs. However, there is a risk that AI-based systems will not be accessible to all students, which could potentially contribute to already existing inequalities. Education experts see great promise in AI assistants that provide support to students at any time of day, as well as using AI to make students' learning journeys unique. However, we must ensure that this type of development involves everyone.
Using data the right way
AI advancements, combined with an increase in available data, open up doors in areas such as learning analytics solutions. But in the current stage of development, AI systems are trained by humans. This means that an AI system can only be biased if it was trained using biased data, which can lead to unfair and discriminatory treatment of students, for example.
Predictive analytics models and algorithms are another type of technology with great potential. For example, an educational institution that uses a predictive analytics model can predict whether a student will pass or fail a course based on existing data. The problem is that they are currently very difficult to use because although we can see that an AI model has reached a conclusion, we cannot see why. Lately, there have been new advances in AI explainability, which means that we have a much better understanding of the factors influencing any given situation. Because of the value of being able to draw insights from this, universities will continue to prioritise data and analytics.
Technology vs. teacher
Undoubtedly, AI can be a useful tool for enhancing our education system, teaching methods, and learning potential. However, it would be troublesome to think that it could completely replace the human factor in teaching. Human interaction is essential for developing critical thinking and creativity. Students should have access to both human and AI-based educational resources.
Teachers continue to be on the front line of education. They must understand how AI-enabled systems can facilitate learning in order to make moral judgments. Teacher training should focus on:
- Using AI to automate repetitive tasks
- Research and data analysis abilities to help teachers analyse data provided by AI systems
- New management skills to help them better manage the human and AI resources at their disposal
AI advancements are ever more present in higher education. These breakthroughs, which occur in both classroom and research settings, give fuel to future technological literacy for businesses, particularly among business students. Institutions are recognising opportunities to use AI to create more adaptive learning environments and to supplement education with analytics, creative tools and automated labour.
It is important to consider the advantages of implementing AI systems for higher education institutions, teaching and learning. It is also critical to recognise the disadvantages of using AI in education and take the necessary steps to mitigate any negative impact.