Techniques for using artificial intelligence to personalise learning for individuals

1. Introduction

Education at all levels is increasingly moving toward differentiation and personalisation of learning. This approach creates more flexible and meaningful educational experiences that better recognise each student's individuality.

In this process, artificial intelligence (AI) is playing an increasingly important role. It enables the collection and analysis of data on student progress, interests, and difficulties and, based on these insights, generates personalised content and feedback.

Since technology is not an end in itself, its true value is realised only when integrated with pedagogically thoughtful approaches and methods that provide students with meaningful, active, and motivating learning experiences. For example, AI can foster reflective learning by automatically generating self-assessment questions, support collaborative processes by analysing contributions within team activities, or facilitate the monitoring of student progress through dynamic reports and data visualisations.

Today, a wide range of AI tools and systems are available on the market. Their successful application in higher education depends largely on teachers' ability to recognise the pedagogical potential of each AI tool and system and to understand its capabilities and limitations.

The following will present specific techniques for applying AI in education and examples of AI tools that support them. Special attention is given to ways these techniques can be connected to pedagogical approaches, encouraging diversity within the group and deeper individualisation of each student's educational experience.