This paper is a systematic literature review (SLR) investigating how intelligent systems leverage learning-related information to adapt their behaviour. This paper is done according to PRISMA guidelines, which ensures reproducibility. For this review, we analysed 58 papers published after 2023. The review focused on types of inputs, system objectives, and application domains. The systems in this survey adapt their behaviour based on various inputs, such as facial expression, gestures, eye gaze, and user preferences. These systems enhance the learning experience by increasing user engagement and motivation. Many of these papers target the education domain, such as STEM, but there are also papers focused on motor skills training or cognitive training. Time constraints limited the scope of the review, particularly in identifying long-term trends. But the result can be a solid base for future research into adaptive learning and training platforms.