The integration of artificial intelligence (AI) into education is redefining traditional learning methods, particularly in the areas of personalised learning, AI tutoring and digital education. One innovative AI-driven platform that I know and have tested is Astra AI (released in 2023), an application developed by Slovenian innovator Andrej P. Škraba that supports students in the subjects of maths, chemistry, English, German and physics. With over 70,000 users, Astra AI offers an adaptive learning experience and provides instant step-by-step solutions to problems submitted by students via text or image input.

Multilingual Astra AI makes the program accessible to a wider audience, allowing students from different language backgrounds to benefit from its features. The study begins with an overview of Astra AI’s core features, including AI-generated study notes that provide comprehensive summaries of any topic of interest. In addition, the Matura AI feature embedded in Astra AI enables structured preparation for the national Matura exam in Slovenia by guiding students through the curriculum of the above-mentioned subjects. It assists primary school students (pupils) with the national knowledge tests and also provides advanced IB maths preparation with expert guidance, over 2,000 previous exam questions and detailed solutions of previous final exams.

One focus of this article is the comparative analysis between AI-driven tutoring and traditional teaching from my personal perspective. The results show that AI tutoring outperforms traditional tutoring in terms of efficiency, accessibility and personalised feedback. Unlike traditional tutoring, it provides instant explanations, customises explanations to the student's learning preferences and is significantly more cost-effective than human tutors. Despite these benefits, I am also exploring its limitations, such as occasional inaccuracies in problem interpretation, misinterpretation of poor quality images uploaded to the app, and the use of alternative solution methods with which students are unfamiliar. These issues are mitigated when students clarify their questions, indicate preferred solution techniques or refine the quality of input.

Empirical data proves the success of Astra AI: 99% of students improved their understanding and academic performance after using the platform, according to the app developer. This study not only assesses the strengths and weaknesses of AI-driven learning, but also discusses its implications for the future of education. The findings contribute to the discussion on the role of AI in personalised education, its potential to complement traditional teaching and its transformative impact on student engagement and independent learning.

In addition to a limited analysis of AI in education, this paper also presents my perspective as a a high school senior by detailing the effectiveness of Astra AI. The discussion includes its real-life applications in exam preparation, concept mastery and independent problem solving, with emphasis on how it supports students in their final year of secondary school.

Astra AI represents an advance in digital education by promoting problem solving, critical thinking and self-directed learning. As AI continues to reshape education, this paper highlights the need for further research on the long-term impact of AI on learning outcomes, its potential integration into traditional curricula and strategies to overcome its current limitations.

Keywords: Artificial intelligence, personalised learning, mathematics education, digital learning tools, AI tutoring, student engagement, AI-generated learning notes, AI-assisted exam preparation.