The paper "AI and Personalized Learning: Bridging the Gap with Modern Educational Goals" by Kristjan-Julius Laak and Jaan Aru explores the alignment between AI-driven personalized learning (PL) solutions and the broader goals of modern education. The authors examine the characteristics of AI-driven PL solutions in light of the OECD Learning Compass 2030 goals, identifying a gap between the objectives of modern education and the current direction of PL. They argue that while PL technologies have shown effectiveness in enhancing learning performance, they often fail to embrace essential elements of contemporary education, such as collaboration, cognitive engagement, and the development of general competencies. The paper highlights the limitations of current PL systems, particularly in fostering learner agency, developing general competencies, and promoting collaboration. It also discusses the potential of large language models (LLMs) like ChatGPT to address these limitations by providing more dynamic and collaborative learning experiences. The authors propose a hybrid model that blends artificial intelligence with a collaborative, teacher-facilitated approach to personalized learning, emphasizing the need for a holistic change in the educational system. The paper concludes by advocating for a more evidence-based approach to PL that aligns with the educational goals set out in the OECD Learning Compass 2030.The paper "AI and Personalized Learning: Bridging the Gap with Modern Educational Goals" by Kristjan-Julius Laak and Jaan Aru explores the alignment between AI-driven personalized learning (PL) solutions and the broader goals of modern education. The authors examine the characteristics of AI-driven PL solutions in light of the OECD Learning Compass 2030 goals, identifying a gap between the objectives of modern education and the current direction of PL. They argue that while PL technologies have shown effectiveness in enhancing learning performance, they often fail to embrace essential elements of contemporary education, such as collaboration, cognitive engagement, and the development of general competencies. The paper highlights the limitations of current PL systems, particularly in fostering learner agency, developing general competencies, and promoting collaboration. It also discusses the potential of large language models (LLMs) like ChatGPT to address these limitations by providing more dynamic and collaborative learning experiences. The authors propose a hybrid model that blends artificial intelligence with a collaborative, teacher-facilitated approach to personalized learning, emphasizing the need for a holistic change in the educational system. The paper concludes by advocating for a more evidence-based approach to PL that aligns with the educational goals set out in the OECD Learning Compass 2030.