## 1 Introduction  
Artificial intelligence (AI) offers promising avenues to revolutionize education, notably through adaptive learning systems. These systems tailor the content to the individual understanding and pace of each learner, freeing teachers from repetitive tasks and allowing them to focus on fostering communication and higher-order thinking skills [1]. As AI takes on subject-specific tasks in education, teachers can focus on fostering creativity and critical thinking. With tools such as ChatGPT capable of learning, processing information, coding, and debugging, educators can redesign assignments to prioritize these skills over rote problem solving [1]. This empowers students to actively participate in their learning and develop skills that transcend current AI capabilities. Personalized education, achieved by adapting to different learning styles and interests, can significantly improve the achievement of learning objectives and prepare students for future careers [2]. However, the implementation of adaptive learning systems presents challenges. These include data collection, processing, and centralized management concerns. Moreover, AI models struggle to understand nuanced user intent, a capability that remains largely human [3]. Ideally, future adaptive systems should better understand the cognitive processes that underlie learning to fully personalize the educational experience. This means that new learning solutions come with technologies and methods to cover these requirements. This article aims to present a way to cover these requirements. Accordingly, this research proposes investigating students' views on the application of ChatGPT in learning and, at the same time, examines the potential for integrating generative AI into learning systems, with the aim of identifying benefits for students. To achieve this, we address two specific questions:  
1. How do students perceive the use of generative artificial intelligence tools, such as ChatGPT, to enhance their learning journey? 2. Is it possible to integrate generative AI into a learning system used in education? The answer to the first question in this article is obtained by analyzing data from a questionnaire sent to students. The results of this questionnaire helped to answer the first question and, at the same time, contributed to proposing an architecture for the learning system. This architectural design proposal represents the way in which question two of this article was addressed. The architectural proposal is also based on an analysis of four existing learning platforms, none of which currently uses generative AI to improve responses to learner questions. Only one platform incorporates large language models (LLMs) for personalization. On the contrary, our architecture emphasizes the role of generative AI in supporting student learning. This paper contributes to a novel architecture of adaptive learning systems that uses generative AI. Through this architecture, our aim is to demonstrate how generative technologies can overcome current limitations in addressing learning needs. We also provide examples of potential learning solutions based on this architecture, illustrating how AI-based generative platforms can create more engaging and motivating learning experiences. Additionally, we explore how components of the proposed architecture can be integrated into other systems to provide continuous access to learning resources. The proposed architecture aligns with [PERSON]'s constructionist theory, which emphasizes that new knowledge builds upon existing knowledge and that learners should actively construct their understanding through practical application. The teacher's role in this model is to guide, not simply to instruct. Our architecture encourages the participation of learners and promotes learning through construction and discovery [4]. Generative AI, which is central to our system, is a subset of AI that creates new content by learning from and reinterpreting existing data.