## 5 Discussion  
The results obtained reinforce the idea that AI is profoundly transforming education, particularly in relation to the personalization of learning. AI technologies, such as intelligent tutoring systems and ML algorithms, are allowing content to be tailored to individual students' needs, an approach widely recognized in the literature. Furthermore, AI provides immediate feedback, which improves the efficiency of educational processes. This finding is consistent with what had been previously discussed, where the flexibility and dynamism that AI brings to the teaching-learning process was highlighted [22]. Another important aspect is the growing attention towards explanatory AI (XAI), which promotes transparency in the algorithms used. Understanding how and why decisions are made within AI systems has been identified as an essential factor to ensure the acceptance of these technologies by educators and students. This study confirms that the explanation of algorithmic processes is key to the successful integration of AI in education [71]. Furthermore, it is confirmed that AI systems must be designed in an ethical and bias-free manner, a topic widely discussed in the literature. The use of big-data analytics and the prediction of academic performance are also highlighted in the results of the study. AI-based tools have the ability to identify learning patterns and predict student performance, allowing early intervention in those who might be at risk of underperformance [24; 72]. These findings are consistent with what has been presented in the literature, which argues that AI can be used to create more personalized and adaptive educational environments. The capacity for early intervention is seen as an opportunity to improve inclusion and reduce inequalities in access to education. The integration of emerging technologies, such as virtual reality (VR) and online learning platforms, has also been shown to be effective in this study. These technologies improve the understanding of complex concepts and increase accessibility to learning, especially in hybrid or remote contexts. These results are in line with previous observations, which have highlighted how VR can create immersive experiences that benefit students by allowing them to practically explore concepts that would otherwise be difficult to understand [73]. The results also highlight important ethical and social challenges that must be addressed for an effective implementation of AI in education. In particular, the risk of bias in AI algorithms has been identified, which can perpetuate pre-existing social inequalities, such as those of gender, race, or social class. This concern coincides with what has been previously noted in the literature, which warms about the possibility that automated systems reproduce the same inequalities that exist in the data with which they are trained [71; 74]. The need to design transparent and equitable systems, which avoid perpetuating injustices, is a central theme in the current debate on the implementation of AI in education. The adoption of advanced technologies in the classroom, especially regarding teacher training, has been another key issue. The results of the study underline that adequate training in the use of AI is essential for teachers to be able to effectively integrate these technologies into their educational practice. Lack of training can lead to resistance to the adoption of AI, limiting its potential to improve education. This finding is in line with previous discussions that emphasize the importance of ongoing training to ensure that educators are prepared to use emerging technological tools [47; 75]. In this sense, the results of this study confirm several of the trends and concerns that had been identified in the literature. AI has the potential to transform education by making it more personalized, accessible, and efficient.