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Immagine del redattoreAndrea Viliotti

Artificial Intelligence in Schools

The introduction of artificial intelligence in schools opens up scenarios of great potential, transforming education towards a more personalized, engaging, and skill-development-oriented approach. Thanks to advanced AI tools, such as adaptive platforms and virtual assistants, learning can be tailored to the specific needs of students, offering customized materials and real-time feedback, with the potential to approximate individual tutoring. However, this evolution also brings crucial challenges: data security and privacy, the risk of bias in models, the transparency of algorithms, and the need for an accessible technological infrastructure for all. Moreover, it is essential that AI remains a complementary tool, one that enhances rather than replaces the irreplaceable human interaction provided by teachers.

Educators thus assume an even more central role, acting as technology mediators and guides in the educational process, capable of integrating AI in an ethical and conscious manner, keeping human development and critical thinking at the forefront.

Artificial Intelligence in Schools
Artificial Intelligence in Schools

The Potential of Artificial Intelligence in Schools

With the rapid development of AI and its global accessibility, numerous educational applications have emerged that facilitate its integration. AI can play a fundamental role in various aspects of education, making the teaching process more efficient and adaptable to the specific needs of students.


One of the main advantages of AI in education is its ability to personalize learning. AI-based platforms can simplify lesson planning, adapt teaching materials, and assess students' progress. This is particularly relevant in a context where individual tutoring is not easily feasible on a large scale. The theory of Benjamin Bloom, known as "The Two Sigma Problem," suggests that highly personalized tutoring can significantly improve students' outcomes. AI, with its ability to personalize learning pathways, can approximate this level of support on a large scale, allowing teachers to provide greater individual attention to students without increasing their workload.


AI also helps improve the efficiency of lesson preparation. Teachers can use tools like Slidego or Algor to generate detailed lesson plans, concept maps, and personalized quizzes. These tools save time in preparation, allowing teachers to focus more on direct interaction with students. Using these tools not only reduces the operational load but also improves the quality of teaching materials, as algorithms can suggest up-to-date and relevant content, considering the most recent developments in the field.


AI can also significantly enhance adaptive learning. By analyzing student data, AI tools can identify strengths and weaknesses of students and adjust content accordingly. For example, an AI model can detect when a student is struggling with a specific concept and provide additional support materials or targeted exercises to strengthen that knowledge. This type of adaptive learning allows students to progress at their own pace, overcoming difficulties before moving on to subsequent topics. Personalization is crucial to meet the needs of students with different learning styles and levels of preparation.


Another significant aspect of AI's potential in education is its ability to stimulate active learning and engagement among students. AI tools, such as educational chatbots or interactive learning platforms, can serve as virtual tutors, available to answer students' questions and help them during times of difficulty. This type of constant and immediate support promotes greater participation, reducing frustration related to comprehension difficulties. Additionally, students can use AI assistants to explore topics of interest autonomously, fostering curiosity and self-directed learning.


AI can also change the way learning assessments are conducted. Traditional assessments can be integrated with automated evaluation systems that provide immediate feedback. Immediate feedback is a powerful tool for learning, as it allows students to correct their mistakes in real-time and reflect immediately on what they have learned.


Another advantage of AI is its ability to facilitate collaboration and communication between students and teachers. Platforms like Google for Education integrate AI-based tools for content sharing, project collaboration, and direct communication between teachers and students. This kind of technology helps overcome the physical limitations of traditional classrooms, creating a more open and connected learning environment. Students can work together on shared projects, easily communicate with their teachers outside school hours, and participate in online discussions that enrich their educational experience.


An interesting example of AI usage in education is represented by learning recommendation systems. Just like streaming platforms use algorithms to suggest movies or series based on user preferences, AI systems can recommend customized study materials, such as articles, videos, or exercises, based on the progress and interests of the student. This approach increases engagement and makes learning more relevant and tailored to the individual needs of students, facilitating the creation of personalized and meaningful learning pathways.


Finally, AI can help bridge educational gaps. In contexts with limited educational resources, the use of AI tools can enable the provision of quality education even in the absence of a sufficient number of qualified teachers. Access to virtual tutors and adaptive content can improve the learning experience of students who would otherwise have limited opportunities for personalized support. AI can also be used to provide learning materials in different languages, ensuring more equitable access to education for students from diverse backgrounds.


Challenges and Risks Associated with AI in Education

Despite the benefits, the adoption of artificial intelligence in schools presents several challenges. One of the main concerns is data security and privacy. Using personal information to train AI models carries the risk of privacy violations, requiring the implementation of advanced measures to protect students' data. It is crucial that every model used is transparent and interpretable, to avoid bias and ensure fair and ethical decisions.


Moreover, the collection and storage of student data raise important questions about responsibility and compliance with current regulations, such as the GDPR in Europe. Schools and educational institutions must ensure that sensitive data is managed with utmost care, ensuring that technology providers adhere to strict security standards and that users are informed about how their data is used. A lack of adequate security policies could lead to hacking incidents or misuse of information, compromising students' and families' trust in technology.


Another challenge concerns the presence of bias in AI models. AI systems are trained on vast amounts of data that often reflect existing prejudices and inequalities in society. Consequently, decisions made by these algorithms may be discriminatory. For instance, if an AI model is trained on historically biased data, it could perpetuate gender or ethnic stereotypes. This can have significant negative consequences in education, where all students should have equal learning and evaluation opportunities. To address this issue, it is crucial to develop AI models that are more equitable and representative and undergo rigorous checks to identify and correct any biases.


The lack of transparency is another critical issue linked to AI, often referred to as the "black box" problem. Many AI models, particularly those based on deep neural networks, are extremely complex and difficult to interpret. This limits teachers' and students' ability to understand how decisions are made, making it harder to identify and correct errors. Low transparency can lead to a lack of trust in AI systems since users cannot understand the basis on which certain decisions are made. To mitigate this issue, it is important to develop AI tools that are more explainable, providing detailed information on their decisions, and train teachers so that they can critically evaluate the outcomes.

Another significant challenge is accessibility and inclusion. While AI can help bridge some educational disparities, there is also the risk that its adoption could exacerbate the digital divide. Schools in disadvantaged areas or with limited resources may not have access to the most advanced technologies or the training needed to use them effectively.


Furthermore, access to connected devices and a stable internet connection is not guaranteed for all students, potentially creating a division between those who can benefit from AI and those who are excluded. To address this challenge, investments in technological infrastructure and training programs for teachers and students are needed to ensure that AI is accessible to all, regardless of socioeconomic context.


Dependence on technology also represents a potential risk. If teachers and students rely too heavily on AI systems, there could be a reduction in cognitive and critical skills. For example, students may become less skilled in solving problems independently or in creative thinking, as they become accustomed to relying on the answers provided by AI. It is therefore essential to find a balance between using AI to support learning and maintaining fundamental cognitive skills, promoting technology as a tool to facilitate, rather than replace, human intellectual activity.


Finally, there is the risk of a gradual dehumanization of the educational experience. No matter how advanced, AI cannot replace the empathy, understanding, and human interaction that are central to education. Teachers play a fundamental role in motivating, inspiring, and understanding students' difficulties on a personal level. Extensive use of AI could reduce these meaningful human interactions, limiting opportunities for students to develop essential socio-emotional skills. Therefore, it is crucial that AI is used as a complementary tool, never losing sight of the irreplaceable value of human interaction in education.


The Central Role of Teachers

Despite the advancement of AI, the role of the teacher remains irreplaceable. AI can support lesson preparation and personalization, but fostering critical thinking and a passion for learning is a responsibility that cannot be delegated to a machine. Teachers must become designers of learning experiences, using AI as a tool to make lessons more engaging and interactive while maintaining control over the educational process.


The role of the teacher in the AI era expands, shifting from being a simple knowledge transmitter to a knowledge mediator, a facilitator of experiences, and a guide in developing critical skills. Teachers are called upon to design learning pathways that are not only informative but stimulate reflection, debate, and practical application of knowledge. In this sense, AI becomes a tool that enriches teaching, but it must be guided by the educator's intention.


Teachers must also educate students on the critical use of technology. AI can produce apparently valid responses, but these need to be verified and contextualized. Teachers must therefore train students to be active users, capable of questioning the results provided by AI, comparing them with other sources, and using them to build more solid and meaningful knowledge. This approach develops critical thinking and prepares students for a world where technology plays an increasingly dominant role.


A crucial aspect of the teacher's role is to maintain human interaction within the educational process. No matter how advanced, AI cannot fully understand human emotions or replace the empathy and ability to inspire that teachers possess. These qualities are essential for creating a positive learning environment, where students feel understood and motivated. Teachers must be able to read body language, perceive signals of discomfort or enthusiasm, and adjust their teaching strategies accordingly. This type of human sensitivity is fundamental to educational success and cannot be replicated by an AI system.


Additionally, teachers have the responsibility to adapt the use of AI to the specific needs of their students. Not all students respond to technology in the same way: some may benefit enormously, while others may feel alienated or overwhelmed. Teachers must therefore be able to modulate the use of AI tools, personalizing the approach and seeking a balance between using technology and more traditional teaching methods. This requires in-depth knowledge of the available tools and the individual characteristics of the students.

Another fundamental aspect is socio-emotional education. Teachers must help students develop social and emotional skills, such as stress management, empathy, and the ability to work in groups. These skills are increasingly important in an automated and technological world, as they represent what distinguishes humans from machines. AI can support the teaching of these skills, but only if guided by a teacher who knows how to value the importance of human relationships.


Finally, teachers must be agents of change within educational institutions, promoting a critical and conscious adoption of AI. They must actively participate in continuous training, to better understand the potential and limitations of technology and to develop new skills that make them protagonists of educational innovation. Their field experience is essential to adapt technologies to the real needs of students and to ensure that the integration of AI takes place in a balanced and sustainable way.


In summary, the role of the teacher in the era of artificial intelligence is more central than ever. The teacher is not only a facilitator of content but also a mentor, a model of critical thinking, and a custodian of the humanity of education. Their ability to integrate AI into the educational process, while keeping the focus on human growth and the comprehensive development of students, represents both the real challenge and opportunity for the future of education.


Examples of AI Use in the Classroom

Many educational contexts are already experimenting with the use of AI. Tools like Google for Education, Khanmigo, and Tutor AI are being used to support learning in various subjects, from mathematics to creative writing. These tools allow for the creation of personalized exercises, quizzes, and instant feedback, improving teaching efficiency and enabling students to work at their own pace.


For example, Tutor AI allows for the generation of personalized study plans for each student. Teachers can monitor the progress of students in real-time, adapting content to their specific needs. This form of personalization, impossible with traditional methods, is particularly useful for students with learning difficulties or special educational needs.

Another example of using AI in the classroom is represented by AI-based tutoring systems, such as ChatGPT, which can be used to assist students in creative writing or solving complex problems. Students can interact with these systems to receive suggestions and detailed explanations, improving their problem-solving and critical thinking skills. For instance, a system like ChatGPT can be used to provide tips on improving the structure of an essay or to explore creative ideas in a writing project.


Gamification is also a sector where AI finds application in education. Tools like DreamBox Learning and Smart Sparrow use artificial intelligence to create personalized learning experiences that engage students through educational games. These tools use student performance data to adjust the difficulty of tasks and provide an engaging and motivating learning experience. Gamification, supported by AI, not only increases student engagement but also encourages the development of fundamental skills such as problem-solving and logical thinking.


Additionally, AI is used to promote foreign language learning. Applications like Duolingo use artificial intelligence algorithms to tailor the learning path to each student's specific needs. This approach makes language learning more efficient and personalized, as students receive exercises based on their previous performance and their weaknesses. Using AI in this context helps students gradually and systematically improve their language skills, making learning more accessible and engaging.


Another emerging field is the use of AI for inclusive education. Tools like Microsoft Immersive Reader use artificial intelligence to support students with reading difficulties, dyslexia, or other learning disabilities. These tools offer features such as text-to-speech, instant translation, and text segmentation into more easily understandable portions, helping students overcome learning barriers and fully participate in school activities.


Finally, AI is also used to improve the administrative management of schools. Systems like Schoology use AI algorithms to help teachers manage assignments, track student progress, and communicate with families. This kind of automation allows teachers to save time on administrative tasks and focus more on teaching and direct interaction with students.


In summary, examples of AI use in the classroom are numerous and continuously expanding. AI offers powerful tools to personalize learning, stimulate student engagement, and improve the efficiency of educational and administrative activities. However, the success of integrating AI in education always depends on the critical and conscious approach of teachers, who must guide students in the responsible use of these technologies and ensure that the focus always remains on human growth and learning.


Towards a Transdisciplinary Approach in Education

The introduction of AI in schools should be seen as an opportunity to rethink the entire educational approach. AI facilitates the development of a transdisciplinary approach, uniting different disciplines to address complex problems, such as environmental sustainability or resource management.


Transdisciplinarity represents a significant shift from traditional multidisciplinary and interdisciplinary approaches. With a transdisciplinary approach, the aim is to overcome barriers between disciplines and create a synthesis that allows students to tackle problems from different perspectives, recognizing connections between concepts that are usually treated separately. AI can facilitate this process by providing tools that integrate data, models, and methods from different disciplines in a harmonious way.


For instance, AI models used in climate analysis can be introduced in geography, science, and even economics classes, allowing students to explore the impact of climate change from multiple perspectives. Students can use real environmental data, model future scenarios, and evaluate possible solutions, thereby developing a deep and holistic understanding of global problems. This kind of approach promotes not only technical knowledge but also critical awareness of current and future challenges.


AI can also facilitate Project-Based Learning (PBL), which is a key component of the transdisciplinary approach. Students can be involved in complex projects that require the combination of mathematical, scientific, artistic, and design skills. For example, a project might involve building a model of a sustainable city, where AI is used to simulate resource management, optimize urban traffic, or predict the environmental impact of urban planning decisions. In this context, students learn to apply diverse knowledge in an integrated way and collaborate with their peers, developing problem-solving, leadership, and collaboration skills.


Another example involves using AI tools to analyze large datasets in social and human sciences. History students could collaborate with computer science students to analyze historical data through text mining and sentiment analysis techniques, discovering patterns and trends that would otherwise not be visible. This type of analysis not only deepens the understanding of historical phenomena but also helps appreciate the importance of data and algorithms in humanities research.


AI, therefore, becomes an enabling tool for addressing global and local issues holistically, developing an understanding that goes beyond the boundaries of individual disciplines. Transdisciplinarity, supported by AI, allows students to tackle the so-called "big questions" of humanity, such as sustainability, social equality, and technological innovation, helping them develop a systemic mindset and prepare for the complex and interconnected world of today and the future.


Moreover, a transdisciplinary approach enriches students' learning experience, allowing them to understand how the skills and knowledge acquired can be applied to real-world problems. This type of learning increases motivation and engagement, as students see a purpose in their school activities, recognizing the real impact of their work. AI, in this context, acts as a facilitator that enables students to explore complex scenarios, visualize outcomes, and simulate the consequences of different actions.


In conclusion, the adoption of a transdisciplinary approach in education, supported by AI, represents an opportunity to overcome the limitations of traditional teaching methods and prepare students to face the challenges of the 21st century. This perspective promotes collaboration, innovation, and critical understanding, forming aware and competent citizens capable of making a significant contribution to society.


Conclusion

The introduction of artificial intelligence in schools represents an educational paradigm shift that requires a radical rethinking of teaching and the very role of education. AI is not just a support tool but a catalyst for personalized learning, which can make education more inclusive and suited to individual needs. However, this transformation brings with it a series of implications and risks that require strategic management and a clear educational vision. AI, indeed, amplifies the ability to reach students in ways that traditionally would require resources impossible to implement on a large scale. But this personalization, while offering immediate advantages, requires a robust technological infrastructure, widespread digital skills, and a critical capacity to interpret and evaluate algorithms.


One of the most delicate points concerns data privacy and the risk of bias, which could affect equitable access to educational opportunities. In managing students' personal data, for example, there is a real risk that information could be used improperly or even commercially, requiring high ethical standards and a conscious digital governance. For AI to respect educational equity, its models must be transparent and continuously monitored to prevent existing social disparities from being replicated and amplified in educational environments. Without this oversight, schools risk losing the primary goal of education: providing equal opportunities and holistic development for every student.


In this context, the role of the teacher becomes even more strategic. With AI taking on part of the operational teaching load, teachers can redefine themselves as facilitators of critical and human skills—skills that cannot be replicated by AI, such as empathy, conflict resolution, and leadership. Their responsibility is also to ensure that AI is used in an ethical and conscious manner, transforming themselves from content deliverers to mentors who stimulate critical and autonomous learning. Teachers must therefore constantly update their skills, both technical and educational, becoming a conscious guide in a world of machine-mediated knowledge.


Moreover, the potential of AI manifests itself in an educational approach that goes beyond the limits of individual subjects, promoting a transdisciplinary vision. In this way, students are not only exposed to disciplinary knowledge but also acquire a systemic and multidimensional mindset. This vision not only prepares young generations to understand global complexity but also enables them to imagine innovative solutions for real problems, such as climate change or social equity. Transdisciplinarity enabled by AI opens up a new perspective, where technical knowledge intertwines with ethics and active citizenship, encouraging critical thinking and collaboration.


In summary, artificial intelligence in education brings enormous opportunities but requires prudent and humanly conscious management. The risk of dehumanized learning and technological dependence is real, but it can be countered by valuing the irreplaceable role of teachers and investing in education that develops not only technical skills but also social awareness and judgment capacity. AI, therefore, should not become a shortcut but a tool for enrichment that amplifies the human potential of attentive, equitable, and forward-looking education.


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