The Silent Revolution in Learning
A powerful wind of change blowing now also in the classrooms, colleges and universities are reshaping not only the physical space but, above all, the way in which teachers and students interact with knowledge. This silent revolution is triggered by the artificial intelligence (AI), a technology that, with its unstoppable advance, is questioning paradigms consolidated and opening the way to a new horizon educational. And the parallelism with the advent of the printing press, the innovation that centuries ago scardinò access elitist knowledge, democratizzando education, and widening the boundaries, is not hazardous. Indeed, AI promises to do the same, if not more: personalize learning, and make it more accessible and engaging, prepare the new generations for the challenges of a world increasingly shaped by automation. Of course, this transformation of the epoch-making is not exempt from shadow areas, from ethical dilemmas and educational complex that require thoughtful answers, and far-sighted.
Tutor: Learning Cropped tailored
The image of the teacher, surrounded by students, each with its own peculiarities, their talents and their own pace of learning, is an ideal that has shaped the imaginary school for centuries. But the concrete reality of the traditional classrooms, often with large classes and uniform methods, has often struggled to translate it into practice.
In this scenario, the artificial intelligence comes with a promise that he knows of the revolution: that of creating a virtual classroom cropped tailored to each individual learner, in which the knowledge is to bow meekly to the needs of the individual, and in which the learning becomes an experience truly immersive and personalized.
And at the heart of this vision is the figure of the “virtual tutor” based on the IA, an intelligent assistant that is capable of supporting the student in his formative years, offering a tutorial individualized, timely, and effective. These sophisticated systems, powered by advanced algorithms, they are able to analyze in real time to a host of data regarding performance and behavior of the learner: what topics can easily understand, what ideas will create difficulties, how much time he dedicates to the study, the way in which it interacts with the material, what are its strengths and weaknesses, and even which emotions test during the learning process.
Through this rich amount of information, the AI is able to draw a profile of learning, detailed and dynamic, adapting a result, the educational path. The result is an educational experience highly personalized, in which the virtual tutor can propose targeted exercises to consolidate the acquired knowledge, suggest additional resources and study material to overcome the difficulties, to modulate the level of difficulty of the activities depending on the speed of learning, and provide constant feedback and constructive, tailored to the specific needs of the student. In this way, the student never feels abandoned to itself, but feels the presence of a mentor virtual guide, supports him and encourages him to overcome their own limits.
A concrete example is represented by the platforms of online learning using AI to personalize the courses of mathematics, foreign languages, or programming. The system, after evaluating the skills initials of the student through an entrance test targeted, and an analysis of his previous training, build a learning path, dynamic, and constantly adapts to its responses, with all its errors and its progress. If a student appears to have difficulty with the equations, for example, the virtual tutor offer extra exercise, alternative explanations, interactive visualizations, and analogies with concrete situations, offering him a reinforcement targeted. On the contrary, a student who demonstrates a quick understanding of the material will speed up the pace, tackle advanced problems, explore topics, and extra to participate in stimulating challenges, thus maintaining its high level of motivation and active involvement.
But the transformative potential of AI in education is not limited to the simple customization of the path. These technologies also promise to enrich the educational experience, making it more interactive and engaging for students of all ages and skill levels. Some tutor virtual, for example, integrate the techniques of gamification, transforming the exercises in fun challenges, awarding points for correct answers, rewarding the progress of the student with a badge for virtual and placing it in the rankings, in order to increase his motivation and his active involvement. Altri, più avanzati, ricorrono alla realtà aumentata, permettendo agli studenti di esplorare concetti astratti in modo immersivo e tridimensionale, magari “visitando” virtualmente l’antica Roma per studiarne la storia, o manipolando modelli 3D di molecole per comprenderne la struttura chimica.
Of course, it is important to underline the fact that the AI cannot, and should not, replace the human teacher. The ability to inspire, motivate, create a stimulating learning environment, understand the nuances of interpersonal relationships, manage group dynamics and to guide students in their personal and social growth remains skills only human, irreplaceable by any machine. The future of education, therefore, should be a synergy between the artificial intelligence and empathy, the experience and the passion of the teacher, a union that promises to redefine the boundaries of learning, elevating it to a higher level of efficiency and humanity. In this new era, the teacher must necessarily acquire new skills, learning to interpret the data provided by the IA, to further customize the learning path according to the specific needs of each student and to manage the social interactions within the class, thus becoming a real “orchestrator” of the educational process.
For the Evaluation: A more Objective?
In addition to reshape the traditional teaching methods, the artificial intelligence (AI) is entering forcefully, even in the delicate field of evaluation, raising a debate and interesting about how to measure the competences and learning outcomes in a more efficient, accurate, and possibly the lens. Algorithms, AI can automate and streamline various stages of the evaluation process, freeing teachers from repetitive tasks and time-consuming, and allowing them to devote more energy to direct interaction with the students, the instructional design and the enrichment of the learning experience in general.
Consider, for example, the automatic correction of homework, exams and essays. Sophisticated Software, powered by natural language processing (NLG), and machine learning techniques, are able to analyze the texts of the students, by assigning scores based on predefined criteria, and identifying areas of strength and weakness. These systems can provide immediate feedback to the students, highlighting the errors in grammar, syntax, spelling, structure of argument and understanding of the concepts, thus helping them to internalize their mistakes and improve their performance.
But the AI doesn't stop at a simple mechanical correction. Advanced algorithms can also analyze the students ' responses in more detail, evaluating the quality of argumentation, the clarity of the exposition, the ability to make use of the sources, the originality of the ideas and even the expressive creativity. Some systems of IA, for example, can even detect cases of plagiarism, by comparing the text of the student with an extensive database of educational materials, articles, and publications.
Another area where AI can play an important role is that of a formative assessment, or evaluation which accompanies the learning process, providing continuous feedback to the students and allowing them to monitor their progress. Systems, AI can collect and analyze data on the activities of students in the learning platforms online, tracing their paths of study, their interaction with the learning materials, their performance in the quizzes and tests, and providing them with feedback, personalized, and timely. Thanks to this continuous analysis, students can identify their own strengths and weaknesses, adapt your own study strategies and improving their effectiveness.
An interesting application of AI in the field of education is the creation of custom reports that can provide teachers with a clear and detailed picture of the level of learning of each student. These reports can highlight what students have achieved the learning objectives, which need more support and which have difficulty in specific topics. The teacher, supported by these data, can intervene in a targeted and timely manner, providing a personalised help and optimizing the effectiveness of the work.
