The Application of Artificial Intelligence in Education and Training.

Introduction

Recently, we have witnessed a rapid and pervasive spread in every area of artificial intelligence (AI) or AI systems. Specific areas such as education and training are not exempt. The use of AI systems in the “educational” sphere constitutes a unique opportunity, but at the same time, it may conceal serious risks. The issue assumes such importance that International bodies have developed research, frameworks and standards identifying the benefits, effects, and risks of using AI systems for both teachers and students.

However, adopting AI also presents significant challenges, such as ethical issues, the risk of dependence on technology, and the need for new digital skills. This article explores the main applications of AI in education and training, highlighting its benefits, challenges, and prospects.

1. Personalization of Learning.

The use of AI systems in education allows teachers to modulate and adapt personalized programs while students can improve their knowledge with innovative learning tools.

Machine learning algorithms analyze student performance and adapt educational content in real-time, providing a tailored educational experience. This approach helps bridge the gap between students with different learning abilities, providing additional support to those who need it and more complex challenges to those who show more talent.

2. Virtual Tutors and AI Assistants.

Another significant innovation in education is the use of AI-based virtual tutors. These systems support students by answering their questions, explaining complex concepts, and providing personalized feedback. Examples include IBM Watson Tutor and AI assistants developed by some Big Techs.

Virtual tutors improve accessibility to education and reduce teachers’ workload, allowing them to focus on more complex aspects of teaching. In addition, they can be available 24/7, allowing students to receive assistance at any time.

3. Automation of Assessment and Feedback.

AI systems have long been developed to correct grammatical, style, or form errors in written texts and suggest the best solutions.

Some tools use AI to assess the quality of writing, detect plagiarism, and determine whether AI systems or humans wrote the content.

In addition, teachers can use AI to analyze student responses in open-ended tests, providing detailed and immediate feedback. That speeds up the assessment process and enables continuous learning improvement.

4. Large Language Models (LLMs) and their informed use.

Large Language Models are one of the earliest innovative frontiers that, leveraging neural network studies, have enabled the development of AI systems capable of analyzing vast amounts of text and answering user questions. One of the best-known models is GPT-4, which, like other advanced systems based on deep neural networks, has opened up new possibilities in education. LLMs can generate text, articulately answer questions, and provide personalized support to students, increasing virtual tutoring capabilities and enhancing instructional content creation.

However, promoting the conscious use of LLMs in education is critical. These tools, although powerful, have limitations, including the risk of generating incorrect or biased information, dependence on pre-existing data, and the potential to reflect biases inherent in training datasets. In fact, phenomena known as hallucinations and biases impose human and ethical oversight for the proper use of the output. For this reason, it’s necessary to train educators to:

• Critically evaluate the responses generated by LLMs, verifying the sources and reliability of the information.
• Use LLMs as supportive tools, rather than as substitutes for critical thinking and independent research.
• Sensitizing students to the ethics of AI, teaching them to recognize possible bias and develop a critical awareness of the use of these technologies.

By incorporating a conscious approach to using LLMs, education can benefit from their potential without incurring the risks of blind reliance on technology.

5. AI and Inclusion in Education

AI has the potential to make education more accessible to people with disabilities. Voice recognition systems, automatic captioning, and AI-based translation tools facilitate learning for students with hearing or language difficulties.

Some systems already help people with visual impairments interact with their surroundings through AI-generated audio descriptions. These tools are helping to make education more equitable and inclusive.

6. Legal Aspects and Privacy (hints).

The use of AI in education involves critical legal issues.

On the one hand, European legislation on artificial intelligence (rectus, artificial intelligence systems, because there is no normative definition of “artificial intelligence”) must be complied with. Europe has passed EU Regulation 2024/1689, better known as the AI Act, which is the world’s first risk-based law on AI regulating artificial intelligence systems and their use.

The AI Act will apply gradually. In fact, as of February 2, 2025, under Article 113 of EU Regulation 2024/1689, the following will apply:

• Chapter I (General Provisions):
  • Article 1 (Subject matter);
  • Article 2 (Scope).
  • Article 3 (Definitions)
  • Article 4 (AI literacy)
• The Chapter II (Prohibited AI Practices):
  • Article 5 (Prohibited AI practices).

In addition, Section 99(3) (Penalties) of the AI Act states: “Non-compliance with the prohibition of the AI practices referred to in Article 5 shall be subject to administrative fines of up to EUR 35 000 000 or, if the offender is an undertaking, up to 7 % of its total worldwide annual turnover for the preceding financial year, whichever is higher..”

On the other hand, European legislation on personal data protection, governed by the EU Regulation 2016/679 (GDPR), cannot be disregarded, which establishes precise rules for the processing of personal data to which the data controller and processor must adhere by the principle of accountability (accountability).

Educational and training institutions must ensure that applicable laws use data collected by AI systems.

Under Article 13(2)(f) of the GDPR, the controller or the processor should inform the data subject (e.g., the student) about how their personal data are processed and more specifically about “the existence of automated decision-making, including profiling, referred to in Article 22(1) and (4) and, at least in those cases, meaningful information about the logic involved, as well as the significance and the envisaged consequences of such processing for the data subject.”.

According to Article 22 of the GDPR, “The data subject shall have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly significantly affects him or her.”.

Therefore, AI systems must also be designed to minimize the risk of data protection regulation breaches by taking appropriate technical and organizational measures, including anonymization and encryption.

The topic is broad and deserves specific insights, so it is impossible to devote space here. In fact, judgments on the subject must be considered beyond the aforementioned regulatory framework. On the other hand, the so-called soft law, which consists of the documents published by the European Data Protection Board and the Data Protection Authorities in each state, should be deepened.

7. Importance of International Standards

Adopting international standards for using AI in education and training is crucial for ensuring the safety, reliability, and transparency of the technologies involved. Organizations such as UNESCO, OECD, and ISO have developed guidelines to assist educational systems in implementing AI ethically and responsibly.

Adhering to these standards allows for:

• Improved quality and safety of AI systems.
• Fair and transparent use of technology.
• A comprehensive framework for teacher training and data protection.

8. UNESCO: AI competency framework for teachers and for students

In 2024, UNESCO published two documents: “AI competency framework for teachers” and “AI competency framework for students”.

Here, we briefly focus on the “AI competency framework for teachers”, pointing out that the use of AI in education requires precisely a clear competency framework for teachers.

The “AI Competency Framework for Teachers” published by UNESCO, establishes 15 key competencies distributed in five dimensions:

1. human-centered mindset;
2. AI ethics;
3. foundations and applications of AI;
4. AI pedagogy;
5. AI for professional learning.

This framework helps teachers thoroughly understand AI and use it ethically and effectively in teaching.

The following main aspects emerge from this report.

A) Rationale for an AI competency framework
Artificial intelligence has profound implications for education, teaching, and teacher competencies. Its ability to process vast amounts of data, identify patterns, and generate content offers significant opportunities to improve learning processes. However, there are risks, including the loss of human autonomy, the risk of privacy violations, and the amplification of existing inequalities.
A competency framework is needed to address these challenges and help teachers ethically and effectively understand and manage the use of AI in the classroom.

B) Objectives and target audience
The AI CFT is intended for teachers who use AI to facilitate learning in core subjects, not for teachers who specialize in advanced AI teaching. The framework aims to support continuing professional development by providing guidelines for creating national and institutional AI training programs.
Specific goals include:

• Set standards for teachers’ AI competencies.
• Provide operational references for designing training courses.
• Create criteria for the assessment of teachers’ AI competencies.

C) Alignment with the UNESCO ICT competency framework for teachers.
The AI CFT is aligned with the 2018 UNESCO framework on information and communication technologies (ICT) for teachers. This alignment provides continuity in digital skills development, ensuring teachers can effectively use digital technologies and AI.
The framework is based on a common structure that integrates initial training, in-service training, and continuous learning, promoting a holistic approach.

D) Evolution of AI technologies and implications for teacher competencies.
As AI evolves, teachers’ roles are changing. They must become facilitators of learning, promoters of ethical practices in the use of AI, and models of continuous learning. The AI competency framework helps them navigate the opportunities and challenges of AI, ensuring that this technology is used inclusively and equitably.

The AI competency framework for teachers aims to ensure that the use of AI in education is effective, ethical, and human-centered. With proper training, teachers can harness AI’s potential to enhance learning without sacrificing the value of human interaction and traditional teaching.

9. Future Perspectives

The educational field is one of the new frontiers for developing and using AI systems based on increasingly advanced technologies.

Emerging trends include:

• Using conversational AI to improve interaction between students and educational systems.
• The implementation of blockchain ensures the security and traceability of educational data.
• The development of AI-based learning platforms that can deliver immersive and personalized experiences.

Conclusions

Integrating artificial intelligence in education and training is revolutionizing how we learn and teach.

A balanced approach between innovation and critical reflection will be critical to the future of AI-based education.

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