The ten challenges of artificial intelligence in teaching


Artificial intelligence (AI) is a branch of computer science. It combines algorithms and data that allow machines to learn and perform complex tasks. It imitates, to a certain extent, the functioning of human intelligence.

After successive waves of development and expansion, AI is now experiencing a new spring. It will continue to develop and impact our lives.

In education, its main areas are: neural networks , deep learning , reinforcement learning and machine learning . TheGenerative AI or LLM ( Large Language Models ), virtual machines based on natural language with the capacity to generate content (text, images, videos), such as chatbots , are driving the debate about their use.

Pedagogical and ethical implications

The debate is focused on digital literacy and its pedagogical and ethical implications: the creation of respectful environments, the stimulation of flexible learning, the existence of accessible resources and the promotion of positive attitudes . The focus is on how AI can contribute to successful education for all. To guide this process, there is a global proposal called the Beijing Consensus (UNESCO, 2019).

Regarding this, there are five essential aspects:

  1. Political : Is AI a political priority? Does it favor a better education?
  2. Social : Does it contribute to the social function of education?
  3. Pedagogical : Does it offer opportunities to improve education ? What limits does it have? How can it be integrated with a formative sense? Can it promote personalization of learning? Does it improve teaching competence?
  4. Ethical : Does it contribute to the common good? Is it safe? What ethical challenges does its integration in education pose ? Can responsible and ethical use be ensured? Is it possible to build ethical AI?
  5. Emotional : How does it affect emotional education? Does it have emotional effects on the student body? Can we talk about an emotional AI?

Ten challenges

The ten challenges within the current educational debate for educational artificial intelligence (IAE) are the following:

  1. Serve as educational support, and improve teaching and learning both in administrative aspects and in educational tasks.
  2. Contribute to reflective teaching and pedagogical coherence. By transforming the teaching role and automating some tasks, you will leave more time for personalized treatment. Reflection on practice will be enhanced. Greater use can be made of proposals such as collaborative international online learning ( COIL ) or challenge-based learning .
  3. Achieve critical and creative learning. Identify lies and hoaxes; analyze information and its sources; and considering different perspectives to form informed opinions will be the skills to be developed. This will encourage imagination and originality for creative thinking.
  4. Integration and gender perspective. It could be used to combat discrimination and gender bias through the analysis of images or texts. However, there is a prior task pending: reduce the digital divide and avoid gender bias in AI applications.
  5. For and with everyone –educational equity–. AI can offer opportunities and tailored responses to all students, enhance universal accessibility, the removal of barriers and participation in learning.
  6. The promotion of transversal skills – oral communicative, investigative, reflective, emotional and ethical – becomes even more essential to contribute to the formation of a citizenry committed to current environmental, social and economic challenges. And to promote decision making.
  7. Permanent training of teachers. The redefinition of access, use and security within the framework of digital skills. Training should promote conscious use and improvement, aligned with the learning outcomes.
  8. Communication, training and participation of families. Promote new forms of collaboration and participation of families in education.
  9. The promotion of ethical learning; avoid dishonest behavior such as plagiarism or false attribution of authorship, and use with intention to harm.
  10. Formative and shared evaluation. The evaluation can be guided with a lot of data, in a valid and reliable way. In this way, it makes students more aware of what and how they learn.

Flexibility and openness

Reflecting on the challenges posed by the use of IAE is key and has repercussions in three areas:

  1. The creation of meaningful learning environments and situations that transcend the limits of the classroom, valuing the students’ previous knowledge and providing support to explore new knowledge.
  2. The connection with educational and professional guidance that promotes learning throughout life.
  3. The promotion of its formative use with a critical and ethical sense: the IAE is an aid to review how we are doing it, contributing to change what we do not like.

The IAE can be an opportunity to advance necessary pedagogical changes and improvements, in the sense that education offers relevant and meaningful learning for students throughout life for the 21st century.

Risks and caution

Many voices warn of the risks of AI in the fields of privacy and security. It is a technology that makes us vulnerable to deception and manipulation, even emotional. Especially in the case of the student body, who might not have enough control over the situation.

In a framework of profound digital transformation, we must keep in mind the “Know thyself” of the Temple of Apollo in Delphi. Nothing new under the sun, some people say. The truth is that these challenges show an extraordinary transformation in the teaching process, but above all in the learning process. It is time to be prudent and aware of the importance of building an IAE.

Author Bio: José Sánchez Santamaría is a Full Professor of Educational Equity at the University of Castilla-La Mancha