The introduction of AI into education is a topic that both interests and concerns in equal measure. Its ability to process information rapidly and offer diverse solutions prompts reflection on how schools can adapt to new scenarios without losing the formative essence that stimulates independent thinking and creativity. Some schools have even started implementing AI-based solutions to address specific needs, design more flexible learning experiences, and support the teaching process. Nevertheless, we still do not know how this technology will impact the development of students’ independent reasoning skills.
In many institutions, the initial debate centred on blocking or restricting systems like ChatGPT, as it was feared that technological dependence would negatively affect reasoning and academic honesty. Concerns about cheating in assessments and the potential decline in the quality of learning soon followed. Over time, these positions have gradually shifted, pointing towards a strategic use of AI to reshape teaching methodology (Bieser, 2022). In this regard, Rodrigo Fábrega, a prominent specialist in education, technology, and creativity, and an associate researcher at the MIT Media Lab, underscores the importance of applying AI pedagogically, with the aim of strengthening critical thinking and the ability to link ideas, rather than relegating them to mere reception of information (Fábrega, 2024).
According to this approach, the primary virtue of AI would not be limited to its speed in processing vast amounts of data. It would also include the contribution AI can make, for example, by establishing novel associations or stimulating curiosity in the educational process. In this article, we will see how this creative potential can be realised to enrich education with the help of AI, without losing sight of the precautions we must take to maintain what truly matters: the human spark that ignites creativity.
AI as the New Modelling Clay of Education
Fábrega uses a very graphic metaphor to describe the role AI can play as a trigger for creativity in education: who doesn’t remember playing with modelling clay as a child? This simple material allows for the creation of an infinite variety of shapes, figures, and structures. Its value lies in the hands of the one who moulds it: a raw tool that takes shape depending on the intention, skill, and imagination of the user. Similarly, AI offers a powerful technological base capable of analysing vast amounts of data, generating patterns, and proposing solutions. However, it is the direction set by teachers and students that determines whether it becomes a resource to enhance creativity or a mere automated response mechanism.
When AI is conceived as “modelling clay”, its capacity to adapt to different contexts and learning styles is acknowledged. Rather than imposing a uniform methodology, AI can be personalised to meet the specific needs of each student, whether by proposing alternative routes to solve mathematical problems, suggesting creative strategies for writing texts, or facilitating the design of interdisciplinary projects. This adaptability is crucial for fostering inclusive educational environments where each student has the opportunity to explore and express their creativity without feeling limited by a single way of learning.
This scenario demonstrates that the so-called “technological modelling clay” is not limited to repetitive tasks or process automation. It also enables the creation of learning environments where technology acts as a bridge between imagination and practice.
AI offers a powerful technological base capable of analysing vast amounts of data, generating patterns, and proposing solutions. However, it is the direction set by teachers and students that determines whether it becomes a resource to enhance creativity or a mere automated response mechanism.
Three Approaches to Integrating AI into Creative Education
Various proposals agree on the need to balance the speed offered by AI with thoughtful reflection and in-depth exploration (Fábrega, 2024). Below are three lines of work that have proven effective in training students with a critical and creative mindset.
Speed: Automation Oriented Towards Innovation
The most visible characteristic of AI is the automation of tasks that previously required a considerable amount of time and effort. Among these are the correction of exercises, the generation of reports, or the selection of personalised content (Fábrega, 2024). At the K-12 level, teachers across various subjects have incorporated ChatGPT to produce study guides, reading summaries, and diagnostic quizzes (Fernández, 2023). This practice can lead to a positive scenario, as the school community receives immediate answers to specific doubts, freeing up valuable time for interactive, creativity-focused teaching.
However, the use of AI should not replace the essential task of consciously understanding and analysing information. If students become accustomed to receiving only automatic solutions, they may adopt superficial study habits. Therefore, it is advisable for teachers to combine AI assistance with reflective activities, where students explain the reasoning behind the solutions, compare alternative approaches, or justify the mathematical and scientific procedures underlying the machine’s suggestions.
Slowness: Reflection and Critical Thinking
The immediacy offered by current technologies is not always beneficial to the learning process. In this regard, Fábrega suggests promoting “slowness” in the classroom, understood as the practice of pausing to evaluate the quality and relevance of automatically generated answers. For example, there have been instances where the teacher deliberately programmes complex or paradoxical questions in ChatGPT, and then the students analyse the resulting arguments to detect inconsistencies, biases, or relevant omissions.
This exercise fosters the ability to question and debate, while also reinforcing the importance of data verification and the reliability of sources. Thus, AI is no longer seen as an infallible entity, but rather as a tool that stimulates the confrontation of perspectives and the search for empirical evidence. The act of verifying information across multiple sources or contrasting the algorithm’s output with reality encourages the development of more nuanced and robust positions.
Depth: Experimentation and Long-Term Projects
The third approach focuses on creating educational environments that promote the role of students as developers, not merely as passive users (Fábrega, 2024). In K-12 education, this form of AI integration could involve programming machine learning models in interdisciplinary projects. For example, creating a classifier for poetic texts, where the goal is to recognise literary styles, rhythmic patterns, or themes, and reflect on AI’s limitations when dealing with metaphorical language.
Following Seymour Papert’s ideas, these experiences turn error into a substantial part of the learning process. By training and adjusting the model, students internalise the idea that an imprecise result is not a failure but a starting point for refining the strategy. In this way, AI becomes a research tool that enriches the ability to formulate hypotheses and test them with concrete data.
Risks and Ethical Challenges: AI as a Source of Complexity
AI presents remarkable possibilities, but it also brings challenges that should not be overlooked. One of the main concerns is the tendency of some students to assume the role of passive recipients, expecting answers without questioning them or exploring beyond what is provided. This can lead to a decrease in independent reasoning abilities and an over-reliance on algorithmic outputs, which in some cases may be biased.
Moreover, several researchers have warned about the opacity of some AI systems, making it difficult to accurately assess the origin and quality of information (Bieser, 2022). This lack of transparency can lead to inequity and perpetuate cultural stereotypes, especially when training data does not reflect the diversity of educational contexts. Therefore, a framework is needed to guide the application of AI and safeguard data integrity, privacy, and the equity of education.
Another thorny issue concerns the objectives of technology providers, as there is sometimes a commercial interest that influences access to upgraded versions of the tools. As a result, the gap between well-resourced schools and those with financial limitations may widen, deepening existing inequalities (Bieser, 2022).
Recommendations for Promoting Creativity Through AI
To ensure AI contributes to the creation of creative environments in education, Fábrega suggests several actions to be implemented collaboratively by school administrators, teachers, and regulatory bodies:
- Ongoing Teacher Training. Continuous training in the technical and ethical foundations of AI allows teachers to understand its limitations and advantages. This includes addressing issues such as algorithmic biases, data collection, and scientific validation methods.
- Collaborative Projects Between Disciplines. Several studies suggest integrating AI into initiatives that involve subjects from the sciences, humanities, and arts (Bieser, 2022). A K-12 example could be analysing literary patterns in a corpus of texts from different eras. This type of experience fosters the connection between digital skills and cultural interpretation.
- Promoting Critical Thinking. The analysis of AI-generated outputs should include source verification, evaluation of assumptions, and comparison with alternative perspectives (Fernández, 2023). This process turns the classroom into a space where academic dialogue and rigorous argumentation are regular practices.
- Transparency and Data Protection Regulations. Competent authorities must establish guidelines to ensure oversight of the algorithms used in school contexts. The goal is to protect students’ identity and wellbeing while promoting equitable access to technological resources (Bieser, 2022).
- Emphasis on Autonomy and Creativity. AI should be seen as a means of expanding perspectives, not as a tool that unambiguously dictates answers. The challenge is to design exercises that allow students to generate their own proposals, challenge AI’s suggestions, and offer original solutions using available technology.
References
Bieser, J. (2022). Creative through AI. How Artificial Intelligence Can Support the Development of New Ideas. GDI. Economic and Social Studies.
Fábrega, R. (2024). La Inteligencia Artificial como una oportunidad para cultivar el pensamiento creativo en la escuela. Medellín 189. Vol. L. Julio-diciembre (2024), pp. 309-323.
Fernández, M. (May, 2023). Inteligencia artificial en las escuelas: del miedo inicial a las ideas innovadoras de hoy. El Mercurio innovación.
