As part of the AI-CARE Educational Innovation Project, a pioneering training initiative has been carried out focused on posing geometric problems using Generative Artificial Intelligence (GenAI). This was a practical seminar implemented in the course “Didactics of Magnitudes and Geometry,” part of the Bachelor’s Degree in Primary Education at the University of Las Palmas de Gran Canaria (ULPGC). All students enrolled in the course (196 students) participated in this initiative, after providing informed consent for the use of their responses for research purposes.

The main objective of this initiative was to train future teachers in the strategic, critical, and reflective use of GenAI as an ally in the design of high-quality pedagogical learning situations. The session was led by researchers Eduardo Quevedo and Rubén Lijó (ULPGC), in collaboration with Josefa Perdomo-Díaz and Sara Embid (University of La Laguna), and Pilar Gómez and Salvador Angosto (University of Seville).

Seminar Structure: From Theoretical Rigor to Practice with GenAI

The seminar was designed using a hybrid methodological approach, combining in-person sessions and independent work. Particular emphasis was placed on posing open-ended problems, exploring the area-perimeter relationship, and critically evaluating GenAI models:

·         Justification of open-ended problems: Initially, students internalized the characteristics that define a “good” mathematical problem (curricular alignment, absence of errors, reasonable context, and a wealth of solutions). Work was conducted using the “low floor, high ceiling, and wide walls” problem-solving approach, ensuring the promotion of creativity, critical thinking, and inclusion in the classroom.

·         Exploration of the area-perimeter relationship: The mathematical core of the intervention focused on foundational knowledge regarding the exploration of the properties of plane figures. Participants were tasked with designing specific problems to conceptually address the relationship between area and perimeter.

·         Critical evaluation of large language models (LLMs): Using advanced comparison tools (such as ChatHub or LMArena dashboards), working pairs simultaneously evaluated the performance of four major language models. The students did not simply accept the AI’s responses; they analyzed the mathematical quality of the outputs based on the project’s five quality indicators, adjusted the prompts, and established an empirical ranking of educational utility.

As a final product, each team of students posed an original open-ended problem, specifying the level of AI assistance and the intellectual refinement process used to ensure pedagogical rigor.

 Dissemination of Results to the Scientific Community

Preliminary findings from this training and research initiative have already begun to be shared with the academic community and educators across the archipelago. Specifically, they were presented at the recent Interuniversity Meeting on Teacher Training and Research in Mathematics Education, a conference jointly organized by the Mathematics Education Areas of the University of La Laguna (ULL) and the University of Las Palmas de Gran Canaria (ULPGC), which took place on May 15 and 16, 2026. This presentation underscores the project’s commitment to knowledge transfer and leadership in the ethical and pedagogical integration of emerging technologies into teacher training.

We deeply appreciate the involvement of all students in the Bachelor’s Degree in Primary Education, whose critical thinking and professional skills demonstrate that the future of mathematics education is prepared to successfully navigate the era of artificial intelligence. We also thank the ForDiMat Research Project (PID2022-139007NB-I00) and the AI-CARE Educational Innovation Project (PIE-ERUA 2025-01), within which this work is carried out.

AN IMPLEMENTATION AT THE UNIVERSITY OF LAS PALMAS DE GRAN CANARIA

TEACHER: Patricia Arnaiz Castro (Department of Specific Didactics)

SUBJECT: Innovation in Teaching and Educational Research in English Language Teaching. Master’s degree in teacher training. 

DEGREE: University Master’s Degree in Teacher Training for Compulsory Secondary Education, Upper Secondary Education, Vocational Training and Language Teaching

NUMBER OF STUDENTS INVOLVED: 29

BRIEF DESCRIPTION OF ACTIVITY

The task focuses on designing a small-scale action research proposal based on a real classroom issue. Working in small groups of three, students analyse the problem, propose an intervention, and plan how to evaluate its impact. As part of the process, students are asked to choose and consult two AI tools and critically assess their suggestions. Their  final proposal should reflect their own professional judgement and the knowledge developed during the master’s degree.

First, students identify a specific pedagogical challenge they have observed or experienced in a Spanish secondary education classroom, either in compulsory lower secondary education (ESO) or upper secondary education (Bachillerato). Second, they  select two different AI tools of their choice. They then provide both tools with exactly the same context and four prompts focusing on:  why the problem occurs, a proposed action or intervention, a research question and the data collection or analysis procedure.

In the critical thinking stage of the task, students compare the output produced by each AI tool, choose the proposal they consider most suitable according to criteria such as theoretical grounding, clarity and feasibility, and identify limitations of both proposals. Finally, they develop their own action research proposal and reflect on the whole process.

RELATION WITH THE USE OF AI AND THE OBJECTIVES OF AI-CARE: This activity aligns with the AI-CARE project’s aim of building a community of learners and educators who approach artificial intelligence with critical awareness, ethical integrity and a sense of shared responsibility.

On 25–26 May, SWPS University in Warsaw, Poland, hosted a workshop, AI-CARE Interuniversity Workshop on AI-Enhanced Teaching, Ethics and Critical Thinking, organized within the framework of the AI-CARE project, with the participation of representatives from all four partner institutions. The workshop included expert-led training sessions focusing on strategically significant topics aligned with the project’s goals and activities. Particular emphasis was placed on:

• AI in higher education teaching conducted by Professor Dr Maciej Kościelniak, Dean’s Representative for Academic Innovation | SWPS University Poznań. 

• Ethics and AI conducted by Professor Dr Paulius Pakutinskas, Head of the LegalTech Centre, Mykolas Romeris University, the UNESCO Chair on AI, Emerging Technologies and Innovations for Society and Dr Benedetta Giovanola, Professor at the University of Macerata, UNESCO Chair Ethics of AI and Practical Wisdom.

In addition, several collaborative working sessions were conducted with representatives from the partner universities participating in the project consortium. These sessions addressed a range of key thematic and operational issues, including:

•             Implementing critical thinking through AI.

•             Analysis of the initial results from the proposed questionnaire.

•             Planning the development of open educational resources.

The workshop proved to be a highly productive experience, providing a valuable opportunity for in-person engagement and knowledge exchange among project coordinators from the partner universities. Such interactions contributed to strengthening interinstitutional collaboration and fostering closer cooperation within the consortium. During the event, the University of Las Palmas de Gran Canaria (ULPGC) presented several innovative teaching proposals to be developed and implemented within the AI-CARE framework during the forthcoming academic year.

We are pleased to announce the upcoming AI-CARE Interuniversity Workshop on AI-Enhanced Teaching, Ethics and Critical Thinking, hosted by SWPS University in Warsaw on May 25–26, 2026. This two-day event is a milestone for the AI-CARE (Artificial Intelligence for Critical Awareness, Responsibility, and Ethics) project, a collaborative initiative under the European Reform University Alliance (ERUA). The workshop brings together educators and researchers from across our partner institutions, including ULPGC, UniMC, MRU, NBU, and SWPS, to develop a human-centered approach to AI in higher education.

The preliminary program features intensive training sessions on integrating AI into teaching and peer-learning workshops focused on fostering critical thinking. Participants will also explore the ethical dimensions of AI and participate in dedicated working groups to refine survey results and co-create Open Educational Resources (OER) and pedagogical guidelines. These efforts are designed to equip both teachers and students with the necessary soft skills to navigate the complexities of AI-rich environments responsibly.

This workshop represents our commitment to fostering cross-institutional innovation and ethical reasoning in the age of digital transformation. We invite you to stay updated on our progress and explore our mission by visiting the official project website at: https://sites.google.com/view/ai-care-project/home.

The AI-CARE project —Artificial Intelligence for Critical Awareness, Responsibility, and Ethics through a Collaborative Approach— has completed its first phase of implementation within the ERUA alliance. This initial stage has focused on designing the project’s methodological foundations, strengthening coordination among partner universities, and preparing the ground for future pilot activities.

Since its official launch in October 2025, the project has brought together teams from the University of Las Palmas de Gran Canaria, Università di Macerata, Mykolas Romeris University, SWPS University and New Bulgarian University. During this first period, partners have worked on defining shared priorities, establishing communication routines, and aligning the project’s objectives across different institutional and disciplinary contexts.

One of the main outcomes of this phase has been the development of the AI-CARE Best Practices Survey, designed to collect teaching experiences related to artificial intelligence, ethics, critical awareness, and collaborative learning in higher education. The survey will help inform the project’s pedagogical framework and support the future development of Open Educational Resources, case studies, and teacher training materials.

The project has also promoted staff development through training activities on artificial intelligence, critical pedagogy and critical thinking. In addition, AI-CARE has begun to connect educational innovation with research, including doctoral work focused on the critical and ethical use of AI in language teaching and learning.

These first steps provide a solid basis for the next stages of the project, including pilot implementation, evaluation and broader dissemination activities.