Acknowledgements: We would like to thank Álvaro Salinas, the Director of OPED, and Patricia Canales, its Pedagogical Coordinator, for providing us with information about the centre’s new AI curriculum. We also extend our gratitude to Daniel Canales from the Center for Teaching Development for sharing with us the main initiatives related to AI competencies at the university level.
1Since the early 1990s, Chile has implemented a policy to integrate digital technologies into education, ensuring that students have access to digital devices and the Internet. This policy has also supported digital skills development in the national curriculum and provided teacher training to incorporate these technologies into pedagogical practices (Claro and Jara, 2020). The rapid advancement of digital technologies introduces new, ongoing challenges, such as interaction with artificial intelligence (AI). Initial teacher training must address these changes, as it lays the foundation for educating future generations. AI requires educators to critically assess its implications on learning objectives, teaching methodologies, and evaluation strategies. In this paper, we present and analyse the case of the Observatory of Digital Educational Practices (OPED),1 a research centre within the Faculty of Education of the Universidad Católica de Chile,2 which aims to prepare future teachers to learn and teach in an increasingly digital society.
2Since 2018, OPED has implemented a training model that encompasses four key dimensions, integrated into course curricula through co-design and co-teaching sessions with faculty. These modules, delivered during 110-minute class blocks, aim to integrate digital resources and skills into teacher education while fostering reflection on how digital contexts challenge traditional content and learning goals. They also support the professional development of faculty.
3The four dimensions are:
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Personal and social development: focusing on critical reflection on digital issues and preparing teachers to address socio-emotional challenges in digital environments;
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Digital learning and creation: developing operational, informational, and creative skills while emphasising safe, ethical digital practices;
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Digital disciplinary skills: equipping teachers to use technology for subject-specific tasks, such as data modelling or digital tools to explain complex concepts;
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Active digital methodologies: encouraging the use of digital tools to create interactive and inclusive learning environments that foster student engagement and achievement.
4OPED currently offers 20 modules addressing these four dimensions. The aim is to ensure that teacher education students, throughout their academic journey, have opportunities to engage with the most relevant aspects of skill development and the use of digital resources for teaching and learning.
5Alongside this initial teacher training model, OPED also disseminates successful digital practices and systematises and conducts research into innovative educational experiences within digital contexts.3 AI has emerged as a new challenge for teacher education. To date, OPED has developed two modules: Learning assessment and AI, and Bibliographic analysis using AI. However, these modules do not yet form a sequentially organised training plan, nor do they address key aspects of the impact of AI on education.
6A new curriculum is currently under discussion in alignment with international trends, university policy, and national public policy guidelines. Within the University, the Center for Teaching Development (CDDoc, for its acronym in Spanish) has published a series of resources on AI in higher education. This centre is committed to strengthening the teaching skills of faculty members, enabling them to foster deep and meaningful learning experiences for all students. To this end, it provides training, educational consulting, and support for academic units, faculty, and teaching assistants in adopting innovative teaching methodologies.4 These resources have recently included recommendations for integrating AI into teaching, descriptions of relevant experiences, and useful tools for faculty members and students.5
7The aim of OPED’s new AI curriculum is to cover fundamental aspects of the impact and use of AI in education that every elementary and secondary school teacher should master, focusing on their technological–pedagogical knowledge (Koehler et al., 2013). In 2025, the curriculum will include the following modules:
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AI and Academic Integrity: addressing AI’s challenges to information production and promoting academic honesty. This module seeks to engage students in a discussion about the challenges AI poses to the production and use of information (e.g. in essays and research paper) and to provide guidelines for upholding academic integrity in schoolwork.
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The Curricular Challenges of AI: encouraging students to identify relevant knowledge for schools in the context of widespread AI use. More specifically, the aim is to discuss with students what relevant knowledge should be taught in schools within contexts of widespread AI use, analysing specific cases in which AI challenges and questions the current learning objectives and skills set out in the Chilean school curriculum.
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AI as an Academic Tutor: offering students opportunities to explore AI tools for learning enhancement. This module involves using and evaluating available AI tools to prepare, deepen, and/or resolve doubts before, during, or after a class.
8In addition, the existing modules will be restructured. For AI and Learning Assessment, the aim is to analyse the importance of students’ review and critical judgement regarding evaluative proposals generated by AI. For AI and Bibliographic Reviews, the aim is to increase opportunities for students to create basic structures for literature reviews with the help of AI, delving into key aspects through dialogue with AI.
9Systematic training in AI for education is expected to be implemented through three key approaches:
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Comprehensive coverage: the five modules collectively address two main aspects: (a) the opportunities and challenges that AI introduces in education, and (b) the dual role of the module participants, who are both current teacher education students and future primary and secondary school teachers. This dual role underscores the need for specialised training tailored specifically to teacher education students, distinct from that offered by CDDoc.
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Integrated curriculum: the modules will be incorporated throughout the teacher training programme, allowing students to engage with AI-related topics at multiple stages of their academic journey. The timing and placement of each module will align with the most relevant courses in the curriculum. Determining the optimal sequence for these modules will form part of the training design process.
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Sequential learning: the design of each module will build upon the knowledge and skills developed in previous modules, ensuring a cohesive, progressive learning experience.
10Finally, the responsibility for developing the modules will lie with the teachers of the courses in which they will be implemented, with guidance and oversight from the OPED team presenting this proposal.
11A key question is how current initiatives enhance teacher competencies to address the challenges that AI presents in education. Like previous technologies, AI has generated many promises, particularly in its potential to personalise learning and transform knowledge acquisition, compared to the Internet. While the Internet offers tools for accessing and sharing information, it relies on human decision-making for personalisation. In contrast, AI introduces active intelligence, enabling dynamic and adaptive learning experiences. However, as with earlier digital technologies, the effectiveness of AI hinges on its application, users, and context. Without appropriate skills and design, AI may reinforce passive learning and undermine educational competencies. Its benefits will only materialise through intentional use, effective guidance, and integration within a broader pedagogical framework. This necessitates the development of foundational skills in both students and teachers, the creation of higher-order tasks that promote critical engagement with AI, and the consideration of ethical issues in practice and policy.
12To evaluate the transformative potential of the modules developed by OPED, Puentedura’s SAMR model can serve as a useful framework. This model outlines four levels that describe the extent to which technology transforms the educational experience, categorised into two main groups: Enhancement and Transformation (see Figure 1).
Fig. 1. Puentedura’s SAMR model
Source: extracted from Puentedura (2013, p. 4)
13As outlined in Table 1, two modules have the potential to enhance (augment) existing educational practices (AI and Bibliographic Reviews, and AI and Academic Integrity), two focus on task redesign or modification (AI and Learning Assessment, and Curricular Challenges of AI), and one redefines learning by enabling the creation of previously unthinkable tasks (Redefinition). AI as an Academic Tutor introduces a new educational experience by providing personalised, real-time support.
Table 1. SAMR model for categorising OPED modules
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OPED modules
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SAMR level
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Explanation
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AI as an Academic Tutor
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Redefinition
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Transforms learning by enabling personalised, real-time support through AI tools like SIMBA, creating entirely new educational experiences.
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Transformation
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Curricular Challenges of AI
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Modification
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Modifies the curriculum by encouraging students to analyse how AI challenges current learning objectives and rethink relevant knowledge for schools.
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AI and Learning Assessment
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Modification
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Changes assessment practices by integrating AI, encouraging students to critically evaluate AI-generated evaluative proposals.
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AI and Bibliographic Reviews
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Augmentation
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Enhances traditional bibliographic review processes by allowing students to use AI to structure reviews and engage in deeper dialogue on sources.
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Enhancement
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AI and Academic Integrity
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Augmentation
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Enhances traditional discussions on academic honesty by incorporating AI’s challenges to information production, promoting critical thinking about ethical issues.
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14Although this analysis indicates that the AI modules OPED is starting to develop and implement have transformative potential for teaching and learning, it is also necessary to consider the institutional conditions required to sustain this training effort and prepare educators to harness the promise of AI.
15We will reference Unesco’s proposal for developing an AI competency framework for teachers, which outlines five institutional implementation strategies (Miao and Cukurova, 2024). Using this framework as a basis, we analysed the implementation strategies adopted at both the university and Faculty of Education levels (see Table 2).
Table 2. Strategies implemented at the university and Faculty of Education
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Suggested implementation strategies (Unesco, 2024)
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Chile case study
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Strategies implemented at the university and Faculty of Education
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Regulate AI and ensure trustworthy AI tools for education.
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✓
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At the university level, efforts focus on AI’s educational implications, fostering ethical dialogues on transparency, fairness, privacy, and responsibility. Inclusive practices accommodate diverse abilities, and a dedicated department ensures security. The goal is to integrate AI into classrooms with a critical, reflective approach, helping students and teachers understand its limitations and risks.
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Build enabling policies and conditions for the use of AI in education.
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✓
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The University’s AI policies aim to encourage teachers to use AI responsibly. For instance, the Framework for the Use of Artificial Intelligence in Teaching (Universidad Católica de Chile, 2024) establishes principles such as fostering critical thinking, promoting dialogue on AI-related skills, and ensuring transparent AI policies in courses. Additionally, the university provides AI training, offers funding to promote new educational practices, and recognises teachers’ innovative use of AI.
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Formulate and adopt local AI competency frameworks for teachers.
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✓
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At the OPED level, a new curriculum is currently under development to cover key aspects of the impact and use of AI in education that every elementary and secondary school teacher should master, addressing their technological–pedagogical knowledge.
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Design and streamline training and support programmes on AI competencies.
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✓
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OPED will implement systematic training in AI for teacher education through modules based on three key approaches: Comprehensive Coverage, an Integrated Curriculum, and Sequential Learning. In parallel, within the Uuiversity, CDDoc provides training, educational consulting, and support for academic units, faculty, and teaching assistants in adopting innovative teaching methodologies and resources on AI in higher education.
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Develop contextual performance-based assessment tools.
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-
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At the university level, a self-assessment tool for digital competencies for teachers is being developed (not yet implemented) to identify teachers’ strengths and areas for improvement in digital skills. This will link teachers’ training needs to the university’s educational offerings and promote professional development in the digital field. This tool includes some competencies related to AI use, but these remain at a very early stage.
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*
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16OPED stands out as a case of leadership in Chile through the implementation of a training model aimed at equipping future teachers with the competencies required to learn and teach in the digital era. This initiative, spearheaded by the Faculty of Education at UC, aligns with broader institutional strategies at the university level to foster digital competencies among educators and students. These efforts have laid a strong foundation for the initial development of a training programme focused on preparing future teachers to effectively teach and learn with AI. Key challenges include completing the curriculum to ensure comprehensive coverage of all transformative dimensions of AI in teaching and learning practices, integrating these competencies into the graduation profile, and developing an assessment tool to evaluate the AI-related skills of future teachers, considering their dual roles as learners and educators. Additionally, at the university level, it is essential to continue fostering an environment that promotes trustworthy AI tools for teaching and learning, while creating the conditions necessary to support effective AI practices in education.