The LAMB Project and open source in education

Illustration by Marta Forment

License Creative Commons

Antoni Hernández-Fernández

For years, secondary school technology teachers have sought to teach programming, foster an understanding of information systems, and develop their students’ critical and computational thinking. Yet they have often had to rely on tools that function as black boxes. The paradox is difficult to ignore: we aim to cultivate critically minded citizens with strong digital competences, while remaining dependent on platforms we cannot audit, modify or fully explain—largely because they are protected by corporate patents and embedded in business models that thrive on opacity. If the goal is to understand technology, what sense does it make to do so through closed infrastructures whose inner workings remain concealed?

In the current context of artificial intelligence (AI), this contradiction has only intensified—indeed, AI has made it more visible. Increasingly, teachers are incorporating assistants and chatbots into the classroom, often through the uncritical use of commercial tools, thereby implicitly outsourcing pedagogical decisions to the companies that design them. The risk is not merely technical but educational: the uncritical acceptance of learning models, training biases and limitations that, in most cases, have not been designed for our specific context or our educational aims.

Against this backdrop, initiatives such as LAMB (Learning Assistants Manager and Builder) are particularly welcome. LAMB (Alier et al., 2025) is an open-source platform that enables teachers and institutions to create learning assistants based on language models, trained on their own materials (notes, textbooks, videos, and so forth), and integrated directly into widely used environments such as Moodle. In this way, the AI assistant becomes a pedagogical resource aligned with the curriculum and guided by teachers’ professional judgement. LAMB makes it possible to design subject-specific tutors, ensuring that AI-generated responses remain within the scope of the course. Its modular architecture facilitates integration into existing systems while reducing dependence on external commercial tools.

What matters most about LAMB, however, is not simply what it does, but how it does it. As an open-source tool, it restores control to teachers and educational institutions: they can decide which models to use, how data are handled, and how AI assistants are tailored to the needs of the classroom. This is especially important in secondary education, where technology must not only be effective but also formative in itself, in line with professional codes of ethics (Hernández-Fernández, 2025), techno-ethical principles (Bunge, 1974; Steels & López de Màntaras, 2018), and international frameworks for the safe and responsible use of AI (Alier et al., 2024; UNESCO, 2022). Working with open tools is therefore not merely a technical decision, but a pedagogical opportunity to show how technology actually works. It is also, if one may say so, a way of restoring the professional standing of technology teachers, who have often been marginalised within the curriculum and reduced, in many schools, to little more than IT maintenance staff. ICT coordinators, in particular, deserve far greater recognition—both in terms of remuneration and allocated time—given the centrality of their role in the present context.

In programming education, this issue becomes even more pressing. Code assistants can be powerful allies, but they can also serve as opaque shortcuts for students. Open solutions allow teachers not only to discourage unreflective use, but also to analyse, adapt and critically integrate these tools into the learning process—keeping, as the familiar phrase has it, the human in the loop. This is, ultimately, a matter of pedagogical coherence: teaching technology from the inside, rather than merely skimming its surface.

Ultimately, projects such as LAMB point towards a necessary shift in the age of AI: from producing passive users of technology in schools to cultivating active agents—citizens capable of critically engaging with both its construction and its use. For secondary school technology teachers, and for those working in vocational education and training in technical fields, this is neither a luxury nor an ideological stance, but a natural extension of their discipline. If teaching technology means understanding it, then open source ceases to be optional and becomes an essential component of pre-university education.

References:

Alier, M., Pereira, J., García-Peñalvo, F. J., Casañ, M. J., & Cabré, J. (2025). LAMB: An open-source software framework to create artificial intelligence assistants deployed and integrated into learning management systems. Computer Standards & Interfaces, 92. DOI: 10.1016/j.csi.2024.103940.

Alier, M., García-Peñalvo, F., Casañ, M. J., Pereira, J. A., & Llorens, F. (2024, October 8). Safe AI in Education Manifesto (Version 0.4.0). Safe AI in Education Manifesto. https://manifesto.safeaieducation.org

Bunge, M. (1974). Por una tecnoética. En: Bunge, M. (2013). Pseudociencia e ideologia. Pamplona: Laetoli.

Hernández-Fernández, A. (2025). Tecnologia, tecnoètica i codi deontològic docent. Revista de tecnologia, 13, p. 56-59. DOI: 10.2436/20.2004.01.69. https://hdl.handle.net/2117/442517

Steels, L., & Lopez de Mantaras, R. (2018). The Barcelona declaration for the proper development and usage of artificial intelligence in Europe. AI Communications. SAGE Publications. http://doi.org/10.3233/aic-180607

UNESCO (2022): Recommendation on the Ethics of Artificial Intelligence.  https://unesdoc.unesco.org/ark:/48223/pf0000381137

LAMB WEB (with materials, tutorials, links…): https://lamb-project.org/

Source: educational EVIDENCE

Rights: Creative Commons