Abstract:

Artificial intelligence (AI) tools are rapidly becoming embedded in university learning environments, influencing not only academic practices but also the ways students approach knowledge production, information evaluation, and problem-solving. In this context, generative AI systems are increasingly used for tasks such as information retrieval, text generation, and academic support, creating new opportunities for learning but also raising concerns related to critical thinking, academic integrity, and responsible use of technology in higher education.

While many universities are currently developing institutional policies and guidelines regarding the use of AI in teaching and assessment, less attention has been devoted to the informal learning processes through which students develop practical competencies for interacting with these technologies. In many cases, students acquire AI-related skills through experimentation, peer interaction, and everyday academic practices rather than through structured instruction.

The aim of this study is twofold: to examine how university students develop artificial intelligence (AI) literacy through their everyday interactions with generative AI tools, and to identify the informal learning processes that shape these competencies. The research focuses on the concept of the hidden curriculum of AI, understood as the set of implicit practices, norms, and strategies that emerge as students integrate artificial intelligence into their academic work.

The study adopts an empirical research design combining quantitative and qualitative approaches. Data were collected through an online survey administered to university students enrolled in courses where AI tools are actively discussed or used as part of learning activities. The survey explores patterns of AI use, perceived benefits and risks, and students’ strategies for evaluating and integrating AI-generated outputs into academic tasks. In addition, qualitative responses provided by participants offer insights into how students learn to formulate prompts, verify information, and critically interpret algorithmically generated content. Participants include university students with learning experiences in different higher education contexts, particularly Spain, Chile, and Mexico, allowing the study to capture diverse perspectives on the integration of AI into academic practices.

Preliminary results suggest that AI literacy often develops through informal experimentation rather than through structured institutional guidance. Students progressively acquire tacit knowledge about how to collaborate with AI systems, including strategies for refining prompts, verifying sources, and integrating AI-generated content into academic work.

The findings highlight the importance of recognizing the hidden curriculum of AI within higher education. Understanding these informal learning processes can inform the design of pedagogical strategies, digital literacy initiatives, and institutional policies aimed at fostering responsible, critical, and transparent engagement with AI technologies in university learning environments.

Keywords:

Artificial intelligence, AI literacy, hidden curriculum, higher education, digital competencies.