Learning with Artificial Intelligence at the higher level. The case of Distant Reading

Abstract

Worldwide, generative AI tools have significantly changed the assumptions of higher education. This article questions the idea that the ability to face the challenges that AI presents to higher education can be solved only with teacher training in AI literacy. Our hypothesis is that in addition to teaching AI literacy to teachers, it is necessary to review the curriculum. A task that each teacher can only do with their own subject. This theoretical reflection based on research into the foundations of digital humanities pedagogy, from a socio-material pedagogical framework, explores the case of Distant Reading. In this way, from a corpus of texts, it is possible to carry out data visualizations such as word clouds and analysis of knowledge networks and plots, among other things. This generates new frameworks for interpreting literature, but also amplifies reading skills in various fields of the social sciences and engineering. The results indicate that the generative AI tools available for Distant Reading provide one of the best trajectories for carrying out the work of curriculum review. Therefore, the proposed socio-material pedagogical framework of AI provides an educational praxis that does not abandon the critical perspective and serves as a model for other intellectual practices to be reviewed for the changes caused by AI in cognitive processes. Higher education institutions must develop AI policies and good institutional practices not only to guarantee ethics, transparency, responsibility and inclusion but also to balance the incorporation of AI in learning with the teaching of a critical perspective in the post-digital world.