The teaching-learning of automated journalism in public institutions: Studies, feasibility proposals and future impact of artificial intelligence

María José Ufarte Ruiz, César Fieiras-Ceide, Miguel Túñez-López

Abstract

The use of artificial intelligence (AI) in newsmaking is a thriving practice that requires the adaptation of journalism curricula. The objective of this research is to identify, from an exploratory perspective, training courses on content automation in bachelors’ and master’s degree programs in journalism and communication at Spanish public universities. A total of 768 courses from 17 bachelor degree programs and 116 courses from 8 master’s degree programs are analyzed. Opinions of experts in AI were also collected regarding how the application of AI in teaching will change the relationship with university students, especially in communication programs. The results reveal that the Spanish educational offering in AI is insufficient, as there are very few specific proposals for the total or partial study of the transformations of journalistic roles, routines and conventions. This is especially important in a context in which this emerging technology will cause a “transformative revolution” by allowing ultra-personalized teaching with tools for anticipating and identifying teaching/learning problems, paces, preferences and deficiencies in both face-to-face and online teaching environments.

Keywords

automation; journalism; bachelor; master; study programs, machine learning

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