AI and Big Data in Journalism Education: Spain’s Gap

What is it?

This study evaluates how journalism education in Spain incorporates artificial intelligence (AI) and big data into university curricula. These emerging fields are redefining how journalists report, verify, and disseminate information.

Why is it important?

According to the research of Tejedor, Cervi, Romero-Rodríguez, and Vick, despite AI transforming journalism practices, only 7 Spanish universities offer full courses on data journalism and just 19 partially address AI or big data in broader subjects. This article explains the mismatch between industry needs and academic training.

Key Findings from the Study

Methodology

• Analyzed 41 journalism degrees across Spanish universities (1775 courses total).

• Identified courses explicitly or implicitly addressing AI, big data, or automation.

• Categorized approaches as critical, applied, or hybrid (theoretical and practical).

Results at a Glance

• Only 7 courses explicitly focus on data journalism or big data.

• 19 additional courses include AI/big data as partial themes.

• Just 5 courses offer hands-on applied training.

• 13 courses take a critical perspective (ethics, theory).

• 8 courses combine critical and applied approaches.

Journalism Education: Critical vs Applied

Critical Approach

These courses focus on ethical, social, and philosophical implications of AI. They encourage students to question the use of automation and algorithms, promoting media literacy and algorithmic accountability.

Example: “Digital Formats and Documentation” at Pompeu Fabra University examines AI’s media impact, not just its tools.

Applied Approach

These courses teach technical skills: data visualization, API use, programming, content creation with AI, etc. Yet, very few institutions focus on this type of training.

Example: “Creativity and Innovation” at UIC teaches AI-generated content, including chatbots, audio, and image synthesis.

Curriculum Weaknesses and Recommendations

What’s missing?

• No exclusive courses on AI in journalism.

• Topics are fragmented across electives and general tech courses.

• Low emphasis on hands-on tools like NLP, bots, or AI-driven fact-checking.

• Limited collaboration between communication and computer science departments.

What should change?

This article explains that journalism schools must:

• Create dedicated AI and big data modules.

• Integrate applied training with critical reflection.

• Foster interdisciplinary programs combining tech, ethics, and media.

FAQs

Do Spanish journalism students learn AI?
Very minimally. Only 7 full courses directly address data journalism or big data, and just 5 offer applied training with AI tools.

Why is this a problem?
Without AI skills, future journalists won’t meet evolving media industry needs, such as automation, fact-checking, and audience analytics.

How can universities fix it?
By revising curricula to include mandatory, specialized training in AI and big data alongside critical education on ethical implications.

Final Thoughts

The main findings indicate that Spanish journalism education is not keeping pace with technological disruption. A balanced curriculum—combining critical analysis and practical skills—is vital for preparing ethical, competent journalists. Future work should foster collaboration across disciplines to ensure students are not just tech users, but thoughtful innovators in digital media.