The methodology of this course includes theoretical classes, analysis exercises and debates in the seminars and a practical part where the final group project will be developed which consists of the analysis and research of a current digital audience trend chosen by the stuents.

A detailed schedule outlining the content of each session will be presented on the first day of the course and will be available on the course’s Virtual Campus, where students will

find the various teaching materials deemed appropriate by the instructors and necessary information for effective course monitoring. Should the teaching modality change for reasons of force majeure according to the competent authorities, the teaching staff will inform students of any modifications to the course schedule and teaching methodologies.

Note: The course content will be sensitive to issues related to gender perspective and the use of inclusive language.

Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

The course includes the following assessment activities:

• Exam: 30% of the final grade.
• Seminars: 30% of the final grade.
• Group project: 40% of the final grade.

In order to pass the course, students must obtain a minimum grade of 5 out of 10 in the exam.

This course/module does not provide for a single-assessment system.

Students will be entitled to resit the course provided that they have been assessed on activities accounting for at least two-thirds of the total course grade.

Students will receive a grade of "Not Assessed" if they have neither submitted the seminar assignments nor sat the theoretical exam.

The seminars (30% of the final grade) are excluded from the resit process. The resit assessment will consist of an exam, the mark of which will be averaged with the seminar grade obtained in the first assessment period.

In this course, the use of Artificial Intelligence (AI) technologies is permitted as an integral part of the development of coursework, provided that the final result reflects a significant contribution by the student in terms of analysis and personal reflection. Students must clearly identify which parts have been generated using this technology, specify the tools used, and include a critical reflection on how these tools have influenced both the process and the final outcome of the activity. Failure to disclose the use of AI transparently will be considered a breach of academic integrity and may result in a penalty in the activity grade or more serious sanctions in severe cases.

Any irregularity committed in an assessment activity (academic fraud, plagiarism, or improper use of AI, unless such use is expressly authorised in the course guide) that may lead to a significant alteration of the assessment result will result in that activity being graded with a 0. If the course guide establishes obtaining a minimum mark in that assessment activity as an essential requirement for passing the course, or if several irregularities occur in the assessment activities of the same course, the final grade for the course will be 0. In addition, disciplinary proceedings may be initiated against any student involved in such irregularities.

Any student suspected of submitting work generated by AI, produced by other individuals, or copied from other sources; including AI-generated content without proper acknowledgement; or falling outside the permitted uses, may be required to provide draft versions or other materials demonstrating that the work is original and the result of their own authorship. Students may also be asked to explain or justify their work separately. Teaching staff may use AI-detection systems or carry out any verification procedures they consider appropriate. If irregularities are detected after review, the work may be graded with a zero and the student may be subject to additional disciplinary measures.