The course is based on lectures, which will be accompanied by interactive activities and other educational tasks. Field trips to museums, exhibitions, or workshops will also be carried out to deepen technical knowledge about the history of art.

Theoretical classes
Presentation of the fundamental theoretical contents of the subject by the professor using audiovisual materials and with references to the bibliography.

Fieldwork (PCAM) and assignment
Three mandatory field trips to museums or institutions linked to artistic production and heritage conservation will take place during December and January. The schedule for the trips will be from 10:00 am to 2:30 pm. On the first day of class, details about the assignment will be provided.

In-class activities
A set of activities, methodologies, and interactions carried out during in-person sessions with the aim of facilitating active learning, student participation, and content comprehension. These activities will always take place in the classroom and may include debates, reading and analysis of texts, case study analysis, group work, presentations, guided exercises, or other strategies that promote a critical and participatory attitude.

Follow-up tutorials
Their purpose is to monitor student progress, guide possible interests, and also address any questions or needs regarding individual work or study follow-up for the subject. Students must email the professor in advance to schedule a tutorial.

Complementary activities
Attendance is recommended, whenever possible, to other exhibitions and lectures related to the course and recommended by the professor.

This course does not have a single final evaluation system. Continuous assessment consists of four parts:

• Partial exam 1: 35% of the final grade.
• Partial exam 2: 35% of the final grade.
• Fieldwork assignment (PCAM), which accounts for 20%.
• In-class activities and assignments posted on the \"Campus Virtual\": attendance and active participation in classroom activities will be evaluated, as well as the completion of tasks posted on the Campus Virtual to ensure good monitoring of the subject (10% of the final grade).

To pass the course, it is mandatory to have taken both partial exams (exam 1 and 2), submitted the PCAM assignment, attended the three field trips, and participated in at least half of the in-class activities. Class attendance, participation in all activities, and submission of all tasks posted on the Campus Virtual may help to raise the final grade if appropriate.

Only students who have failed but met the following conditions will be eligible for resit exams—on the date set by the Faculty’s Academic Management: attended both partial exams, attended all three PCAM field trips, submitted the PCAM assignment, and participated in at least half of the in-class activities. To calculate the average with the other grades, one of the two exams must be passed with a grade of 5 or higher and the other with at least a 4. In the resit, students only need to retake the part they failed (either the 1st and/or 2nd exam; other assessments are nonrecoverable). To participate in the resit process, the student must have obtained a minimum final grade of 3'5.

Definition of Non-evaluable

Students will receive a \"Non-evaluable\" grade if they have submitted less than 30% of the assessment activities.

Plagiarism

If a student commits any irregularity that could lead to asignificant variation in the grade of an assessment activity, that activity will be graded with a zero, regardless of any disciplinary process that may follow. If multiple irregularities occur in the assessments of the same course, the final grade for that course will be zero.

Use of AI

For this course, the use of Artificial Intelligence (AI) technologies is allowed exclusively in tasks or activities designated by the professor. Students must clearly identify which parts were generated using AI, specify the tools used, and include a critical reflection on how these influenced the process and the final outcome of the activity. Lack of transparency in the use of AI in any assessed activity will be considered academic dishonesty and may result in partial or total grade penalties or more severe sanctions in serious cases.