Assessment

Continous Assessment Activities

Title	Weighting	Hours	ECTS	Learning Outcomes
Final project	0,45	4	0.16	CM03, CM04, CM05, CM06, CM08, CM09, CM10, CM11, CM56, CM57, CM58, CM59, KM05, KM15, KM39, SM03, SM12, SM48
Invidual short tests	0,2	0	0	CM05, CM10
Portfolio	0,35	0	0

The students must:

• Answer 10 tests and view the corresponding conferences
• Complete 5 deliveries of the proposed ones
• Write and present a paper in English in a group of 3-4 members

 

The details of these activities are described below

There are three types of evaluation activities:

A) Individual short objective tests (20% of the final grade).

These are multiple-choice tests that assess attention and understanding of the material.

Students must participate in at least 8 lectures and complete a specific test for each one via the Moodle platform.
The students must complete the corresponding tests of all lectures.
The average of the tests will be calculated based on the 10 tests. If fewer than 10 are completed, the missing tests will count as zero.

B) Student portfolio (35% of the final grade)

The student must maintainan up-to-date virtual portfolio on Moodle, where all mandatory exercises and assignments proposed throughout the course will be submitted.
It should also include a selection of materials demonstrating the student’s engagement in the discussion sessions of the lectures, including personal opinions and individual research.
Depending on the type of exercise, transversal skills such as critical thinking, autonomous learning, and the ability to analyze and synthesize will be assessed. These requirements may vary depending onwhether the student is in the first or fourth year, adapting to their level.
The average of the submissions will be calculated based on the 5 assignments. If fewer than 5 are submitted, the missing ones will count as zero.

C) Final project (45% of the final grade)

Each student must participate in the completion of a final project, mandatory to be done in groups of three to four students, chosen among those proposed by the lecturers of the various sessions.
The final project must be submitted in written form (electronically) within the established deadlines and must comply with the formal and content requirements of a scientific paper, following the criteria that will be explained at the beginning of the course in a dedicated info session.
In the case of fourth-year students, the paper must be written in English, the presentation must be held in english and the work cannot cover topics directly related to their own degree program.

At the end of the course, several public presentation sessions will be held on dates announced in the course calendar. All group members must participate in the presentation.
Evaluation will be carried out by a committee of professors who will assess the quality of the presentation, communication skills, organization, etc.
Where possible, the schedule will consider availability so that both attending and non-attending students can present their project, as the presentation is strictly mandatory.
For students abroad, presenting via videoconference will be considered.

In any case, it is the student’s responsibility to reserve the presentation dates, which will be known at the beginning of the course, in order to be able to present the project.
In case of schedule conflict, the course team must be notified in advance to explore possible adjustments.

The final project grade will take into account both the written paper and the oral presentation. The final mark must be at least 4 out of 10 to pass the course.
If the final project grade is below 4, the team may be asked (though not necessarily) to revise and resubmit the project.

AI

Permitted use: “In this course, the use of Artificial Intelligence (AI) technologies is permitted as an integral part of the development of the work, provided that the final result reflects a significant contribution from the student in terms of analysis and personal reflection. The student must clearly identify which parts were generated using this technology, specify the tools used, and include a critical reflection on how these influenced the process and the final result of the activity. Lack of transparency in the use of AI will be considered academic dishonesty and may lead to a penalty in the activity grade, or more severe sanctions in serious cases. Excessive use of AI will be penalized if there are serious errors or, for example, if the style and language of the written work differ significantly from those used in the oral presentation.”

Not gradable
All students who do not submit the final course assignment will be considered “not gradable.”