Assessment

Continous Assessment Activities

Principles of evaluation

The assessment is structured so that students can choose a format of continuous evaluation or a format where most of the weight of the assessment is concentrated at the end of the course (which can also be used as a recovery mechanism for the continuous evaluation). This allows the student to adapt the pace of completion of the assessment elements to their needs and preferences.

Evaluation elements

There will be the following evaluation elements:

• Follow-up activiites
• Practices
• Partial Exam 1
• Partial Exam 2
• Recovery Exam

The follow-up activities (NS) will consist of participation in class, carrying out problems or tests in class and/or outside of class. The follow-up note will only be used to raise the final grade (maximum of 20%).

The grade of practices (NP) will be evaluated based on the reports that must be submitted at the start and / or end of the practice sessions, the work and possible exercices done during or after the sessions, and the possible additional exercises deliveries. It is not necessary to approve each practice individually. Laboratory sessions are an activity that is not recoverable.

The Partial Exam 1 (ExP1) will be held approximately halfway through the course. It does not release matter why the contigunts of this course are cumulative; that is to say, they must master the first issues to be able to follow the last ones.

The Partial Exam 2 (ExP2) will be carried out approximately the last week of face-to-face activities (theoretical classes).

The Recovery Exam (ExR) will be carried out once the face-to-face activities have been finalized, during the time period specifically devoted to examinations.

Calculation of the final grade

- Continuous assessment note: AC = max {0.4*ExP1 + 0.6*ExP2, ExP2}

- Overall note of the exams (NE):

       - NE = AC if the recovery exam is not peformed.

       - NE = ExR if the recovery exam is performed.

- The final grade (NF) of the subject is: NF = max {0.8 x NE + 0.2 x NP, 0.8 x (0.8 x NE + 0.2 x NP) + 0.2 x NS}

- To approve it is necessary that NF >= 5.

Repeating students

You can keep the Lab Grade from previous years. It is the option that is considered by default if they do not go back to doing the practices.

Honor grades

Granting an Honor qualification is a decision of the faculty responsible for the subject. Honors will be awarded only to students who have shown a great level of excellence in the subject, and not bydefault to those who have removed the highest marks. The regulations of the UAB indicate that Honors can only be awarded to students who have obtained a final grade of 9.00 or more. It can be granted MH up to 5% of the total number of students enrolled.

Consideration of "Not Evaluable"

The final grade will be "Not Evaluable" only when the student is not present at any exam, neither of the continuous evaluation nor recovery exam.

Consideration in case of copy or plagiarism

Notwithstanding other disciplinary measures that are deemed appropriate, and in accordance with the current academic regulations, the evidenceorreports where the student has committed irregularities (eg plagiarism, deception, copying, the fact to leave copy, etc.) that could lead to a variation of the qualification.

Communication

The Virtual Campus will be the communication platform with the students.

Single evaluation

This subject does not consider a single assessment system.

Review procedure

A regular, in-person review period will be established after each exam.

Use of AI

In this course, the use of Artificial Intelligence (AI) technologies is allowed as an integral part of the development of coursework, 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 have been generated using this technology, specify the tools employed, and include a critical reflection on how these have influenced both the process and the final result of the activity. Lack of transparency in the use of AI will be considered an act of academic dishonesty and may result in a grade penalty for the activity, or more severe sanctions in serious cases.