Tutorials

Between October and November, a group tutorial will be held with the Master's Coordinator, Dr Maria Corominas, to advise on individual project proposals. Each student will be assigned a master's tutor who will supervise the thesis process; they will guide the student in defining the topic and the structure of the thesis, and will monitor its development. The list of thesis supervisors will be published on the website in December 2026.

To prepare and defend their thesis, each student must attend a minimum of four compulsory tutorials with their supervisor.

The first meeting with the supervisor will take place in December. The thesis topic proposal will be finalised, and the conditions for supervision, as well as the schedule of tasks and deadlines, will be agreed upon.

Subsequently, a minimum of 3 compulsory meetings will be held and the student must sign the monitoring sheet. This monitoring covers both the holding of the meeting and the submission of agreed materials by the pre-set deadlines. The supervisor may decide to hold a greater number of tutorials, which must be agreed with the student.

Indicative timetable:

February - Submission of the first TFM proposal, in accordance with the guidance provided by the supervisor

April - Supervision on the progress of the TFM, based on materials previously agreed with the supervisor

May - From the submission of materials previously agreed with the supervisor, supervision on the TFM draft

Final review by the supervisor before the final submission: Before the final submission, the supervisor must read the final document in its entirety so that corrections and modifications can be made. Therefore, this document must be provided to the supervisor at least 20 days before the submission deadline.

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

Virtual Campus

The TFM's schedule will be available on the course's Virtual Campus, were students willfind the various materials deemed appropriate by 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 modification of the course schedule and teaching methodologies.

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.

ASSESSMENT

The submission of the Master Thesis must be accompanied by the consent of the tutor. According to Faculty criteria (https://www.uab.cat/ca/comunicacio/faq-tfm question 21), the tutor will prepare an evaluation report (rubric) to allow the defense of the Master Thesis. The report shall include the tutor's grade, which shall correspond to 30% of the final grade of the Master Thesis. In the event that the tutor's score is less than 4, it will be understood that he/she does not give his/her consent.

The public defense of the Master's Thesis will take place on between 1st-15th July 2027. The day will be announced via web.

Students must publicly defend their Master's Thesis in front of an evaluation committee formed by three lecturers of the master. The evaluation will be carried out by applying the following rubric:

a) Master thesis (85%): global evaluation of the work, use of theories, research methodology and formal aspects.

b) Public Defense of the Master's Thesis (15%): oral explanation, quality of the arguments and debate, ability to defend one's ideas, ability to synthesize and adapt to the allotted time.

According to Faculty criteria (https://www.uab.cat/ca/comunicacio/faq-tfm question 21), the grade awarded by the examining board or commission corresponds to 70% of the final grade of the Master thesis.

REEVALUATION

Pursuant to Article 261 of the UAB Academic Regulations, the Master’s Thesis (TFM) is not subject to the recovery process.

NOT ASSESSABLE

The Master’s Thesis (TFG) will be graded as Not Assessable if any of the following circumstances occurs:

• The supervisor considers that the project does not meet the minimum requirements for submission and assessment.
• The student does not complete the 4 mandatory tutoring sessions and/or, by the deadline established and published on the faculty’s website, has not completed the first 3 mandatory tutoring sessions.
• The student fails to submit the Final Master Thesis.
• The student does not defend the Final Master Thesis

SINGLE ASSESSMENT

This module does not use the single assessment system.

ARTIFICIAL INTELLIGENCE

The Master’s Thesis (TFM) supervisor shall determine whether the use of Artificial Intelligence (AI) tools is permitted in the TFM, depending on each specific case and the type of TFM, as well as the phases of the work in which such tools are employed and their intended purpose (for example: initial phase (source search), generation of tables and visual representations…). Students must clearly identify any content generated using AI, specify the tools employed, and include a critical reflection on how these technologies have influenced both the process and the final result of the assignment. Failure to disclose the use of AI in this assessed activity will be considered a breach of academic integrity and may result in a partial or total penalty to the assignment grade, or more serious sanctions in severe cases.

IRREGULARITIES

The performance of any irregularity in an evaluation act (academic fraud, plafiarism or improper use of AI, unless this use is expressly authorized by the teaching guide), which may lead to a significant variation in the grade, assumes that this act will be graded with a 0. In the event that the teaching guide foresees that in order to pass the subject it is an essential requirement to have obtanied a minimum grade in this evaluation act or that there are several irregularities in the evaluation acts of the same subject, the final grade of this subject is 0. Apart from this, a disciplinary process may be instructed to the student that incurs any of these irregularities.

Any student suspected of submitting assignments that have been generated by AI, written by others or copied; include unatributed AI-generated content, or fall outside the permitted scope, may be asked to provide the preliminary work or other materials that can demonstrate it is original work and the result of his/her own authorship. they may also be asked to separately explain or justify their work. Teachers may also use AI detection systems or carry out any verification tasks they deep appropriate. If, after review, the instructor detectsirreguarities, the assignment may be graded zero, and the student may be subject to further disciplinary action.