The course combines lectures, practical sessions, supervised activities, and independent work. The Challenge-Based Learning (CBL) methodology will be implemented, guiding the formative activities of the course, with the exception of the theoretical exam.

CBL involves tackling real-world challenges/problems posed by local organizations or institutions. Based on these challenges, students will work in teams to propose possible solutions, following a process divided into three phases: Connection/Commitment, Research/Prototyping, and Implementation/Evaluation. This methodology connects theory with practice by working with real case studies, fosters collaborative work, and helps develop key skills for professional practice.

Theoretical sessions will present the course content, providing the necessary elements to address the challenge and practical tasks. Practical work will be oriented toward the production of deliverables linked to the development of the challenge, under the supervision of the teaching staff. The design and production of practical exercises and proposed solutions will be part of the students’ independent work.

An individual written exam will be held to assess the level of theoretical knowledge acquired and the ability to apply it.

Students may request additional tutorials with the teaching staff during the course.

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

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.

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.

Given the practical nature of this course, a single final assessment is not considered.

Incorporating the Challenge-Based Learning (CBL) methodology, continuous assessment will be applied, gathering evidence of the work carried out in each learning activity and across the various phases of the process in a transversal manner. This evaluation will be complemented by reflection on both individual and group progress, assessing the learning outcomes.

The competencies of this course will be assessed through the following activities:

A. Laboratory practices, deliverables (60%)

B. Written test, exercises related to theoretical content, reports, and active participation (40%)

In order to pass the course, it is mandatory to complete all scheduled practical activities. The final grade will be the sum of the scores obtained in both the practical tasks and the written test. To qualify for this weighted average, students must independently pass both components (practical and theoretical). No average will be calculated if either component is graded below 5.

Revaluation:

Students will be entitled to reassessment in the course if they have been evaluated on a set of activities accounting for at least two-thirds of the total course grade.

Students who have followed the continuous assessment and failed the written test (theoretical part) may retake it, provided they obtained a minimum score of 3.5 on the test and attended the regular review session. The grade obtained in the revaluation will be the final grade for that component.

The practical part of the course cannot be retaken, due to the complexity of its group-based and sequential development, except in duly justified and approved exceptional cases.

Artificial Intelligence:

In this course, the use of Artificial Intelligence (AI) technologies is permitted as an integral part of the work development, provided that the final outcome demonstrates a significant contribution by the student in terms of analysis and personal reflection. Students must clearly identify any content generated using AI, specify the tools employed,

and include a reflection on how these technologies have influenced the process and the final result of the assignment.

Irregularities:

The performance of any irregularity in an evaluation act (academic fraud, plagiarism 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 obtained 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 unattributed 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 their 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 deem appropriate. If, after review, the instructor detects irregularities, the assignment may be graded zero, and the student may be subject to further disciplinary action.