The Analysis and Presentation of Scientific Data module combines lectures, practical classes and seminars, including the analysis and discussion of scientific articles and practical case studies. The teaching methodology is adapted to the objectives of each of the three sections of the module. The organization and teaching methodology of each section are described below.

Topic 1. Statistics

This section will be delivered primarily through practical classes held in computer classrooms. The sessions will combine a brief introduction to the theoretical concepts with their immediate application to the analysis of experimental data. Throughout the course, different statistical analysis tools and software commonly used in biomedical research will be introduced, which students will use to complete the proposed exercises and practical activities.

In addition to the activities carried out during the face-to-face sessions, students will be required to complete two practical case studies. For each case study, a set of experimental data will be made available through the Virtual Campus, which students will analyse by applying the statistical methodologies covered during the course. Students will be required to interpret the results obtained, justify the procedures used and present their conclusions appropriately.

Topic 2. Scientific communication

This section combines lectures and seminars. The contents will be delivered mainly through lectures supported by audiovisual materials. The presentations used by the teaching staff will be made available in advance through the Virtual Campus.

Learning will require the active participation of students, who will prepare different scientific communication proposals in a variety of formats, including abstracts, posters and graphical abstracts, and will prepare and orally present one of these works to the rest of the class and the teaching staff.

The seminars will focus on monitoring the work prepared by students and will encourage peer review and discussion among students, together with feedback from the teaching staff. During these sessions, the different materials will be discussed before their oral presentation, with the aim of improving their scientific content, the quality of the communication and the ability to provide constructive criticism of both one's own work and that of others.

Topic 3. Good Scientific Practices Guidelines

This section combines lectures and seminars. The contents will be delivered mainly through lectures supported by audiovisual materials. The presentations and the rest of the teaching materials will be made available in advance through the Virtual Campus.

Students will acquire the knowledge and competences associated with this section through the analysis and discussion of cases related to good scientific practices, which will be discussed during the face-to-face sessions. This activity will be complemented by the preparation of a written commentary on one of the proposed cases, which must be submitted within the established deadline and will be evaluated. In addition, the cases will be discussed during an in-class discussion session, in which critical reflection on the ethical, legal and professional aspects associated with research practice will be encouraged.

The cases and the guidelines for their development will be provided by the teaching staff at the beginning of the course.

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 activities

The assessment of the module will be based on the following activities:

Topic 1. Statistics

The assessment will consist of the resolution of two practical statistical case studies, in which students will be required to apply the methodologies covered during the course, interpret the results obtained and justify the procedures used.

Topic 2. Scientific communication

Students will be required to work on an abstract, a poster or a graphical abstract, and an oral presentation on a scientific topic previously agreed upon with the teaching staff. The assignments must be original and submitted within the established deadlines. Assessment will take into account both the scientific quality of the content and its communication, including the structure, clarity of presentation and appropriateness of the visual resources used.

Topic 3. Good Scientific Practices Guidelines

Assessment will be based on the written commentary prepared on the proposed bioethics case. Compliance with the submission deadline will be taken into consideration; therefore, assignments submitted after the case discussion session will not be accepted.

Assessment weighting

To pass the module, students must obtain an overall mark equal to or greater than 5 points based on the module's assessment activities.

Topic 1. Statistics (overall weighting: 40%)

The relative weighting of each assessment activity will be:

· Practical case study 1: 50%

· Practical case study 2: 50%

Topic 2. Scientific communication (overall weighting: 40%)

The relative weighting of each assessment activity will be:

· Abstract: 33%

· Poster (or graphical abstract): 33%

· Oral presentation: 34%

Topic 3. Good Scientific Practices Guidelines (overall weighting: 20%)

The relative weighting of the assessment activity will be:

· Written commentary and public discussion of the bioethics case: 100%

Resit assessment

A resit assessment equivalent to the corresponding assessment for each topic of the module will be offered, except for those activities specifically indicated otherwise in each case.

To be eligible for the resit assessment, students must have previously been assessed in a set of activities whose combined weighting represents at least two-thirds of the total module grade.

Additional considerations

· This module does not provide for the single assessment system.

· Students will receive a grade of "Not Assessable" when the assessment activities completed account for less than 67% of the final grade.

· In this module, the use of Artificial Intelligence (AI) technologies is permitted exclusively as a support tool for information search, linguistic revision of texts, and the generation and debugging of computer code or scripts for data processing. Students must clearly identify which parts have been generated using this technology, specify the tools used, and include a critical reflection on how these tools have influenced both the process and the final outcome of the assessment activity. Failure to disclose the use of AI in this assessment activity will be considered a breach of academic integrity and may result in a partial or total reduction of the grade for the activity, or more severe disciplinary sanctions in serious cases.

· Any irregularity committed during an assessment activity (academic fraud, plagiarism, or improper use of AI, unless such use is expressly authorized in the course guide) that may lead to a significant alteration of the grade will result in that assessment activity being graded 0. If the course guide establishes that obtaining a minimum grade in that assessment activity is an essential requirement to pass the module, or if multiple irregularities are committed in the assessment activities of the same module, the final grade for the module will be 0. Furthermore, disciplinary proceedings may be initiated against any student who incurs any of these irregularities.