Guia docente 2024_25 Centro Universitario de la Defensa de la Escuela Naval Militar de Marín

Master Universitario en Dirección TIC para la defensa

Assessment

	Description	Qualification	Training and Learning Results
Presentation	Exhibition by part of the students, in an individual way or in the group, of a subject related to the contents of the matter or of the results of a work, exercise, project, etc. Through the presentation can evaluate knowledge, skills, and aptitudes. There will be 1 presentation (P) that will be evaluated during the face-to-face phase: it will cover all the contents of the subject.	10	A6 A7 A8 A9 A10	B1 B2	C15	D4 D5
Objective questions exam	Proof that evaluates the knowledge and that includes enclosed questions with different alternative answers (true or false, multiple elections, the pairing of elements, etc.). The students/ace select an answer from among a number limited of possibilities. It will consist in a written exam (PE) at the end of the in-person stage, in which all the contents of the subject will be assessed (including the contents of the phase to distance and the face-to-face)	40	A6 A7 A8 A9 A10	B1 B2	C15	D4 D5
Essay	Text or document elaborated on a subject that has to draft following some norms established of style and length. It allows us to evaluate the skills, the knowledge, and, in lower measure, the aptitudes of the student. There will be 1 work (T) that will be evaluated during the online stage: it will cover all the contents of the subject.	20	A6 A7 A8 A9 A10	B1 B2	C15	D4 D5
Problem and/or exercise solving	Resolution of different exercises (E1, E2, and E3) proposed in class about assumptions applicable to different aspects of the subject matter. Each exercise has a weight of 10% and will be completed in the distance phase.	30	A6 A7 A8 A9 A10	B1 B2	C15	D4 D5

Other comments on the Evaluation
It is necessary to reach 50% of the mark in order to pass the course. A continuous evaluation mechanism will be used, which it is intended to monitor the student's progress throughout the course, assessing their effort globally. Denoted as EV_CON, the continuous evaluation mark is calculated as follows: EV_CON = 0.2T + 0.1P + 0.1E1 + 0.1E2 + 0.1E3 + 0.4PE. In case the student fails to pass the course in the ordinary call, he/she will have the right to a second evaluation opportunity (extraordinary call) that will take place in the distance mode on the dates established for that purpose by the Master's Academic Committee. The evaluation will consist in that case in a single written test that will account for 100% of the grade, being necessary to obtain at least 50% to pass the subject. ACADEMIC INTEGRITY: Students are expected to show adequate ethical behaviour, committing to act honestly. Based on article 42.1 of the Regulation on the evaluation, qualification and quality of teaching and the student learning process of the University of Vigo, any violation of academic integrity in the assessment process, as well as the cooperation in it will result in the assignment of a failing grade to the student (zero) for the entire course in the corresponding assessment opportunity, regardless of the percentage of importance that the test in question had in the overall continuous assessment, and independently of other disciplinary actions that may be applied. In the academic activities and assignments of this course, the use of Generative Artificial Intelligence (GAI) tools is allowed, used in an ethical, critical and responsible manner. In case you have used GAI, you should critically evaluate any results it provides, carefully verify any citations or references generated, and declare the use of these tools. It is not necessary to disclosure the use of GAI in tasks that do not produce content (proofreading language - spelling or grammar - in a document, translating text, obtaining suggestions to reorganize content or modify the style of a document, or to adapt the format of bibliographic references). AI-generated content (text, images, etc.) must be disclosured and correctly referenced, providing, at least, the following elements: generated content, prompt used in the query, tool used, version, company authoring the software, date on which the query was made and the link to the tool's website. The detection of situations involving non-disclosure of GAI will be considered academic fraud and the measures described in the previous paragraph will be applied. In the case of any difference between the Galician/Spanish/English guides related to the evaluation, the Spanish guide will always prevail.