Checking date: 18/05/2022

Course: 2022/2023

Master’s Thesis Seminar
Study: M. Computational Social Science (375)

Coordinating teacher: UCAR MARQUES, IÑAKI

Department assigned to the subject: Statistics Department

Type: Compulsory
ECTS Credits: 3.0 ECTS


Core Competences: - Having and understanding the knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context - Students know how to apply their acquired knowledge and problem-solving skills in new or unfamiliar settings within broader (or multidisciplinary) contexts related to their field of study. - Students are able to integrate knowledge and to face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgments. - Students know how to communicate their conclusions and the knowledge and ultimate reasons behind them to specialised and non-specialised audiences in a clear and unambiguous way. - Students have the learning skills that will enable them to continue studying in a way that will be largely self-directed or autonomous. General Competences: - Ability to apply theoretical and methodological knowledge of computational social sciences to the analysis and resolution of specific cases and empirical problems. - Ability to address issues raised under new or unfamiliar environments, within the context of computational social sciences. - Ability to plan and carry out research in the field of computational social sciences in an autonomous way. - Ability to communicate and present, in a clear, precise and rigorous manner, concepts and results related to computational social science activities to both specialized and non-specialized audiences. Specific Competences: - Ability to prepare, present and adequately defend in public an original and rigorous Master's Thesis, related to one or some of the subjects of the degree. The defense will be individual. Learning Outcomes: - Originality in the approach and use of computational tools. - Ability to write proposals and essays. - Ability to present results of important written works and know how to link them with current social problems.
Skills and learning outcomes
Description of contents: programme
1. Features and structure of the Master's Thesis 2. The logic of social research 3. Theoretical, methodological and technical alternatives used in the elaboration, presentation and defense of the Master's Thesis 4. Workshop
Learning activities and methodology
Training Activities: - Theoretical-practical classes - Individual student work Teaching Methods: - Presentations in the professor's lecture room with computer and audiovisual support, in which the main concepts of the subject are developed and a bibliography is provided to complement the students' learning. - Presentation and discussion in class, under the moderation of the professor, of topics related to the content of the subject, as well as practical case studies. - Developing pieces of work and reports, individually or in group.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100
Basic Bibliography
  • Bui, Y.N.. How to write a master's thesis. Sage Publications.. 2013

The course syllabus may change due academic events or other reasons.