Degree | Type | Year |
---|---|---|
Sociology | OT | 4 |
You can view this information at the end of this document.
There is none.
The aim of this course is to interrogate knowledge from a sociological perspective. Throughout the semester we will pose questions such as: “What do we understand by ‘knowledge’ in our society? How do people decide what to believe and what is worth believing? What role do institutions like the university play in the production of knowledge? Whom do we consider an expert in our society? What is the relationship between knowledge and reality? And between knowledge and conspiracies? And what role does knowledge play in how we imagine and construct possible future scenarios?”
Thus, the main objective is to provide students with a theoretical and methodological toolbox to critically analyze how knowledge is defined, produced, and disseminated. We will ask what we mean by “knowledge” in various contexts (scientific, professional, artistic, religious), which actors—intellectuals, experts, institutions—determine which narratives gain social validity, and how all these dynamics influence the imagination and construction of possible futures.
At the same time, this course seeks to highlight the central role of epistemological reflection for the research process itself and for sociological reflection. Therefore, we will combine classical readings that gave rise to the sociology of knowledge with more recent contributions addressing the challenges of globalization, digitalization, and the “datafication” of everyday life.
Main Program Module
1. Background: the sociological reflection on knowledge
2. Intellectuals and experts
3. The university in a context of neoliberal globalization
4. Production and dissemination of knowledge: issues of translation
5. The thresholds of scientific knowledge: art, astrology, and other knowledge
6. In search of truth? Conspiracies and political mobilization
7. Algorithms and the datafication of life
8. Imagining the future: knowledge and future scenarios
These modules may be adapted and/or slightly modified in the specific course program.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Section 1 and 2 | 20 | 0.8 | 1, 2, 3, 8, 11 |
Section 3 and 4 | 20 | 0.8 | 1, 3, 4, 8 |
Section 5 and 6 | 20 | 0.8 | 14, 13, 1, 7, 3, 4, 6, 8, 9, 15, 11, 12 |
Type: Supervised | |||
Debates in class and preparation of the essay | 30 | 1.2 | 14, 13, 1, 3, 4, 6, 5, 8, 9, 11, 12 |
Type: Autonomous | |||
Reading and commentary of the texts | 60 | 2.4 | 14, 13, 1, 2, 7, 3, 4, 6, 5, 8, 9, 10, 15, 11, 12 |
The course will combine lectures, reading seminars, and presentations on specific topics. Additionally, the students will develop an essay on a topic that will be agreed upon initially.
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.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Essay | 30 | 0 | 0 | 14, 13, 1, 2, 7, 3, 4, 6, 5, 8, 9, 10, 15, 11, 12 |
Final Exam | 50 | 0 | 0 | 1, 2, 3, 5, 8, 9, 12 |
In-class presentation | 20 | 0 | 0 | 13, 1, 3, 6, 5, 8, 9, 15 |
Continuous Assessment
An essay to be defined at the beginning of the course (30%)
An exam (50%)
A class presentation (20%)
Single Assessment
A memorization exam (70%)
An essay (30%)
The review of the final grade follows the same procedure as for continuous assessment.
**It will be necessary to obtain a minimum of 4,75 in all parts of the assessment (exam, essay, and class presentation) to be able to pass the course.
**Non-assessable Students: when a student is deemed not to have provided sufficient evidence for evaluation, the course will be recorded as “non-assessable” on the transcript.
A student will be considered non-assessable if they fail to submit the required coursework, as outlined in this syllabus.
Restricted use of AI
In this course, the use of Artificial Intelligence (AI) tools is permitted exclusively for support tasks, such as bibliographic or factual research, text correction, translation, or language refinement. AI may not be used to generate or structure core argumentative content without prior authorization from the instructor.
Students must clearly identify any sections generated or assisted by AI technologies, specify which tools were used, and include a brief critical reflection on how these tools influenced their process and the final result.
Failure to be transparent about the use of AI in graded assignments will be considered a breach of academic integrity and may result in a partial or total penalty, or more severe disciplinary action in serious cases.
There is no specific one.
Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PAUL) Classroom practices | 1 | Catalan | first semester | morning-mixed |
(TE) Theory | 1 | Catalan | first semester | morning-mixed |