Degree | Type | Year |
---|---|---|
Sociology | OB | 2 |
You can view this information at the end of this document.
It is recommended to have passed the courses on Methodology and Design of Social Research, Quantitative Methods, and Qualitative Methods.
Within the curriculum of methods and techniques for social research, this course is designed as a continuation of the "Methodology and Research Design" course from the first year, and the "Quantitative Methods in Social Research" and "Qualitative Methods in Social Research" courses from the first semester of the second year of the degree.
The main aim of the course is to equip students with the theoretical foundations and technical tools necessary to develop the applied aspect of what it means to be a sociologist.
The fundamental objective is to provide students with the information and skills development for the application of both qualitative and quantitative techniques during the empirical testing phase of research, particularly in data analysis.
On one hand, the course will focus specifically on qualitative methods and techniques for observation and analysis of qualitative data (content analysis and thematic analysis).
On the other hand, from a quantitative perspective, the course concentrates on statistical techniques for analyzing relationships and associations between two variables.
QUALITATIVE BLOCK
Topic 1: Observation techniques – direct observation
Topic 2: Content and thematic qualitative analysis
Topic 3: Axiological aspects in qualitative research
Topic 4: Quality in qualitative research
QUANTITATIVE BLOCK
Topic 0: Statistical data analysis techniques
Topic 1: Data retrieval and spreadsheet treatment
Topic 2: Contingency table analysis
Topic 3: One-way ANOVA
Topic 4: Simple linear regression analysis
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Classroom practicals | 15 | 0.6 | 2, 1, 5, 13, 14, 15, 6, 9, 12, 20 |
Lectures | 37 | 1.48 | 2, 1, 3, 13, 14, 15, 11, 6, 7, 8, 9, 12, 16, 20 |
Type: Supervised | |||
Group tutorials | 15 | 0.6 | 2, 1, 18, 4, 13, 14, 15, 11, 6, 19, 12, 16, 20 |
Type: Autonomous | |||
Group work | 23 | 0.92 | 2, 1, 18, 17, 3, 5, 4, 13, 14, 15, 6, 7, 19, 9, 12, 16, 25, 20 |
Individual assignments | 11 | 0.44 | 2, 1, 18, 3, 4, 14, 7, 12, 16 |
Individual exam prep | 22 | 0.88 | 2, 1, 14, 6, 8, 12, 16, 20 |
Readings | 23 | 0.92 | 11, 6, 8, 9, 16 |
Since the course is primarily focused on learning the basic techniques of quantitative and qualitative analysis, the teaching methodology and formative activities place the student at the center of the teaching-learning process.
Thus, the teaching methodology will combine: lectures (to guide and clarify doubts about the required readings) and in-person practical sessions (in seminars and/or computer labs). This teaching format allows for the application of the concepts learned and the techniques explained, and will be combined throughout the course with follow-up tutorials and independent work.
As mentioned in the content section, the course is divided into two clearly distinct blocks: the qualitative block and the quantitative block. Both blocks will be developed sequentially, starting with the quantitative block and continuing with the qualitative block.
Below, the different activities are detailed, along with their specific weight in the total time distribution that the student should dedicate to 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.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Qualitative block: Attendance to practicals | 5% | 0 | 0 | 2, 1, 3, 14, 6, 7, 8, 9, 12, 20 |
Qualitative block: Group research project | 25% | 0 | 0 | 2, 1, 18, 17, 3, 5, 4, 13, 14, 15, 11, 6, 7, 19, 8, 9, 12, 16, 25, 20 |
Qualitative block: Written exam | 20% | 2 | 0.08 | 2, 1, 3, 5, 13, 14, 15, 11, 6, 7, 8, 9, 12, 16, 20 |
Quantitative block: Course participation and follow-up | 5% | 0 | 0 | 5, 6, 19, 8, 20 |
Quantitative block: Excel and group research project | 20% | 0 | 0 | 2, 1, 18, 17, 3, 5, 4, 13, 14, 15, 11, 6, 7, 19, 8, 9, 12, 16, 20 |
Quantitative block: Written exam | 25% | 2 | 0.08 | 2, 1, 3, 5, 4, 14, 15, 11, 6, 7, 19, 8, 9, 10, 12, 16, 21, 22, 20, 23, 24 |
This course does not offer a unique assessment system. Additionally, it requires active student participation and considers regular attendance as a way of integrating the different learning activities.
To pass the course, a minimum final grade of 5 is required, calculated as the weighted average of the 6 evaluation activities. See the weight distribution of each activity in the table above.
For the calculation of this weighted average, the following criteria will be applied based on course participation:
Students who do not attend class regularly (attendance and/or participation below 70%): The average will only be calculated if the grade for each and every part is at least 5.
Students who attend class regularly (attendance and/or participation above 70%): The average will be calculated if the grade for each and every part is at least 4.
(A) Attendance at Scheduled Practical Sessions (5%)
During the classroom sessions, group activities will be carried out to apply the theories discussed in class, with the aim of putting into practice the theoretical and methodological tools presented during the session.
(B) Written Test (20%)
A theoretical exam in which the student will be asked to demonstrate their understanding and familiarity with the main theories of qualitative data analysis.
(C) Group Research Assignment (25%)
Qualitative material collected during the first methodological courses will be used to analyze it through a simple thematic analysis. The definition of a coding system for the text and its relation to the scientific debate the student wishes to contribute to will be evaluated, as well as the ability to comprehend the text.
(A) Course Follow-up (5%)
This consists of two types of activities:
In-Class Activities: In each session, a brief test will be conducted with questions on the content covered in class or the reading materials assigned for the session. Failure to answer this test will be considered as lack of follow-up.
Out-of-Class Activities: At the end of each session, a series of exercises and problems will be given that must be submitted before the next class. Failure to submit them will be considered as lack of follow-up.
(B) Written Test (25%)
A practical exam in which the following will be evaluated:
Mastery of bivariate statistical concepts (both descriptive and inferential) and their application using RStudio software.
The ability to work correctly with a spreadsheet.
(C) Group Assignments (20%)
Two group assignments must be completed with a maximum of 5 people per group:
Excel Applications (7%): This will involve applying the Excel functionalities explained in the sessions. It represents 35% of the total grade for the block.
Hypothesis Testing in RStudio (13%): Continuation of the research started in the first semester in the course "Quantitative Methods for Social Research", using bivariate statistical techniques for data analysis.
1c. Consideration of Non-Assessable Students
In the evaluation report, students will be marked as "non-assessable " if they have not completed any evaluation activities or if they have only submitted the first research assignment (either from the qualitative or quantitative block).
2. Retakes
During the re-sit period, students who do not pass (<5) any of the individual tests or group assignments may present themselves for compensatory assessment.
Follow-up activities and/or attendance are excluded from the re-sit process.
3. Carrying Grades from Previous Years
Students who have passed any block in previous convocations MUST contact the responsible teaching staff at the beginning of the course.
Under no circumstances will partial credits for any of the two blocks be accepted for validation.
4. Plagiarism Policy
It is reminded that, at the moment of signing the enrollment, the following commitment was made:
“I DECLARE that the Universitat Autònoma de Barcelona has informed me that (...) plagiarism is the act of disclosing, publishing, or reproducing a work or part of it in the name of an author different from the original, which constitutes the appropriation of ideas created by another person without explicitly acknowledging their origin. This appropriation constitutes a violation of the intellectual property rights of that person, which I am not authorized to infringe under any circumstances: exams, assignments, practices... Therefore, I COMMIT to respecting the regulatory provisions regarding intellectual property rights in relation to teaching and/or research activities carried out by the UAB in the studies I am undertaking.”
Exams: In case any student is detected copying unauthorized content, all individuals involved will be automatically suspended without the possibility of recovery.
Assignments: In cases of plagiarism in the writing of assignments, each case will be assessed individually, and in extreme cases, direct suspension without the option for recovery may be applied. In writing, both human and technological assistance is considered plagiarism.
5. Use of Artificial Intelligence
The use of Artificial Intelligence (AI) technologies is permitted in this course exclusively for support tasks, such as literature or information searches, text correction, translations, and support in the use of software packages.
Students must clearly identify which parts were generated using AI, specify the tools used, and include a critical reflection on how these influenced the process and the final outcome of the activity.
Lack of transparency in the use of AI will be considered a breach of academic honesty and may result in partial or total penalties to the activity grade, or more serious sanctions in severe cases.
1. REQUIRED READINGS
At the Virtual Campus webspace and face-to-face sessions we will inform you which readings are mandatory (content evaluable in written tests) and which are complementary. In general, the base material for the subject is sufficiently addressed in the corresponding chapters of the following references:
2. RECOMMENDED READINGS
QUALITATIVE BLOCK
+ Digital resources (dossiers for practice, documents, links, ...) on the Virtual Campus.
QUANTITATIVE BLOCK
+ Digital resources (dossiers for practice, documents, links, ...) on the Virtual Campus.
Spreadsheet: Microsoft Excel
Quantitative data transformation and analysis: RStudio
Qualitative data analysis: Atlas.Ti
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 |
---|---|---|---|---|
(SEM) Seminars | 1 | Catalan | second semester | morning-mixed |
(SEM) Seminars | 10 | Catalan | second semester | morning-mixed |
(SEM) Seminars | 51 | Catalan | second semester | afternoon |
(SEM) Seminars | 510 | Catalan | second semester | afternoon |
(TE) Theory | 1 | Catalan/Spanish | second semester | morning-mixed |
(TE) Theory | 51 | Catalan/Spanish | second semester | afternoon |