1. Module 1: Introduction to research
1.1. The scientific method
1.2. Qualitative and quantitative approaches
1.3. Research designs
1.4. The data life cycle
2. Module 2: Primary data - The survey
2.1. Definition and steps
2.2. Population and sample
2.3. Data collection methods
2.4. Questionnaire design
2.5. Coding and editing of data
2.6. Survey errors
3. Module 3: Tipology, search, and evaluation of secondary data
3.1. Concept
3.2. Sources of secondary data
3.3. Where to find secondary data?
3.4. Open Science and ethical aspects
4. Module 4: Introduction to data analysis
4.1. Introduction to Statistics
4.2. Types of variables and structure of a dataset
4.3. Univariate descriptive analysis with Jamovi
5. Practical skills
5.1. Type of publicatoins and literature search
5.2. Plagiarism, citation, and reference management with Zotero
5.3. Critical analysis of information sources
5.4. Academic use of AI
A minimum score of 4/10 in the final exam and an overall mark (based on a weighted average of all evaluation tasks) of minimum 5/10.
For those not reaching a 4/10 in the final exam or a 5/10 in the overall mark, there will be a resit examination. Attending the final exam is a requirement to take the resit examination.
Specific criteria for the "No show" grade:
Those students not attending the final exam will be graded as "Not Presented". Attending the final exam is a requierement to take the resit examination.
Single Assessment:
Overall mark based on the secondary data project (25% of the final mark) and a final exam (75% of the final mark).
The final exam will include a written part and a practical part, which will evaluate information literacy skills, the use of secondary data platforms and statistical software. A minimum mark of 4/10 in the exam is required and there will be a resit examination. Attending the final exam is a requirement to take the resit examination.
Minimum requirements to pass:
A mininum score of 4/10 in the final exam and weighted average of all evaluation tasks of minimum 5/10.