PSBB005 Practice empirical research

Faculty of Arts
Autumn 2024
Extent and Intensity
0/2/0. 3 credit(s). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
prof. PhDr. Marek Blatný, DrSc. (seminar tutor)
doc. PhDr. Iva Burešová, Ph.D. (seminar tutor)
doc. PhDr. Jaroslava Dosedlová, Dr. (seminar tutor)
doc. PhDr. Martin Jelínek, Ph.D. (seminar tutor)
Mgr. Vojtěch Juřík, Ph.D. (seminar tutor)
Mgr. Helena Klimusová, Ph.D. (seminar tutor)
PhDr. Kateřina Koros Bartošová, Ph.D. (seminar tutor)
doc. PhDr. Petr Květon, Ph.D. (seminar tutor)
Mgr. Terezie Pilátová Osecká, PhD (seminar tutor)
prof. PhDr. Hana Přikrylová Kučerová, Ph.D. (seminar tutor)
PhDr. Zuzana Slováčková, Ph.D. (seminar tutor)
PhDr. Zdenka Stránská, Ph.D. (seminar tutor)
Mgr. Beáta Suriaková (seminar tutor)
prof. PhDr. Tomáš Urbánek, Ph.D. (seminar tutor)
PhDr. Dalibor Vobořil, Ph.D. (seminar tutor)
Guaranteed by
doc. PhDr. Petr Květon, Ph.D.
Department of Psychology – Faculty of Arts
Contact Person: Jarmila Valchářová
Supplier department: Department of Psychology – Faculty of Arts
Timetable
Fri 18. 10. 14:00–15:40 C51, Fri 15. 11. 14:00–15:40 C51
  • Timetable of Seminar Groups:
PSBB005/Dopravni_ps: Wed 18. 9. 8:00–11:40 C42, Wed 9. 10. 8:00–11:40 C42, Wed 23. 10. 8:00–11:40 C42, Wed 6. 11. 8:00–11:40 C42, B. Suriaková
Prerequisites
PSBA009 Methodology of Psychology I
PSBA009 Methodology I
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
Students participate in one of the research projects conducted at the department. The aim is to obtain basic experience with research design, data collection and/or basic data processing. The students might find the knowledge highly useful, for example, when working on their own diploma theses. The course includes lecture and practice lecture, the dates of which are announced at the beginning of the semester. The lecture introduces concepts related to the practical aspects of research projects, such as computer-based assessment, data management, open science and the system of control of scientific work in the publication process. Two specific tools for collecting research data in online and experimental environments are presented in practice lecture. Participation in the lecture and tutorial is only mandatory for students who are not actively involved in any research project.
Learning outcomes
Output competences vary depending on the specific research project for which the student registers. Some of the most common outputs include:
- Advanced experience with doing literature review relevant for a specific research question;
- Enhanced knowledge of procedures and pitfalls of selecting and preparing research methods for a specific research project: looking for information, translating and piloting instruments, putting together an electronic questionnaire, designing a test, etc.;
- Practical experience with the selection of target population and sampling procedures appropriate for a specific research project;
- Practical experience with addressing ethical issues in research (e.g. writing up informed consent forms and obtaining informed consent from participants);
- Practical experience with participant recruitment and data collection;
- Skills and knowledge necessary for compiling error-free data files ready for statistical analysis (e.g. aligning data from various sources, reversing scores, computing total scores, identifying problematic cases, etc.);
- Enhancement of skills and knowledge of statistical analysis through hypothesis testing under the investigator's supervision;
- Experience with collaborative preparation of a research report for publication (e.g. a conference poster).
Syllabus
  • Students are involved in research projects conducted at the department. Their contribution especially includes:
  • 1. Finalizing research design and organizing data collection;
  • 2. Performing data collection (e.g., administering tests and questionnaires, online or in person);
  • 3. Data processing (e.g., data coding, rewriting data to Excel, etc.).
  • Students' participation on the research project is not remunerated. Sessions and meetings might take place outside the regular semester schedule.
Literature
  • Vzhledem k charakteru předmětu se literatura neuvádí.
Teaching methods
Team sessions and laboratory classes in small seminar groups; individual or collaborative data collection and processing (depending on the specific demands of the research project).
Assessment methods
Students are expected to perform a specific task (data collection, data processing, etc.), depending on the agreement with the supervising teacher.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught each semester.
Information on course enrolment limitations: Dlouhodobý seminář je určen pro předem vybrané studenty.
The course is also listed under the following terms Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022, Autumn 2022, Spring 2023, Autumn 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/phil/autumn2024/PSBB005