FF:PSB_22 Empirical Research I - Course Information
PSB_22 Empirical Research: Practical Classes I
Faculty of ArtsSpring 2019
- Extent and Intensity
- 0/2/0. 4 credit(s). Type of Completion: k (colloquium).
- Teacher(s)
- doc. PhDr. Iva Burešová, Ph.D. (seminar tutor)
doc. PhDr. Jaroslava Dosedlová, Dr. (seminar tutor)
doc. PhDr. Jana Marie Havigerová, Ph.D. (seminar tutor)
PhDr. Pavel Humpolíček, Ph.D. (seminar tutor)
doc. PhDr. Martin Jelínek, Ph.D. (seminar tutor)
Mgr. Lenka Ježíková (seminar tutor)
Mgr. Helena Klimusová, Ph.D. (seminar tutor)
PhDr. Irena Komendová, Ph.D. (seminar tutor)
Mgr. Sylvie Kropáčová, Ph.D. (seminar tutor)
Mgr. Tatiana Malatincová, Ph.D. (seminar tutor)
PhDr. Katarína Millová, Ph.D. (seminar tutor)
Mgr. et Mgr. Monika Mrázková, Ph.D. (seminar tutor)
doc. PhDr. Alena Slezáčková, Ph.D. (seminar tutor)
PhDr. Zuzana Slováčková, Ph.D. (seminar tutor)
PhDr. Zdenka Stránská, Ph.D. (seminar tutor)
Mgr. Lenka Štěpánková, Ph.D. (seminar tutor)
prof. PhDr. Tomáš Urbánek, Ph.D. (seminar tutor)
doc. PhDr. Lubomír Vašina, CSc. (seminar tutor)
PhDr. Dalibor Vobořil, Ph.D. (seminar tutor)
PhDr. Katarína Zvončáková, Ph.D. (seminar tutor) - Guaranteed by
- PhDr. Zdenka Stránská, Ph.D.
Department of Psychology – Faculty of Arts
Contact Person: Jarmila Valchářová
Supplier department: Department of Psychology – Faculty of Arts - Timetable of Seminar Groups
- PSB_22/DAQUAo: No timetable has been entered into IS. J. Havigerová
PSB_22/KARDIO: No timetable has been entered into IS. J. Dosedlová
PSB_22/SENIORS_HK: No timetable has been entered into IS. J. Havigerová
PSB_22/1: No timetable has been entered into IS. A. Slezáčková - Prerequisites
- PSA_038 Methodology I
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
- Psychology (programme FF, M-PS) (2)
- 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.
- 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
- Follow-Up Courses
- Further comments (probably available only in Czech)
- Study Materials
The course is taught each semester.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/phil/spring2019/PSB_22