PSB_22 Empirical Research: Practical Classes I

Faculty of Arts
Spring 2019
Extent and Intensity
0/2/0. 4 credit(s). Type of Completion: k (colloquium).
doc. PhDr. Iva Burešová, Ph.D. (seminar tutor)
PhDr. Jaroslava Dosedlová, Dr. (seminar tutor)
doc. PhDr. Jana Marie Havigerová, Ph.D. (seminar tutor)
PhDr. Pavel Humpolíček, Ph.D. (seminar tutor)
PhDr. Martin Jelínek, Ph.D. (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)
doc. PhDr. Alena Slezáčková, Ph.D. (seminar tutor)
PhDr. Zuzana Slováčková, Ph.D. (seminar tutor)
PhDr. Zdenka Stránská, Ph.D. (seminar tutor)
PhDr. Katarína Šafárová, 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)
Mgr. et Mgr. Monika Víchová, Ph.D. (seminar tutor)
Mgr. Lenka Vildová (seminar tutor)
PhDr. Dalibor Vobořil, 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
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
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).
  • 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.
  • 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
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught each semester.
The course is also listed under the following terms Autumn 1998, Spring 2000, Spring 2001, Spring 2002, Spring 2003, Spring 2004, Spring 2005, Autumn 2008, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018.
  • Enrolment Statistics (recent)
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