Bachelor's Thesis Preparation 2 - JSB738

• Title: Bachelor's Thesis Preparation 2
• Guaranteed by: Department of Sociology (23-KS)
• Faculty: Faculty of Social Sciences
• Actual: from 2025
• Semester: summer
• E-Credits: 10
• Examination process: summer s.:
• Hours per week, examination: summer s.:0/4, C [HT]
• Capacity: unknown / 20 (unknown)
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: taught
• Language: English
• Teaching methods: full-time
• Additional information: https://dl1.cuni.cz/course/view.php?id=17896
• Note: enabled for web enrollment
• Guarantor: doc. Mgr. Martin Hájek, Ph.D.; Aysha Farhana Chakkampully
• Teacher(s): doc. Mgr. Martin Hájek, Ph.D.; Aysha Farhana Chakkampully
• Pre-requisite : JSB737

Annotation

The seminar is to help students develop their thesis. During the course students present an discuss their progress in their thesis and comment on the progress of their peers.

Last update: Hájek Martin, doc. Mgr., Ph.D. (31.01.2026)

Course completion requirements

To successfully complete the course, students must:

• attend seminars, 
• actively participate in discussions, 
• submit all homework assignments in the required quality, 
• participate in group sessions, 
• and deliver a final presentation of their bachelor's thesis.

Last update: Hájek Martin, doc. Mgr., Ph.D. (01.02.2026)

Syllabus

Week 1 (17./19.2.2026)
Introduction: Reflection on the current state of research and writing. Plans A and B. Visualisation of the path to completing the thesis.

Week 2 (24./26.2.2026)
Data: what are current state of data acquisition, existing obstacles; creating the data corpus and data management; starting with the analysis.
HW: describe your data generation plan + schedule; how data will be organised and stored for the analysis. 

Week 3 (3./5.3.2026)
Data (production and) analysis.
HW: Describe your data analysis plan and schedule.

Week 4 (10./12.3.2026)
Troubleshooting session for data acquisition and analysis.

Week 5 (17./19.3.2026)
Generating results: How to transform analysis outputs into research results. From identifying patterns to describing findings. 
HW: Demonstrate an example of the transformation of detected patterns into research results.

Week 6 (24./26.3.2026)
Generating results. 
AI vs. human work. AI with human work.

No class - Dean's Day holidays (31.3./2.4.2026)

Week 7 (7./9.4.2026)
Making results theoretically relevant: how to construct findings with the theory in mind.
HW: Provide an example of connecting results with the theory.

Week 8 (14./16.4.2026)
Troubleshooting session for linking findings to theory.

Week 9 (21./23.4.2026)
Writing the Results and Discussion:
- Separate Findings and Discussion
- Combined Findings and Discussion
HW: Write an example of a results section with separate and combined findings.

Week 10 (28./30.4.2026)
Troubleshooting session for writing results and discussion.

Week 11 (5./7.5.2026)
Thesis presentation - 1st group

Week 12 (12./14.5.2026)
Thesis presentation - 2nd group

Last update: Hájek Martin, doc. Mgr., Ph.D. (31.01.2026)