POLS791 PhD Thesis
POLS791 PhD Thesis
Syllabus | International University of Sarajevo - Last Update on Mar 03, 2026
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Political Science and International Relations
Hamza Preljević
Course Lecturer
Course Objectives
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
No specific textbook / The list of required readings will be delivered separately.
Additional Literature
Not specified.Teaching Methods
Supervising via regular meetings with an appointed advisor or via email correspondence
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Supervision and mentoring | |
| 2 | Supervision and mentoring | |
| 3 | Supervision and mentoring | |
| 4 | Supervision and mentoring | |
| 5 | Supervision and mentoring | |
| 6 | Supervision and mentoring | |
| 7 | Supervision and mentoring | |
| 8 | Supervision and mentoring | |
| 9 | Supervision and mentoring | |
| 10 | Supervision and mentoring | |
| 11 | Supervision and mentoring | |
| 12 | Supervision and mentoring | |
| 13 | Supervision and mentoring | |
| 14 | Supervision and mentoring | |
| 15 | Supervision and mentoring |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| POLS791.1 | Course | - | - | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Wednesday | 09:00 - 12:00 | B F1.31 | |
| Friday | 09:00 - 11:00 | B F1.31 |
Assessment Methods and Criteria
Assessment Components
PhD Thesis
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 120 ECTS credit course corresponds to 3000 hours of total student workload, distributed as follows:
PhD Thesis
3000 hours ⏳ (60 week × 50 h)
3000 Total Workload Hours
120 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [POLS791] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Mar 03, 2026 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| POLS791 | PhD Thesis | 0 | 0 | 120 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Hamza Preljević | Office Hours / Room / Phone | Wednesday: 9:00-12:00 Friday: 9:00-11:00 |
|||||||
| hpreljevic@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | ||||||||||
| Textbook | No specific textbook / The list of required readings will be delivered separately. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
| Teaching Methods | Supervising via regular meetings with an appointed advisor or via email correspondence, | |||||||||
| Teaching Method Delivery | Hybrid / blended | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Supervision and mentoring | |||||||||
| Week 2 | Supervision and mentoring | |||||||||
| Week 3 | Supervision and mentoring | |||||||||
| Week 4 | Supervision and mentoring | |||||||||
| Week 5 | Supervision and mentoring | |||||||||
| Week 6 | Supervision and mentoring | |||||||||
| Week 7 | Supervision and mentoring | |||||||||
| Week 8 | Supervision and mentoring | |||||||||
| Week 9 | Supervision and mentoring | |||||||||
| Week 10 | Supervision and mentoring | |||||||||
| Week 11 | Supervision and mentoring | |||||||||
| Week 12 | Supervision and mentoring | |||||||||
| Week 13 | Supervision and mentoring | |||||||||
| Week 14 | Supervision and mentoring | |||||||||
| Week 15 | Supervision and mentoring | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| PhD Thesis | 1 | 100 | 1,2,3, 4 | Not Allowed | |
| Semester Evaluation Components | |||||
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| PhD Thesis | 50 | 60 | 3000 | |||||||
| Total Workload Hours = | 3000 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 120 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 27/03/2026 | |||||||||