ARCH508 Graduate Studio
Syllabus | International University of Sarajevo - Last Update on Feb 02, 2026
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Architecture
Nerma Omićević
Course Lecturer
Course Objectives
Define the design problem and develop an architectural design solution in relation to the chosen topic.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Baiche, B., Neufert, E. (2011). Architects' data. New York, NY: Wiley-Blackwell;
Additional Literature
Based on a student's project area.Teaching Methods
Active tutorial consultations
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Weekly consultation: definition of the design brief | Baiche, B., Neufert, E. |
| 2 | Weekly consultation | Baiche, B., Neufert, E. |
| 3 | Weekly consultation | Baiche, B., Neufert, E. |
| 4 | Weekly consultation | Baiche, B., Neufert, E. |
| 5 | Weekly consultation; progress check 1 | Baiche, B., Neufert, E. |
| 6 | Weekly consultation | Baiche, B., Neufert, E. |
| 7 | Weekly consultation | Baiche, B., Neufert, E. |
| 8 | Weekly consultation | Baiche, B., Neufert, E. |
| 9 | Weekly consultation; progress check 2 | Baiche, B., Neufert, E. |
| 10 | Weekly consultation; Mid-term presentation in front of the committee | Baiche, B., Neufert, E. |
| 11 | Weekly consultation | Baiche, B., Neufert, E. |
| 12 | Weekly consultation | Baiche, B., Neufert, E. |
| 13 | Weekly consultation | Baiche, B., Neufert, E. |
| 14 | Weekly consultation | Baiche, B., Neufert, E. |
| 15 | Weekly consultation; progress check 3 | Baiche, B., Neufert, E. |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| ARCH508.1 | Course | - | - | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Wednesday | 09:00 - 12:00 | A F3.18 | |
| Thursday | 09:00 - 12:00 | A F3.18 |
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes :
Progress
AI: Not AllowedAlignment with Learning Outcomes :
MId-term presentation
AI: Not AllowedAlignment with Learning Outcomes :
Design process
AI: Not AllowedAlignment with Learning Outcomes :
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 12 ECTS credit course corresponds to 300 hours of total student workload, distributed as follows:
consultations
16 hours ⏳ (16 week × 1 h)
Individual work
136 hours ⏳ (17 week × 8 h)
Design process
136 hours ⏳ (17 week × 8 h)
Midterm presentation
2 hours ⏳ (1 week × 2 h)
Home study
10 hours ⏳ (5 week × 2 h)
300 Total Workload Hours
12 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 [ARCH508] 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 Feb 02, 2026 | International University of Sarajevo
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| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| ARCH508 | Graduate Studio | 0 | 6 | 12 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Nerma Omićević | Office Hours / Room / Phone | Wednesday: 9:30-12:00 Thursday: 9:30-12:00 |
|||||||
| nomicevic@ius.edu.ba | ||||||||||
| Assistant | - | Assistant E-mail | ||||||||
| Course Objectives | Define the design problem and develop an architectural design solution in relation to the chosen topic. | |||||||||
| Textbook | Baiche, B., Neufert, E. (2011). Architects' data. New York, NY: Wiley-Blackwell; | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
| Teaching Methods | Active tutorial consultations | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Weekly consultation: definition of the design brief | Baiche, B., Neufert, E. | ||||||||
| Week 2 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 3 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 4 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 5 | Weekly consultation; progress check 1 | Baiche, B., Neufert, E. | ||||||||
| Week 6 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 7 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 8 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 9 | Weekly consultation; progress check 2 | Baiche, B., Neufert, E. | ||||||||
| Week 10 | Weekly consultation; Mid-term presentation in front of the committee | Baiche, B., Neufert, E. | ||||||||
| Week 11 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 12 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 13 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 14 | Weekly consultation | Baiche, B., Neufert, E. | ||||||||
| Week 15 | Weekly consultation; progress check 3 | Baiche, B., Neufert, E. | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 50 | Not Allowed | ||
| Semester Evaluation Components | |||||
| Progress | 3 | 15 | Not Allowed | ||
| MId-term presentation | 1 | 20 | Not Allowed | ||
| Design process | 1 | 15 | Not Allowed | ||
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| consultations | 1 | 16 | 16 | Individual work | 8 | 17 | 136 | |||
| Design process | 8 | 17 | 136 | Midterm presentation | 2 | 1 | 2 | |||
| Home study | 2 | 5 | 10 | |||||||
| Total Workload Hours = | 300 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 12 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 17/02/2026 | |||||||||