ENS309 Ethics in Engineering and Natural Sciences
ENS309 Ethics in Engineering and Natural Sciences
Syllabus | International University of Sarajevo - Last Update on Feb 02, 2026
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Genetics and Bioengineering
Muhamed Hadžiabdić
Course Lecturer
Course Objectives
To provide students with an understanding of the Ethics in the context of engineering. To present students to the algorithms and theories on resolving conflicting situations in terms of ethical behavior. To present students with case studies related to engineering ethical conflicts.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Additional Literature
Teaching Methods
Lectures
Case studies
Class discussions.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction | notes |
| 2 | Data Privacy in (Bio)Ethics | notes |
| 3 | Ethical considerations in animal studies | notes |
| 4 | Professional Ethics | notes |
| 5 | GMO ethical concerns | notes |
| 6 | Holiday | notes |
| 7 | AI Ethics in Engineering and Natural Sciences | notes |
| 8 | Midterm | |
| 9 | Sustainability and Responsible Design in Engineering | notes |
| 10 | TBA | notes |
| 11 | TBA | notes |
| 12 | Ethical Accountability in Engineering | notes |
| 13 | Biotechnology and Bioethics | notes |
| 14 | TBA | notes |
| 15 | AI and Creativity, Ethics in AI Governance | notes |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| ENS309.1 | Course | Tuesday 14:00 - 16:50 | B F1.23 - Amphitheater I | - | - |
Office Hours & Room
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Midterm Exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Assignments
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
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 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lecture Hours
42 hours ⏳ (14 week × 3 h)
Report
18 hours ⏳ (3 week × 6 h)
Home study
70 hours ⏳ (14 week × 5 h)
Midterm exam study
10 hours ⏳ (2 week × 5 h)
Final exam study
10 hours ⏳ (2 week × 5 h)
150 Total Workload Hours
6 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 [ENS309] 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 | |||||||||
| ENS309 | Ethics in Engineering and Natural Sciences | 3 | 0 | 6 | ||||||
| Prerequisite | Junior Standing | It is a prerequisite to | - | |||||||
| Lecturer | Muhamed Hadžiabdić | Office Hours / Room / Phone | Tuesday: 13:00-15:30 Thursday: 10:00-12:00 |
|||||||
| mhadziabdic@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | To provide students with an understanding of the Ethics in the context of engineering. To present students to the algorithms and theories on resolving conflicting situations in terms of ethical behavior. To present students with case studies related to engineering ethical conflicts. |
|||||||||
| Textbook | Blundell, Barry G. Ethics in Computing, Science, and Engineering: A Student's Guide to Doing Things Right. Cham: Springer, 2020. P. Boddington, AI Ethics: A Textbook. Singapore: Springer Nature, 2023. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Lectures, Case studies, Class discussions. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction | notes | ||||||||
| Week 2 | Data Privacy in (Bio)Ethics | notes | ||||||||
| Week 3 | Ethical considerations in animal studies | notes | ||||||||
| Week 4 | Professional Ethics | notes | ||||||||
| Week 5 | GMO ethical concerns | notes | ||||||||
| Week 6 | Holiday | notes | ||||||||
| Week 7 | AI Ethics in Engineering and Natural Sciences | notes | ||||||||
| Week 8 | Midterm | |||||||||
| Week 9 | Sustainability and Responsible Design in Engineering | notes | ||||||||
| Week 10 | TBA | notes | ||||||||
| Week 11 | TBA | notes | ||||||||
| Week 12 | Ethical Accountability in Engineering | notes | ||||||||
| Week 13 | Biotechnology and Bioethics | notes | ||||||||
| Week 14 | TBA | notes | ||||||||
| Week 15 | AI and Creativity, Ethics in AI Governance | notes | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 40 | 1,2,3 | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm Exam | 1 | 30 | 1,2,3 | Not Allowed | |
| Assignments | 3 | 30 | 1,2,3,4,5 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture Hours | 3 | 14 | 42 | Report | 6 | 3 | 18 | |||
| Home study | 5 | 14 | 70 | Midterm exam study | 5 | 2 | 10 | |||
| Final exam study | 5 | 2 | 10 | |||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 25/02/2026 | |||||||||