BIO424 Introduction to Forensic Science
Syllabus | International University of Sarajevo - Last Update on Oct 10, 2025
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Genetics and Bioengineering
Muhamed Adilović
Course Lecturer
Course Objectives
Introduce students to the discipline of Forensic Science, with a more specific aim on forensic genetics.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
I: An Introduction to Forensic Genetics; William Goodwin, Adrian Linacre, Sibte Hadi; Wiley-Blackwell; II: Illustrated Guide to Home Forensic Science Experiments; Robert Bruce Thompson, Barbara Fritchman Thompson; O'Reilly
Additional Literature
Forensic Science; Andrew R.W. Jackson, Julie M. Jackson; PearsonTeaching Methods
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction to the Course | |
| 2 | Introduction to Forensic Genetics; DNA - Genome Structure | I-1, I-2 |
| 3 | Biological Material; DNA Extraction / Quantification | I-3, I-4 |
| 4 | PCR; STR Analysis, Quiz I | I-5, I-6 |
| 5 | STR Profile Assessment | I-7, I-8 |
| 6 | Statistical Interpretation and Evaluation and Presentation of DNA evidence | 1-8, I-9 |
| 7 | Case Study - Evidence Analysis | II-G2 |
| 8 | Midterm | |
| 9 | DNA Profile Databases; Kinship Testing | I-10, I-11 |
| 10 | SNPs; Lineage Markers | I-12, I-13 |
| 11 | Case Study - DNA workflow | II-G11 |
| 12 | Non-human DNA typing, Quiz II | I-14 |
| 13 | Case Study - Fingerprint Analysis | II-G4 |
| 14 | Project Presentations | |
| 15 | Review |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| BIO424.1 | Course | Thursday 12:00 - 14:50 | B F1.16 | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Tuesday | 08:00 - 11:00 | A F1.33 | |
| Wednesday | 08:00 - 11:00 | A F1.33 |
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Midterm
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Quizes
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Project
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:
Lectures
45 hours ⏳ (15 week × 3 h)
Home Study
45 hours ⏳ (15 week × 3 h)
Quiz Prep
20 hours ⏳ (2 week × 10 h)
Midterm Prep
10 hours ⏳ (1 week × 10 h)
Final Prep
15 hours ⏳ (1 week × 15 h)
Project Work
15 hours ⏳ (1 week × 15 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 [BIO424] 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 Oct 10, 2025 | 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 | |||||||||
| BIO424 | Introduction to Forensic Science | 3 | 0 | 6 | Thu. 12:00-14:50 | |||||
| Prerequisite | Junior Standing | It is a prerequisite to | - | |||||||
| Lecturer | Muhamed Adilović | Office Hours / Room / Phone | Tuesday: 8:00-11:00 Wednesday: 8:00-11:00 |
|||||||
| madilovic@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | Introduce students to the discipline of Forensic Science, with a more specific aim on forensic genetics. | |||||||||
| Textbook | I: An Introduction to Forensic Genetics; William Goodwin, Adrian Linacre, Sibte Hadi; Wiley-Blackwell; II: Illustrated Guide to Home Forensic Science Experiments; Robert Bruce Thompson, Barbara Fritchman Thompson; O'Reilly | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
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| Teaching Methods | ||||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction to the Course | |||||||||
| Week 2 | Introduction to Forensic Genetics; DNA - Genome Structure | I-1, I-2 | ||||||||
| Week 3 | Biological Material; DNA Extraction / Quantification | I-3, I-4 | ||||||||
| Week 4 | PCR; STR Analysis, Quiz I | I-5, I-6 | ||||||||
| Week 5 | STR Profile Assessment | I-7, I-8 | ||||||||
| Week 6 | Statistical Interpretation and Evaluation and Presentation of DNA evidence | 1-8, I-9 | ||||||||
| Week 7 | Case Study - Evidence Analysis | II-G2 | ||||||||
| Week 8 | Midterm | |||||||||
| Week 9 | DNA Profile Databases; Kinship Testing | I-10, I-11 | ||||||||
| Week 10 | SNPs; Lineage Markers | I-12, I-13 | ||||||||
| Week 11 | Case Study - DNA workflow | II-G11 | ||||||||
| Week 12 | Non-human DNA typing, Quiz II | I-14 | ||||||||
| Week 13 | Case Study - Fingerprint Analysis | II-G4 | ||||||||
| Week 14 | Project Presentations | |||||||||
| Week 15 | Review | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 40 | 1,2,3,4,5 | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm | 1 | 24 | 1,2,3,4,5 | Not Allowed | |
| Quizes | 2 | 21 | 1,2,3,4,5 | Not Allowed | |
| Project | 1 | 15 | 1,2,3,4,5 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lectures | 3 | 15 | 45 | Home Study | 3 | 15 | 45 | |||
| Quiz Prep | 10 | 2 | 20 | Midterm Prep | 10 | 1 | 10 | |||
| Final Prep | 15 | 1 | 15 | Project Work | 15 | 1 | 15 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 23/10/2025 | |||||||||