PSY329 Psychometrics
Syllabus | International University of Sarajevo - Last Update on Sep 09, 2025
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Psychology
Pinar Unal Aydin
Course Lecturer
Course Objectives
Psychometrics is a very important subdiscipline of psychology as the maturity of any scientific discipline depends on the extent to which it has its own measuring methods and systems of measurement. This rule does not go round psychology. The goal of the course is to introduce students into basic principles of measuring psychological processes and development of psychological measuring instruments. It is expected that the students will get familiar with the principles of defining variables, constructing test items and assessing the measuring characteristics of tests and questionnaires.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Nunnally, J. C & Bernstein, I. H. (1997). Psychometric theory. Third Edition. McGraw Hill-Series in Psychology.
Additional Literature
Chadha N.K. (2009). Applied Psychometry. California: Sage Publication IncTeaching Methods
Class discussions with examples
Group workouts for engaged learning and continuous feedback on progress
Individual and grouped discussions
Visual and written materials will be supplied
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction, syllabus presentation, course presentation | - |
| 2 | Definition of psychometrics: An Introduction to the theory of measurement-part 1 | Part 1-1,1-2 |
| 3 | An Introduction to the theory of measurement-part 2 | Part 1-3 |
| 4 | Multi-item measures | Part 1-3 |
| 5 | Test theory | Part 1-5 |
| 6 | Linear combinations: Mathematical and statistical operations and test scoring | Part 1-5 |
| 7 | Test sensitivity | Part 2-10 |
| 8 | Midterm Exam | |
| 9 | Theory of error result and test reliability | Part 3-11 |
| 10 | Test validity | Part 3-11 |
| 11 | Prognostic and diagnostic validity | Part 4-16 |
| 12 | Factor analysis-part 1 | Part 4-17 |
| 13 | Factor analysis-part 2 | Part 4-17 |
| 14 | Construction of psychological tests: | Part 2-6 |
| 15 | Construction of psychological tests: | Part 4-16 |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| PSY329.1 | Course | Wednesday 18:00 - 20:50 | A F1.11 | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Monday | 15:00 - 18:00 | ||
| Thursday | 13:00 - 15:00 |
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes :
Midterm Exam
AI: Not AllowedAlignment with Learning Outcomes :
Assignment
AI: Not AllowedAlignment with Learning Outcomes :
Contribution to the class
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 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lecture Hours
42 hours ⏳ (14 week × 3 h)
Home study
10 hours ⏳ (5 week × 2 h)
Midterm Exam
35 hours ⏳ (7 week × 5 h)
Final Exam
63 hours ⏳ (9 week × 7 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 [PSY329] 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 Sep 09, 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 | |||||||||
| PSY329 | Psychometrics | 2 | 1 | 6 | ||||||
| Prerequisite | PSY103 | It is a prerequisite to | - | |||||||
| Lecturer | Pinar Unal Aydin | Office Hours / Room / Phone | Monday: 15:00-18:00 Thursday: 13:00-15:00 |
|||||||
| paydin@ius.edu.ba | ||||||||||
| Assistant | None | Assistant E-mail | ||||||||
| Course Objectives | Psychometrics is a very important subdiscipline of psychology as the maturity of any scientific discipline depends on the extent to which it has its own measuring methods and systems of measurement. This rule does not go round psychology. The goal of the course is to introduce students into basic principles of measuring psychological processes and development of psychological measuring instruments. It is expected that the students will get familiar with the principles of defining variables, constructing test items and assessing the measuring characteristics of tests and questionnaires. | |||||||||
| Textbook | Nunnally, J. C & Bernstein, I. H. (1997). Psychometric theory. Third Edition. McGraw Hill-Series in Psychology. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
| Teaching Methods | Class discussions with examples. Group workouts for engaged learning and continuous feedback on progress. Individual and grouped discussions. Visual and written materials will be supplied. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction, syllabus presentation, course presentation | - | ||||||||
| Week 2 | Definition of psychometrics: An Introduction to the theory of measurement-part 1 | Part 1-1,1-2 | ||||||||
| Week 3 | An Introduction to the theory of measurement-part 2 | Part 1-3 | ||||||||
| Week 4 | Multi-item measures | Part 1-3 | ||||||||
| Week 5 | Test theory | Part 1-5 | ||||||||
| Week 6 | Linear combinations: Mathematical and statistical operations and test scoring | Part 1-5 | ||||||||
| Week 7 | Test sensitivity | Part 2-10 | ||||||||
| Week 8 | Midterm Exam | |||||||||
| Week 9 | Theory of error result and test reliability | Part 3-11 | ||||||||
| Week 10 | Test validity | Part 3-11 | ||||||||
| Week 11 | Prognostic and diagnostic validity | Part 4-16 | ||||||||
| Week 12 | Factor analysis-part 1 | Part 4-17 | ||||||||
| Week 13 | Factor analysis-part 2 | Part 4-17 | ||||||||
| Week 14 | Construction of psychological tests: | Part 2-6 | ||||||||
| Week 15 | Construction of psychological tests: | Part 4-16 | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 40 | All LOs | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm Exam | 1 | 30 | All LOs | Not Allowed | |
| Assignment | 1 | 15 | All LOs | Not Allowed | |
| Contribution to the class | 1 | 15 | All LOs | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture Hours | 3 | 14 | 42 | Home study | 2 | 5 | 10 | |||
| Midterm Exam | 5 | 7 | 35 | Final Exam | 7 | 9 | 63 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 22/09/2025 | |||||||||