PSY329 Psychometrics
PSY329 Psychometrics
Syllabus | International University of Sarajevo - Last Update on Sep 09, 2026
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Psychology
Christian Valt
Course Lecturer
Course Objectives
Psychometrics is the scientific field concerned with the development and use of instruments for measuring psychological attributes. This course provides an introduction to psychometrics, focusing on the theoretical and statistical foundations of test construction, validation, and evaluation for the assessment of psychological, neuropsychological, and behavioral constructs in both healthy and clinical populations. Students will develop familiarity with core psychometric requirements and associated methodological challenges, and learn to address them using appropriate statistical software. Through active use and discussion of popular psychometrics tests, students will develop practical knowledge relevant to psychological research and assessment.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Furr, R. M. (2013). Scale Construction and Psychometrics for Social and Personality Psychology. SAGE publications.
Additional Literature
Furr, R. M. (2021). Psychometrics: an introduction. SAGE publications.Teaching Methods
Course delivery will be via lecture
Practice with psychometric analysis
And seminars about psychometric tests.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction, syllabus presentation, course presentation | - |
| 2 | Definition of Psychometrics: theory of measurement | Chapter 1 |
| 3 📍 | Definition of Psychometrics: type of measurements | Chapter 2 |
| 4 | Definition of Psychometrics: statistical foundations | Chapter 3 |
| 5 | Test dimensionality with factor analysis | Chapter 4 |
| 6 | Reliability | Chapters 5-6 |
| 7 | Validity | Chapters 7-8 |
| 8 | Midterm Exam | |
| 9 | Confirmatory Analysis: assessing test reliability and validity | Chapter 12 |
| 10 | Confirmatory Analysis: measurement of test invariance | Chapter 12 |
| 11 | Bias | Chapters 10-11 |
| 12 | Validation of translated psychometric test | |
| 13 | Summary and Discussion | |
| 14 | Group presentations regarding psychometrics analysis | |
| 15 | Group presentations regarding psychometrics analysis |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| PSY329.1 | Course | Thursday 09:00 - 11:50 | A F2.13 | - | - |
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
Group presentation
AI: Not AllowedAlignment with Learning Outcomes : 3 5
Contribution to the class
AI: Not AllowedAlignment with Learning Outcomes : 2 3
Quiz
AI: Not AllowedAlignment with Learning Outcomes : 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
45 hours ⏳ (15 week × 3 h)
Midterm Exam STudy
21 hours ⏳ (3 week × 7 h)
Final Exam Study
49 hours ⏳ (7 week × 7 h)
Group presentation
15 hours ⏳ (5 week × 3 h)
Quiz
10 hours ⏳ (5 week × 2 h)
Research activities and homework
10 hours ⏳ (10 week × 1 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, 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 | |||||||||
| PSY329 | Psychometrics | 2 | 1 | 6 | Thursday 9:00 - 11:50 | |||||
| Prerequisite | PSY103 | It is a prerequisite to | - | |||||||
| Lecturer | Christian Valt | Office Hours / Room / Phone | Currently not available |
|||||||
| cvalt@ius.edu.ba | ||||||||||
| Assistant | None | Assistant E-mail | ||||||||
| Course Objectives | Psychometrics is the scientific field concerned with the development and use of instruments for measuring psychological attributes. This course provides an introduction to psychometrics, focusing on the theoretical and statistical foundations of test construction, validation, and evaluation for the assessment of psychological, neuropsychological, and behavioral constructs in both healthy and clinical populations. Students will develop familiarity with core psychometric requirements and associated methodological challenges, and learn to address them using appropriate statistical software. Through active use and discussion of popular psychometrics tests, students will develop practical knowledge relevant to psychological research and assessment. | |||||||||
| Textbook | Furr, R. M. (2013). Scale Construction and Psychometrics for Social and Personality Psychology. SAGE publications. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
| Teaching Methods | Course delivery will be via lecture, practice with psychometric analysis, and seminars about psychometric tests. | |||||||||
| 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: theory of measurement | Chapter 1 | ||||||||
| Week 3 | Definition of Psychometrics: type of measurements | Chapter 2 | ||||||||
| Week 4 | Definition of Psychometrics: statistical foundations | Chapter 3 | ||||||||
| Week 5 | Test dimensionality with factor analysis | Chapter 4 | ||||||||
| Week 6 | Reliability | Chapters 5-6 | ||||||||
| Week 7 | Validity | Chapters 7-8 | ||||||||
| Week 8 | Midterm Exam | |||||||||
| Week 9 | Confirmatory Analysis: assessing test reliability and validity | Chapter 12 | ||||||||
| Week 10 | Confirmatory Analysis: measurement of test invariance | Chapter 12 | ||||||||
| Week 11 | Bias | Chapters 10-11 | ||||||||
| Week 12 | Validation of translated psychometric test | |||||||||
| Week 13 | Summary and Discussion | |||||||||
| Week 14 | Group presentations regarding psychometrics analysis | |||||||||
| Week 15 | Group presentations regarding psychometrics analysis | |||||||||
| 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 | 20 | 1,2,3 | Not Allowed | |
| Group presentation | 1 | 20 | 3, 5 | Not Allowed | |
| Contribution to the class | 1 | 10 | 2, 3 | Not Allowed | |
| Quiz | 5 | 10 | 4, 5 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture Hours | 3 | 15 | 45 | Midterm Exam STudy | 7 | 3 | 21 | |||
| Final Exam Study | 7 | 7 | 49 | Group presentation | 3 | 5 | 15 | |||
| Quiz | 2 | 5 | 10 | Research activities and homework | 1 | 10 | 10 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 28/09/2026 | |||||||||