SPS602 Advanced Methods of Policy Analysis and Research
SPS602 Advanced Methods of Policy Analysis and Research
Syllabus | International University of Sarajevo - Last Update on May 05, 2026
Syllabus Quick Jump
Search and navigate to any syllabus instantly
Social and Political Sciences
Aliaksandr Novikau
Course Lecturer
Course Objectives
This doctoral seminar provides advanced training in the theories and methods of policy analysis and empirical policy research. Students will master frameworks for problem definition, alternative construction, and policy evaluation; develop expertise in quantitative, qualitative, and mixed-methods research designs; and learn to apply causal inference, program evaluation, cost-benefit analysis, and data visualization techniques. Emphasis is placed on producing rigorous, policy-relevant research suitable for academic publication, dissertation work, or high-level policy advising. The course prepares PhD students to design, execute, and critically evaluate policy research.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
1. Bardach, E., & Patashnik, E. M. (2023). A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving (7th ed.). CQ Press. 2. Weimer, D. L., & Vining, A. R. (2017). Policy Analysis: Concepts and Practice (6th ed.). Routledge.
Additional Literature
Rossi, P. H., Lipsey, M. W., & Henry, G. T. (2019). Evaluation: A Systematic Approach (8th ed.). Sage.Teaching Methods
Lectures
Intensive discussions of key readings
Hands-on method application workshops
Critical peer reviews of published studies
Data-analysis exercises
And student presentations
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction to Advanced Policy Analysis & Research Design | None |
| 2 | Defining Problems & Constructing Alternatives | Bardach Ch. 1–3 |
| 3 | Gathering Evidence & Selecting Criteria | Bardach Ch. 4–5 |
| 4 | Quantitative Methods I: Regression & Econometrics for Policy | Weimer & Vining Ch. 5–6; selected articles |
| 5 | Quantitative Methods II: Causal Inference | Angrist & Pischke excerpts |
| 6 | Qualitative Methods & Case Study Research in Policy | Selected qualitative readings |
| 7 | Mixed-Methods Designs & Integration Strategies | Creswell & Plano Clark excerpts |
| 8 | Midterm Exam | Review of material from Weeks 1–7 |
| 9 | Program Evaluation & Impact Assessment | Rossi et al. Ch. 1–4 |
| 10 | Cost-Benefit Analysis & Economic Evaluation Techniques | Weimer & Vining Ch. 7–8 |
| 11 | Data Sources, Big Data, Survey & Experimental Design | Selected advanced data readings |
| 12 | Ethics, Equity, Bias & Power in Policy Research | Ethics & equity articles |
| 13 | Communicating Policy Research: Briefs, Visualizations & Stakeholder Engagement | Bardach Ch. 6–8 |
| 14 | Critiquing Policy Studies & Meta-Analysis | Selected published studies |
| 15 | Student Research Proposal Presentations, Course Synthesis & Dissertation Applications | All above |
Course Schedule (All Sections)
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Monday | 14:00 - 15:00 | B F1.5 | |
| Wednesday | 11:00 - 14:00 | B F1.5 | |
| Thursday | 11:00 - 12:00 | B F1.5 |
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Participation
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Facilitation
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Quizzes
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Midterm exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Term project
AI: Consult InstructorAlignment with Learning Outcomes : 1 2 3
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:
Class hours
45 hours ⏳ (15 week × 3 h)
Home preparation
72 hours ⏳ (12 week × 6 h)
Midterm preparation
4 hours ⏳ (1 week × 4 h)
Final exam preparation
8 hours ⏳ (2 week × 4 h)
Term project preparation
21 hours ⏳ (3 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 [SPS602] 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 May 05, 2026 | International University of Sarajevo
Print Syllabus
Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| SPS602 | Advanced Methods of Policy Analysis and Research | 3 | 0 | 6 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Aliaksandr Novikau | Office Hours / Room / Phone | Monday: 14:00-15:00 Wednesday: 11:00-14:00 Thursday: 11:00-12:00 |
|||||||
| anovikau@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | This doctoral seminar provides advanced training in the theories and methods of policy analysis and empirical policy research. Students will master frameworks for problem definition, alternative construction, and policy evaluation; develop expertise in quantitative, qualitative, and mixed-methods research designs; and learn to apply causal inference, program evaluation, cost-benefit analysis, and data visualization techniques. Emphasis is placed on producing rigorous, policy-relevant research suitable for academic publication, dissertation work, or high-level policy advising. The course prepares PhD students to design, execute, and critically evaluate policy research. | |||||||||
| Textbook | 1. Bardach, E., & Patashnik, E. M. (2023). A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving (7th ed.). CQ Press. 2. Weimer, D. L., & Vining, A. R. (2017). Policy Analysis: Concepts and Practice (6th ed.). Routledge. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
| Teaching Methods | Lectures, intensive discussions of key readings, hands-on method application workshops, critical peer reviews of published studies, data-analysis exercises, and student presentations | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction to Advanced Policy Analysis & Research Design | None | ||||||||
| Week 2 | Defining Problems & Constructing Alternatives | Bardach Ch. 1–3 | ||||||||
| Week 3 | Gathering Evidence & Selecting Criteria | Bardach Ch. 4–5 | ||||||||
| Week 4 | Quantitative Methods I: Regression & Econometrics for Policy | Weimer & Vining Ch. 5–6; selected articles | ||||||||
| Week 5 | Quantitative Methods II: Causal Inference | Angrist & Pischke excerpts | ||||||||
| Week 6 | Qualitative Methods & Case Study Research in Policy | Selected qualitative readings | ||||||||
| Week 7 | Mixed-Methods Designs & Integration Strategies | Creswell & Plano Clark excerpts | ||||||||
| Week 8 | Midterm Exam | Review of material from Weeks 1–7 | ||||||||
| Week 9 | Program Evaluation & Impact Assessment | Rossi et al. Ch. 1–4 | ||||||||
| Week 10 | Cost-Benefit Analysis & Economic Evaluation Techniques | Weimer & Vining Ch. 7–8 | ||||||||
| Week 11 | Data Sources, Big Data, Survey & Experimental Design | Selected advanced data readings | ||||||||
| Week 12 | Ethics, Equity, Bias & Power in Policy Research | Ethics & equity articles | ||||||||
| Week 13 | Communicating Policy Research: Briefs, Visualizations & Stakeholder Engagement | Bardach Ch. 6–8 | ||||||||
| Week 14 | Critiquing Policy Studies & Meta-Analysis | Selected published studies | ||||||||
| Week 15 | Student Research Proposal Presentations, Course Synthesis & Dissertation Applications | All above | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 25 | 1,2,3 | Not Allowed | |
| Semester Evaluation Components | |||||
| Participation | 1 | 10 | 1,2,3 | Not Allowed | |
| Facilitation | 1 | 10 | 1,2,3 | Not Allowed | |
| Quizzes | 4 | 20 | 1,2,3 | Not Allowed | |
| Midterm exam | 1 | 15 | 1,2,3 | Not Allowed | |
| Term project | 1 | 20 | 1,2,3 | Consult Instructor | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Class hours | 3 | 15 | 45 | Home preparation | 6 | 12 | 72 | |||
| Midterm preparation | 4 | 1 | 4 | Final exam preparation | 4 | 2 | 8 | |||
| Term project preparation | 7 | 3 | 21 | |||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 27/05/2026 | |||||||||