Introduction to Program Evaluation - JSM678

• Title: Introduction to Program Evaluation
• Czech title: Úvod do evaluace veřejných politik
• Form of teaching: lecture+seminar
• Guaranteed by: Department of Public and Social Policy (23-KVSP)
• Faculty: Faculty of Social Sciences
• Actual: from 2025
• Duration in semesters: 1
• Semester: summer
• E-Credits: 5
• Examination process: summer s.:
• Hours per week, examination: summer s.:1/1, Ex [HT]
• Capacity: unknown / unknown (20)
• Maximum number of enrolled students: 20
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: taught
• Language: English
• Teaching methods: full-time
• Repeated enrollment: 2 / 2 / 1 / 2
• Note: course can be enrolled in outside the study plan; enabled for web enrollment; priority enrollment if the course is part of the study plan
• Guarantor: Mgr. Martin Nekola, Ph.D.
• Incompatibility : JSM654

Annotation

Are public programs working as intended? What are their real effects? Furthermore, are these effects meeting expectations, or could the resources spent be better used? These and other questions are being asked by the relatively young field of social science called program evaluation. As a practical activity, evaluation is vital to designing and implementing public policies and programs. Its main task is to provide reliable and useful information to managers, politicians, civil servants and other public policy actors. Program evaluation provides feedback on what works, under what conditions, and what activities need to be changed or discontinued.

This course serves as an introduction to the theory and practice of evaluation of publicly funded programs. Main aim is to develop basic conceptual knowledge about program evaluation with focus on the practical competencies for applying this knowledge. Students will be introduced to the main concepts, evaluation designs (plans) and methods of evaluation research, starting from program theory to evaluating the effectiveness of program effects and presenting evaluation results.

The acquired skills can be used in different positions within the public, private or non-profit sector (e.g., project manager, internal or external evaluator, policy analyst). Experienced evaluators from practice are involved in the teaching, and students learn on real evaluation projects. Graduates of the course should be able to:
• discuss the different purposes and types of evaluation of public programs;
• develop a complete evaluation project design to evaluate the impact of a specific public program;
• understand the main methods of effect evaluation and assess the effectiveness of the program;
• summarize and interpret the results of the evaluation;
• identify the social, political and ethical issues associated with evaluation.

Last update: Nekola Martin, Mgr., Ph.D. (30.03.2023)

Literature

Primary literature for the course

Mandatory

• Rossi, P. H., Lipsey, M. W., & Henry, G. T. (2019). Evaluation: a systematic approach (Eighth edition). Sage. Hereafter referred to as RLH 2019.

 

Recommended

• Robson, C. (2000). Small-scale evaluation: Principles and practice. Sage Publications.

 

Required literature is available for download in Moodle.

Last update: Nekola Martin, Mgr., Ph.D. (30.03.2023)

Syllabus

Topic 1: Introduction to the course and evaluation of public programs
Topic 2: Planning evaluations
Topic 3: Evaluation criteria and analysis of needs
Topic 4: Assessing program logic and theory of change
Topic 5: Program monitoring and process evaluation
Topic 6: Introduction to effect evaluation: design, internal and external validity
Topic 7: Evaluating effects: experiments in public policy
Topic 8: Evaluating effects: a quasi-experimental design
Topic 9: Analysis and interpretation of program effects
Topic 10: Evaluating effectiveness: cost-benefit analysis
Topic 11: Evaluation in the real world: social context, politics, and ethics

The use of AI tools

In this course, AI tools such as ChatGPT, Copilot, Claude, or similar technologies are permitted to support critical thinking and analysis. Specifically, AI tools may help prepare evaluation projects. Students are encouraged to use these tools for tasks such as:

• conducting research and literature reviews,
• brainstorming, especially in selecting and formulating policy programs,
• summarizing existing literature, and
• improving academic writing style and structure.

However, all uses of AI tools must be explicitly stated in accordance with the guidelines set by FSV UK and adhere to the broader ethical recommendations provided by Charles University. Students should carefully evaluate the information provided by AI tools and ensure that their final work reflects their own contribution and analysis.

Use of AI tools by faculty and opt-out option

AI tools may also be used by teachers for instructional purposes and for evaluating student work. Any use of AI tools will be done in a way that protects students' personal data. Student work will not be used to train AI models, and the instructor’s personal assessment will always supplement the AI-supported evaluation to ensure fairness and academic integrity. If students prefer that their work not be evaluated using AI-supported tools, they may opt out by sending a request via email to the course leader.

Last update: Nekola Martin, Mgr., Ph.D. (22.01.2026)