Enrollment is restricted to students in the School of Continuing and Professional Studies.
Conceptual frameworks and methods related to program evaluation will be covered including process, developmental, outcome, and impact evaluation. Students will be exposed to best practices to measure and document change on the individual, organizational, and macro level including the use of logic models. Quantitative, qualitative, and mixed methods design will be presented. Students will be exposed to analytical tools to interpret qualitative and quantitative data. The use of Big Data will be explored including the implications for behavioral change. Ethical issues in real world evaluation will be addressed.
Course Objectives 1. Describe the main conceptual frameworks used in program evaluation including process(formative), developmental, outcome and impact. 2. Compare and contrast quantitative, qualitative, and mixed methods design for program evaluation. 3. Evaluate best practices in relation to the measurement and documentation of change (individual, organizational, and macro-level). 4. Develop process and outcome objectives and logic models. 5. Interpret data including Big Data to make judgements about the efficacy of program activities and intervention. 6. Describe ethical dilemmas with real world research.
Conceptual frameworks and methods related to program evaluation will be covered including process, developmental, outcome, and impact evaluation. Students will be exposed to best practices to measure and document change on the individual, organizational, and macro level including the use of logic models. Quantitative, qualitative, and mixed methods design will be presented. Students will be exposed to analytical tools to interpret qualitative and quantitative data. The use of Big Data will be explored including the implications for behavioral change. Ethical issues in real world evaluation will be addressed.
Course Objectives 1. Describe the main conceptual frameworks used in program evaluation including process(formative), developmental, outcome and impact. 2. Compare and contrast quantitative, qualitative, and mixed methods design for program evaluation. 3. Evaluate best practices in relation to the measurement and documentation of change (individual, organizational, and macro-level). 4. Develop process and outcome objectives and logic models. 5. Interpret data including Big Data to make judgements about the efficacy of program activities and intervention. 6. Describe ethical dilemmas with real world research.