School Of Management Program Evaluation MPA 513 Week 3

School of Management Program Evaluation MPA 513 Week 3 School of Management Policy in the News Review Needs Assessment / Stakeholders Process Evaluations Exercise

Develop a comprehensive data collection plan for the future evaluation of the Summer Youth Employment Program (SYEP) implemented by the Mosholu Montefiore Community Center (MMCC). The plan should outline methodology, data sources, sampling strategies, and analytical approaches tailored to assess program processes, coverage, organizational functioning, and outcomes. Emphasize how the plan will address key questions such as service reach, quality, participant satisfaction, and program impact, integrating stakeholder perspectives and logistical considerations discussed in the course materials.

Paper For Above instruction

The evaluation of public programs is essential to ensure they fulfill their intended goals, operate efficiently, and adapt to changing needs. The Summer Youth Employment Program (SYEP) operated by the Mosholu Montefiore Community Center (MMCC) requires a systematic and rigorous data collection plan that captures essential process and outcome metrics. Such a plan not only facilitates accountability but also provides insights to enhance program effectiveness, especially in addressing youth unemployment, financial illiteracy, and educational engagement in low-income neighborhoods.

Strategic Framework for Data Collection Plan

Designing an effective data collection plan involves multiple components: identifying relevant data sources, selecting appropriate methodologies, determining sampling strategies, and establishing analytical procedures. The plan must align with the logic model previously outlined, which emphasizes inputs, activities, outputs, intermediate effects, and long-term outcomes. It must also incorporate stakeholder perspectives to ensure the data collected accurately reflects the program's functioning and impacts.

Methodological Approaches

The integration of qualitative and quantitative methods—a mixed-methods approach—provides a comprehensive understanding of the program. Quantitative data can include surveys, administrative records, and service utilization statistics, while qualitative data encompasses interviews, focus groups, and observational studies.

Quantitative Data Collection

Surveys administered to participants at multiple points—pre-program, mid-point, and post-program—can capture changes in employment readiness, financial literacy, and educational engagement. Administrative records from MMCC, the NYC Department of Youth & Community Development, and the NYS Department of Labor will offer detailed information on recruitment, attendance, placement rates, retention, and employment duration.

Sampling strategies should ensure representative coverage of youth from different neighborhoods, age groups, and demographic backgrounds to analyze disparities in participation and outcomes. A stratified random sampling technique will help in capturing diverse experiences, thus ensuring insights into potential over- or under-representation of specific groups.

Qualitative Data Collection

Focus group discussions and semi-structured interviews with program participants, staff, and stakeholders will provide nuanced understanding of participant satisfaction, perceived program quality, organizational challenges, and areas for improvement. Observational data collected during site visits can assess the quality of service delivery and organizational functioning.

Developing interview guides and observation checklists aligned with program objectives will facilitate consistent data collection. Thematic analysis of qualitative data will reveal patterns related to program strengths and weaknesses, behavioral changes, and contextual barriers.

Sampling and Data Management

To ensure data quality and representativeness, a multi-stage sampling procedure can be implemented. For instance, from the total participant pool, a random sample of participants will be selected for in-depth interviews and surveys. Additionally, key informants, such as program staff and community partners, will be purposively sampled.

Data management protocols will include secure storage, anonymization, and coding procedures to protect confidentiality. Regular data quality checks—validation and triangulation—are necessary to maintain reliability and validity of findings.

Analytical Techniques

Quantitative data will be analyzed through descriptive statistics, inferential tests (e.g., t-tests, chi-square, regression analysis), and comparison across demographic groups to identify disparities and measure change over time. Data visualization tools can enhance interpretation and stakeholder presentations.

Qualitative data will undergo thematic coding using software like NVivo or Atlas.ti. Thematic analysis will elucidate participant perceptions, organizational dynamics, and contextual factors influencing program success or failure.

Integration of findings from both data types will support comprehensive evaluation, guiding program improvements and demonstrating accountability.

Addressing Stakeholder Needs and Logistical Considerations

Engagement with stakeholders—program beneficiaries, staff, funders, and community organizations—will inform data collection priorities and dissemination strategies. Their insights ensure that the evaluation addresses relevant questions and produces actionable recommendations.

Logistical components include securing access to records, scheduling interviews, training data collectors, and establishing timelines aligned with program cycles. Budget considerations will influence the scope of data collection activities, emphasizing the importance of prioritizing high-impact metrics.

Conclusion

The proposed data collection plan offers a structured approach to evaluating the Summer Youth Employment Program's processes, coverage, organizational performance, and outcomes. By integrating mixed methods, stakeholder perspectives, and rigorous sampling strategies, the plan will generate reliable data that informs continuous improvement, demonstrates accountability, and advances the program’s mission of empowering youth and reducing inequalities in low-income communities.

References

• Bryman, A. (2016). Social Research Methods. Oxford University Press.
• Patton, M. Q. (2008). Utilization-Focused Evaluation. Sage Publications.
• Rossi, P. H., Lipsey, M. W., & Freeman, H. E. (2004). Evaluation: A Systematic Approach. Sage Publications.
• Fitzpatrick, J. L., Sanders, J. R., & Worthen, B. R. (2010). Program Evaluation: Alternative Approaches and Practical Guidelines. Pearson Higher Ed.
• Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Sage Publications.
• Centers for Disease Control and Prevention. (2011). Framework for Program Evaluation in Public Health. MMWR. Recommendations and Reports, 50(RR-11).
• Weiss, C. H. (1998). Evaluation. Prentice Hall.
• Scriven, M. (1991). Evaluation Thesaurus. Sage Publications.
• Patton, M. Q. (2012). Developmental Evaluation: Applying Complexity Concepts to Enhance Innovation and Use. Guilford Press.
• American Evaluation Association. (2018). Program Evaluation Standards: A Guide for Evaluators and Stakeholders. Wiley.