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How to Engage Stakeholder to Address Data Quality Issues in Outcome Monitoring

In this demonstration, we will introduce attendees to a participatory method of presenting findings that engages program implementers in a reflective process that highlights the importance of data quality

6 attachments

Focus Search - We can say that the changes identified occurred during the intervention and evaluation period of the program. 11 What When Why How Source: www.accionmutua.orgHow to Engage Stakeholders to Address Data Quality Issues in Outcome Monitoring Nidal Karim, PhD, CARE Adrienne Adams, PhD, Michigan State University Introduction Ice breaker Introduction Review Outcome Monitoring Process and Purpose OUTCOME MONITORING A Short Review What is Outcome Monitoring?


Library Entry
Eval11 Session 961: Definitions and Dashboards at Room to Read: Data Quality in an International Education Organization

This paper describes our experience in collecting, storing, analyzing, and reporting this information during the past three years: 2008: Developing a system for collecting, entering, cleaning, and analyzing indicator data; using multiple channels of communication between our headquarters and field offices. 2009: Getting definitions right; improving field-level ownership of data; streamlining communication with a single headquarters communication channel; explaining GI trends. 2010: Developing dashboards (online tools that show real-time performance and progress on key indicators) for communication of data quality issues; improving accountability for data timeliness and accuracy; comparing our internal program GIs with external data sources

2 attachments

Focus Search - Definitions and Dashboards at Room to Read: Data Quality in an International Education Organization www.roomtoread.org November 5, 2011 AEA Annual Conference Sri Lanka 2005 South Africa 2006 Zambia 2007 Bangladesh 2008 Tanzania 2011 Nepal 2000 Vietnam 2001 Cambodia 2002 India 2003 Laos 2005 Where We Work Cumulative Results, 2011: School Libraries: 12,522 Local Language Titles: 591 Schools Constructed: 1,450 Local Language Books: 6.0 M Girls on Scholarship: 13,667 Total Students Benefiting: 6.0 M Global Indicators Performance measures that show progress toward program objectives: • Collected for all programs in all countries • Collected for all active projects • 13 collected quarterly; 25 collected annually Examples: • Number of schools constructed • Number of local language books published • Number of books checked out • Number of girls who advance to the next grade Defining and Using Global Indicators Getting definitions right: • “Telephone” line from HQ to Country M&E Managers to Program Officers to field-level data collectors Internal and external use: • Improve current program performance and future program planning • Describe trends and implications of changes in programs over time • Demonstrate results • Provide context for numbers beyond our projects Project Database Our project database is important for three key stages of the global indicator process: • Data entry • Data quality checking • Data analysis Dashboards are used for all three stages Dashboard characteristics: • Graphic • Country-specific • Allow drill-down Dashboards: Data Quality Missing Library System Data How many 2009, 2010, and 2011 (established by 1 Oct 2011) RR/CRR projects are missing data in the Book classification system in place?


Library Entry
Eval11 Session 704: Healthy Eating and Active Living Survey Data Collection in the School Setting from Students – Response Rates, Data Quality, and Lessons Learned

One school jurisdiction chose the online medium and was not able to provide in-kind support, which resulted in poor response rate and data quality. The findings suggested that support from school stakeholders to facilitate survey data collection was the key factor for good response rate and data quality, not survey media

Stephenson AEA 2011 Presentation.pdf


Library Entry
Creating Cross-Agency Longitudinal Datasets for Education Research

The materials suggest strategies for obtaining and securing personally identifiable information, merging datasets without common identifiers, and overcoming common data quality issues with longitudinal datasets

2 attachments

Focus Search - Department of Education’s Privacy Technical Assistance Center (PTAC) offers up to date guidance and free training modules http://ptac.ed.gov/ Guidance from the Data Quality Campaign on FERPA compliance from a policymaker’s view http://www.dataqualitycampaign.org/find-resources/complying-with-ferpa-and-other-federal-privacy-and-security-laws-and-maximizing-appropriate-data-use/ Specific guidance for disclosure avoidance http://ptac.ed.gov/ptac-new-guidance-disclosure-avoidance-limiting-access-pii Information & Resources for DATA LINKING Steps for designing your own identity resolution software · Identify what data elements you have to match (SSN, name, address, etc) · Define the Exact and “Fuzzy” matching criteria




Library Entry
Eval12 Session 909: Evaluating Federally-Funded Multi-Site Behavioral Health Programs: Methodological Approaches and Lessons Learned

This document includes the four presentations that were delivered in this panel on Federally-funded multi-site behavioral health evaluations that focused on (1) conceptual approaches and issues, (2) implementation and data collection, (3) data management, and (4) data analysis and reporting....

Eval12 Session 909 - Presented 10-27-12.pdf


Library Entry
Session 738 Review of New Directions Issue on Environment

The New Directions volume (Birnbaum, Matthew and Per Mickwitz (ed.) 2009: Environmental Program and Policy Evaluation: Addressing Methodological Challenges, New Directions for Evaluation 123) is reviewed from the perspective of topics covered, concept of evaluand and the likely utility of the...

Review of Environmental Program and Policy Evaluation v2.ppt