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David Wand - Podcast Reviewing Somalia SRH GBV project Performance Measurement Framework 

Public Health Journal - December, 2024

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ORACLE NEWS DAILY - Article by George S. Tengbeh

IEG & World Bank Publication - October, 2024

Getaneh Gobezie - Two Blogs

EVALSDGs Insight Dialogue - October 23rd 2024

Value for Women Publication 2024

Webinar on lessons from “most significant change” method

Event Details

Webinar on lessons from “most significant change” method

Time: January 8, 2020 from 9am to 10am
Location: Online January 8, 2020 at 9 a.m. EST
Event Type: webinar
Organized By: Data for Impact (D4I) and USAID
Latest Activity: Jan 8, 2020

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Event Description

Join Data for Impact on January 8, 2020 at 9 a.m. EST for a one-hour webinar sharing lessons learned in using most significant change for evaluation.
Today, evaluations require methods that are flexible; allow for the complexity of current public health programming in low-resource settings; and address field challenges such as strict budget and time constraints, limited baseline data, and lack of access to comparison groups. Under these circumstances, the most significant change (MSC) method is a useful tool for evaluators.
MSC is a method for surveying diverse program stakeholders and participants with open-ended queries to gather their observations of important changes resulting from a program. MSC is useful when evaluating a program that must adapt to different or evolving contexts. It is appropriate when the evaluation seeks to learn and to show accountability. The MSC method helps evaluators to assess the performance of a program and show whether the program objectives were met.
In this webinar, you will learn how this method was adapted for public health evaluations in multiple contexts in Africa and Asia, including a case study on recent work in Uganda and Ghana for an evaluation of the Local Capacity Initiative, and review lessons learned from its implementation.

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Comment by Jenny Iao on January 7, 2020 at 21:43

To what extent verfication of results with non-implementing stakeholders is needed for having minimal robustness of evidence? How many sources or stakeholders are needed for one reporting change?

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