New Material
Blog entry - 13th October 2021
This blog is a guest post from Gordon Otieno Wanzare, Board Chairperson, Evaluation Society of Kenya (ESK). It was originally published on EvalForward's blog. Evaluation use is a key issue for the evaluation community. The aim of evaluation is to be influential, so it should be of use to policymakers, programme developers, project planners and managers.
Blog entry - 15th September 2021
Effective monitoring is essential for managing performance, however, despite this, monitoring is often undervalued and understood quite narrowly. While the term “Monitoring and Evaluation” (M&E) is widely used, the monitoring function has not always benefitted from the same level of investment, professionalization and systems strengthening as the evaluation function. Instead, the monitoring function is often relegated to or viewed as a lower-level, technical function.
Blog entry - 09th September 2021
As of September 9th, BetterEvaluation’s inaugural CEO, Patricia Rogers has passed on the reins to the BetterEvaluation team and Mark Madden, the interim CEO. In this blog post, Patricia shares some of her highlights over the past 12 years.
Blog entry - 12th May 2021
Eleanor Williams is the Director of the Centre for Evaluation and Research Evidence at the Victorian Department of Health.
Resources - 12th May 2021
This paper explores the nexus of data science and evaluation, probing the issues and challenges of incorporating big data into evaluation practice.
Resources - 22nd April 2021
This paper provides detailed guidance on using big data to fill data gaps in impact evaluations. Data gaps can arise due to the inaccessibility of target populations, inadequate aggregation of data, data collection lag times, and data being missing in some contexts, like pandemics, conflicts, and humanitarian emergency situations. The paper includes a number of specific examples and additional references.
One issue to note when using the paper is that it uses the terms 'control group' and 'comparison group' inconsistently. The examples provided mostly refer to the use of comparison groups and quasi-experimental designs, not to randomly assigned control groups
