手法を比較

	Most Significant Change for Development	Participatory Impact Assessment
分野	Development Studies	Development Studies
系統	Process / pipeline	Process / pipeline
提唱年	2005	2014
提唱者	Rick Davies & Jess Dart	Andy Catley and colleagues, Feinstein International Center, Tufts University
種類	Participatory, story-based monitoring and evaluation technique	Participatory project impact assessment method
原典	Davies, R., & Dart, J. (2005). The 'Most Significant Change' (MSC) Technique: A Guide to Its Use. CARE International, Oxfam, et al.	Catley, A., Burns, J., Abebe, D., & Suji, O. (2014). Participatory Impact Assessment: A Design Guide. Somerville, MA: Feinstein International Center, Tufts University.
別名	MSC technique, Story-based monitoring, Most significant change stories, Monitoring without indicators	PIA, Participatory Impact Evaluation, Community-Based Impact Assessment, Participatory Impact Measurement
関連	4	4
概要	The Most Significant Change (MSC) technique is a participatory, story-based approach to monitoring and evaluating development programmes that dispenses with predefined indicators. Developed by Rick Davies and elaborated with Jess Dart in their widely used 2005 guide, it works by systematically collecting stories of significant change from those closest to a programme and then filtering and selecting the most significant of them through deliberative panels at successive levels of the organisational hierarchy. The result is a structured, dialogical account of what stakeholders themselves judge to be the most important outcomes of an intervention.	Participatory Impact Assessment (PIA) is an approach to measuring the impact of development and humanitarian projects in which the affected communities define the indicators of change and use participatory tools to quantify it. Developed and codified by Andy Catley and colleagues at Tufts University's Feinstein International Center, largely through work on livestock and livelihoods programmes in pastoralist settings, PIA adapts participatory rural appraisal methods to the disciplined logic of impact evaluation — combining locally meaningful indicators with before-and-after and with-and-without comparisons to assess what a project actually changed.