Módszerek összehasonlítása

	Participatory Evaluation	Most Significant Change
Tudományterület	Public Policy	Public Policy
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	1998	2005
Megalkotó	J. Bradley Cousins & Elizabeth Whitmore	Rick Davies & Jess Dart
Típus	Collaborative, stakeholder-engaged evaluation approach	Participatory, story-based monitoring and evaluation technique
Alapmű	Cousins, J. B., & Whitmore, E. (1998). Framing participatory evaluation. New Directions for Evaluation, 1998(80), 5–23.	Davies, R., & Dart, J. (2005). The 'Most Significant Change' (MSC) Technique: A Guide to Its Use.
Alternatív nevek	Collaborative Evaluation, Stakeholder-Based Evaluation, Practical Participatory Evaluation	MSC, MSC Technique, Story-Based Monitoring, Davies-Dart Most Significant Change
Kapcsolódó	4	4
Összefoglaló	Participatory evaluation is a family of approaches in which stakeholders — program staff, beneficiaries, community members — are engaged as active partners in conducting the evaluation rather than as passive subjects of it. In their influential 1998 framing, J. Bradley Cousins and Elizabeth Whitmore distinguished two streams: practical participatory evaluation, oriented to improving program decisions and use, and transformative participatory evaluation, oriented to empowerment and social justice. What unites them is shared control of the inquiry, but they vary along dimensions of who participates, how much control they hold, and how deeply they are involved.	The Most Significant Change (MSC) technique is a participatory, story-based approach to monitoring and evaluation developed by Rick Davies and refined with Jess Dart. It involves the systematic collection of stories of significant change from the field and the deliberative selection of the most significant of these by panels of stakeholders. There are no predefined indicators; instead, value judgements about what change matters most are made transparently by those involved, making MSC especially suited to capturing unexpected and qualitative outcomes in complex programs.