Salīdzināt metodes

	Logic Model Analysis	Outcome Mapping
Nozare	Public Policy	Public Policy
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2004	2001
Autors	Program evaluation field; popularised by United Way and the W.K. Kellogg Foundation	Sarah Earl, Fred Carden & Terry Smutylo (IDRC)
Tips	Visual planning and evaluation framework	Actor-centred planning, monitoring and evaluation approach
Pirmavots	W.K. Kellogg Foundation (2004). Logic Model Development Guide. Battle Creek, MI: W.K. Kellogg Foundation.	Earl, S., Carden, F., & Smutylo, T. (2001). Outcome Mapping: Building Learning and Reflection into Development Programs. Ottawa: International Development Research Centre (IDRC). ISBN: 9780889369597
Citi nosaukumi	Logic Model, Logical Framework Analysis, Program Logic, Logframe Analysis	OM, IDRC Outcome Mapping, Behavioural Change Mapping
Saistītās	4	4
Kopsavilkums	A logic model is a systematic, visual representation of how a program is understood to work: it lays out the logical relationships among the resources invested (inputs), the things done (activities), the products of those activities (outputs), and the changes expected to follow (outcomes and impact). Logic model analysis is the practice of building, examining and using these models to plan programs, guide implementation, and structure evaluation. Popularised by the United Way and codified in the W.K. Kellogg Foundation's widely used 2004 Logic Model Development Guide, it has become the workhorse framework of program planning and evaluation.	Outcome Mapping is a planning, monitoring and evaluation methodology developed by the International Development Research Centre (IDRC) and set out by Sarah Earl, Fred Carden and Terry Smutylo in 2001. It redefines results as changes in the behaviour, relationships, activities and actions of the people and organisations a program works with directly — its 'boundary partners' — rather than as downstream development impacts. By focusing on the behavioural changes a program can plausibly influence, Outcome Mapping addresses the attribution problem head-on and shifts evaluation toward learning and contribution.