Number/percentage of the intended users translating a KM output

Indicator Number: 


Logic Model Component: 

Data Type(s): 
Count, proportion
Short Definition: 
Measures how many intended users translate a KM output to suit the user’s context
Definition and Explanation (Long): 
This indicator measures how many intended users translate a KM output to suit the user’s context. “Translation” is a type of adaptation that refers to rendering written texts from one language into another. The demand for translations reflects the requesters’ assessment that the KM output would be useful and relevant to their local setting.
Data Requirements: 
Quantitative data from user self-reporting regarding translation, including identification of KM output translated, purpose and extent of translation, end results or outputs from translation, if known.
Data Sources: 
Self-reported user surveys (print, online, email, and telephone), requests to translate the product, requests for technical assistance with translation or funding to translate
Frequency of Data Collection: 
Translation can expand the reach and usability of a KM output by making it accessible to those who do not read/speak the language in which the output was originally created.
Issues and Challenges: 
It may be most common to translate outputs into widely used languages; still, other language versions can be important, particularly if needs for certain information/knowledge are particularly great among specific populations or in specific regions.
Sample Topics and Questions for Data Collection Instruments: 
Please indicate if you have adapted information from the [Web product] as follows. (Check all that apply.) o I have translated information from English into a local language. o I have adapted information to better fit the context I work in. o I have adapted complex information to make it simpler to use. o I have used content that I have adapted, or that has been adapted by others. Please give an example of how you have translated or adapted specific information from the [Web product] and used it in your work. (Open-ended.)
Indicator Snapshots: 
A 2017 paper evaluating MSH's internal Technical Exchange Networks (TENs) documented a 14 percentage point increase in intended users adapting or translating technical content sent through the communities of practice. The indicators was adapted to collapse adaptation and translation.
Pages in the Guide: 

Published Year: 

  • 2013
Last Updated Date: 
Wednesday, September 6, 2017