Number of people who made a comment or contribution

Indicator Number: 
23
Category: 
Logic Model Component: 
Data Type(s): 
Count
Short Definition: 

Captures active sharing of programmatic experience and knowledge among people participating in KM outputs

Definition and Explanation (Long): 

This indicator captures active sharing of programmatic experience and knowledge among people participating in KM outputs—usually those hosted online, such as professional network groups, communities of practice, forums, webinars, or social media blogs or sites like Facebook or LinkedIn. The online format makes data collection easy by digitally storing comments and contributions such as postings or materials uploaded into a platform. The number of contributors indicates how many have interacted with the other users and have shared their personal experiences, knowledge resources, or opinions with others. This count helps the organizer to assess the depth of user engagement.

Data Requirements: 

Quantitative data from sources that provide the number of participants, electronic records of postings from participants, identification of product or issue under discussion, characteristics of participants such as country/region where they work, organizational affiliation, job function or type, gender, and level of education. Qualitative data from content analyses of comments and contributions that provide more detailed information about user characteristics, types, themes of contributions

Data Sources: 

Administrative records of comments posted via LISTSERVs, discussion groups, communities of practice, or social media tools

Frequency of Data Collection: 
Quarterly
Purpose: 
Counting attendance is a valid measure, but it does not indicate the degree of engagement. The total number of people in attendance includes people who contribute significantly, those who share a little, and those who listen without contributing, otherwise known as lurkers.
Issues and Challenges: 
Lurkers are usually the majority, especially in virtual settings. Direct user interactions indicate interest in the subject matter, which in turn speaks to the relevance of the KM output. In addition, contributions suggest that the users feel encouraged and comfortable contributing; thus, they have developed a sense of community and belonging in a particular group, which may stimulate further knowledge sharing. However, the indicator does not usually suggest how the user will use the information/product/output in the future or whether the information will continue to spread through the professional networks of the attendees and contributors.
Resources: 

For more information about Web analytics, see Appendix 5 on p.92.

Indicator Snapshots: 

During the LeaderNet webinar on blended learning, 275 participants logged on from 56 countries, sharing 308 posts in English, Spanish, and French.

As of June 2013, there were 7,924 subscriptions to 11 communities of practice managed by MEASURE Evaluation. During the project’s fifth year (July 2012 – June 2013), 273 subscribers posted new insights and knowledge to the community LISTSERVs.

In August 2013, MEASURE Evaluation shared a post on LinkedIn about the availability of M&E materials for trainers by MEASURE Evaluation. The post received 15 shares, 33 comments, and 16 likes in the Monitoring and Evaluation Professionals LinkedIn group. A blog post containing the same information received 21 Twitter shares and 16 Facebook shares.

Pages in the Guide: 
42-43
Published Year: 
  • 2013
Last Updated Date: 
Wednesday, September 6, 2017