Logic Model Component:
Measures the perceived quality of content in a KM output and its relevance to user needs
This indicator measures the perceived quality of content in a KM output and its relevance to user needs. “Content” means the information or knowledge conveyed in a KM output, as distinguished from format and presentation. “Relevance” indicates that intended users find the information or knowledge applicable and important to their professional work.
Quantitative data from responses to questionnaires regarding content quality, importance, usefulness, and relevance, etc.
User ratings can be collected using scales, such as a Likert scale, to gauge reactions to statements.
Qualitative data can provide greater insight into user experience, attitudes, and preferences.
Feedback forms or user surveys distributed with the product or after a KM output has been disseminated and promoted; interviews; focus group discussions
Please rate the following statements about the [Web product] content:
(1-Strongly disagree, 2- Disagree, 3-Not sure, 4-Agree, 5-Strongly agree)
o The content is complete, offering comprehensive coverage of [global health topic].
o The content is credible and trustworthy.
o The topics covered are relevant to my work.
o The information is of equal or higher quality than information on this topic I can find in other online resources (e.g., database, website, etc.)
o The information is of equal or higher quality than information on this topic I can find in print resources (e.g., books, journals, etc.).
The survey results of the LeaderNet webinar on blended learning revealed that 97% of respondents found the discussions useful or very useful for their work, and 99% rated the seminar resources (the Blended Learning Guide) as useful or very useful for their work.