Micro-Learning: Do You Know Your Influencers?

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Micro-learning has become quite popular in modern learning and development organizations. This type of content is a great way to foster a culture of life-long learning. Measuring this is not only about surveying people who access this content, but also about understanding the users behind this access. If your measurement strategy doesn’t include understanding why people are using the content, and you are only focusing on what the survey says, you may be missing an opportunity.

So what does this mean? What types of metrics should you consider with micro-learning? If you have usage data, consider breaking it down into consumption, duration and behavior.

Consumption data is a measure of utilization of the informal learning tool or content. This answers the question around ‘how much’ was consumed. For example, if a library of content was uploaded to a technology tool that organized the content, but only 1% of the workforce accessed the content, that is relatively small consumption assuming the content is intended for the entire workforce.

Consumption data is important early on when using new tools and new modalities so that you can monitor adoption of this new type of learning. While consumption data will not tell you the impact the content had nor the quality of content, it does help you understand if it is getting visibility in your organization, and from a change management and culture perspective, that is important to understand.

Below are some examples of consumption key performance metrics that may be useful for informal learning tools:

Enrollment Rates

Access Rates

Completion Rates

Duration data is a measure of length of time. This answers the question ‘how long’ people were engaged with the tool and its content. For example, if a large percent of people access the tool for under 10 seconds before exiting it, that may indicate confusion or complexity and the notion that they have given up. Likewise, something that is intended for 5 minutes but people are in for 30 minutes may indicate mislabeled content or inaccurate categorization of what the learning objectives or intended audience may have been.

Duration data is important in the early use of the informal learning tool to understand if there is confusion or complexity or inaccurate categorization. It is also a valid measure to trend over time to see if actual duration is near expected duration goals, which would indicate the tool and related content are functioning as designed for the intended audience.

Below are some example of duration key performance metrics that may be useful for informal learning tools:

Average Duration Time in Tool

Average Duration Time in Module

Average Duration by Time of Day

Average Duration by Geo Location

Behavior is a measure of ‘where’ people went when experiencing the platform and its content. The learning path is important to measure because certain paths may be more efficient and effective than others. Likewise, certain paths may lead to higher impact or alignment to results, skills or objectives. Further, measuring behavior can help you understand if the learning path of a high performer is different than the learning path of everyone else.

Behavior as a measurement is of interest because the learners are often on their own experiencing the platform and its content. If the platform or its content are not intuitive and logical it can lead to a negative learning experience. This is increasingly important for platforms and content that are like a ‘choose your own adventure’ book whereby the learner chooses the path that is best for them or the system uses AI or machine learning to choose a path for them based on their profile or their prior behavior, consumption or duration data.

Below are some examples of behavior key performance indicators that may be useful for informal learning tools:

Most/least accessed content

Most popular pathway (one piece of content to another)

Pathway by Demographic (ex. high performers went from module A to C to J).

If you analyze consumption, duration and behavior data, you can identify influencers, which can be really important in the early phases of micro-learning usage. Influencers are those profiles that can build the learning culture and prompt the rest of the organization to engage with the content by understanding what others are doing.

Thank you,

The Performitiv Team

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