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Analyze learning behaviour

Learn how to interpret the analytics dashboard for insights on learning activities and user engagement.

Updated over a month ago

The analytics dashboard provides a comprehensive overview of learning activities, offering insights into user engagement and progress. This guide will walk you through accessing and interpreting the dashboard's features.

Who can use this feature?

  • Available for users with role Owner.
    Learn more about roles and permissions here.

  • Available on All Plans

  • Available on Desktop


Accessing the analytics dashboard

  1. Click on your profile picture located at the top right corner of the screen.

  2. From the dropdown menu, choose Administration.

  3. In the left navigation bar, click on Analytics.

Key performance indicators (KPIs)

In the summary section, the dashboard displays six KPIs that provide insights into learning activities:

  • Weekly active users: Number of users who were active on the platform in the last seven days.

  • Hours learned: Total hours spent on learning. This is calculated based on the total duration of completed learning materials and attended events.

  • Hours saved through personalization: Time saved by users through the personalization process in adaptive learning paths. This is calculated based on the total duration of materials that could be skipped by learners due to their previous knowledge.

  • Learning paths started: Total number of learning paths initiated by users.

  • Learning path completion rate: Percentage of learning paths that have been completed.

  • Average learning path progress: Average percentage of progress made in learning paths.

Note: The average learning path progress often gives a more accurate representation of learner success than the completion rate alone. While the completion rate only accounts for learners who finish 100% of the path, the progress metric reflects overall engagement and progress, even if the course isn’t fully completed.

For example, let's say ten learners start a learning path with a total duration of 50 minutes. On average, each learner completes 40 minutes, but none finish the entire path. Despite this positive engagement, the completion rate remains at 0%. However, the average learning path progress is 80%, offering a clearer and more meaningful insight into learner activity and success.

Active users graph

The active users graph shows the user activity per day and distinguishes between:

  • Daily Active Users (DAU): Users active on a specific day.

  • Weekly Active Users (WAU): Users active in the last seven days.

  • Monthly Active Users (MAU): Users active in the last 30 days.

Note: A user is considered an active user if she

  • started at least one material OR

  • completed at least one material OR

  • started at least one question OR

  • created/updated at least one user skill (e.g. by answering a self-assessment question) OR

  • signed up for an event/journey OR

  • canceled participation in event/journey

within the analyzed time frame.

Learning time graph

This bar chart displays the learning time per day, differentiating between:

  • Learning path time (blue): Sum of completed on learning materials.

  • Event participation time (orange): Time spent attending events.

Learning paths table

The table contains the following information and KPIs for each learning path in the organization:

  • Learning path title

  • Learning path type: Learn more about the different learning path types here.

  • Learning path provider

  • Learning paths started

  • Learning path completion rate

  • Average learning path progress

Mentoring hours graph

This visualization shows mentoring hours by day and type, such as chat or call. Note that this data is only available if the mentoring feature is actively in the organization.

Filter options

The dashboard offers three filter options to refine the underlying data:

  • Date filter: Select a date range for learning activities.

  • Team filter: Choose one or more teams to view activities specific to those groups.

  • User role filter: Filter by user roles. This is useful to exclude admin activities that may skew data. Learn more about user roles here.

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