When you have an expansive learning environment, it's easy to forget about individual needs of learners. Their personal learning patterns may differ from each other, which makes it important to track and curate the content they consume.
In Valamis, there are several ways to recommend content to a specific user.
On any page, you can add a special area that would show the courses relevant to the user.
This is based on Categories that are used in courses. Uncategorized content, naturally, will not be featured in the content recommendations, so make sure to create and assign appropriate and specific categories to your courses.
Whenever a user joins a categorized course, the system will note that as his interest and will start recommending such courses to them. The more they join the courses from the same category the more it will be prioritized.
From the start, when the user hasn’t joined any courses, the recommended courses come from the categories set up in the user profile, if there are any. Go to User Information - Categorization to set them up for a user.
If the user is inclined to check specific categories more, they will see new courses with such categories here. Initially, it will show a random selection of courses.
Aside from the Recommendation option, you can also display either the most popular content, trending weekly or monthly.
Besides lessons, training events, and courses, you can also feature learning paths and LinkedIn Learning courses as recommended or trending content. You can select multiple types of content at once.
You can select the option to ignore user history in the content recommendations, which will mean, for example, that the user will still see the lessons they’ve already passed.
The content is additionally filterable by category and vocabularies.
Recommend similar courses
A Similar courses portlet allows you to recommend the Courses similar to the one the user is currently on.
The similarity is derived from common course categories. If at least one category is shared, the course will be recommended here.
Just like in the recommendation ribbons, you can choose to either consider user completion history or ignore it, which will make it more random.
You can also limit the number of shown courses.
Valbo is our chatbot, based on IBM Watson technology. Valbo makes using the environment more natural by adding a conversational element to learning.
He is tailored and taught specifically to be relevant to your environment, which will make it seamless and intuitive to ask him questions related to your case - he will not look out of place, whatever the context is.
By your request, he can provide you lessons and training materials. For example, if you want to learn a new skill and tell Valbo about it, he will find relevant materials for you to view.
If the user joins a learning path and asks what to do next, Valbo will recommend other lessons from that learning path.
Valbo can also be integrated to Slack, which will allow you to ask him in Slack to create lessons from documents, and more.
With integrated Valbo, you can share and convert YouTube videos, PDFs, and PowerPoint presentations directly into Valamis lessons.