Adaptive Learning can lead to a significant increase in learning success and better learning outcomes. With the introduction of Adaptive Learning, success rates improve, and user engagement is higher, making it an attractive learning method.
The flexible Talent Development Software Totara TXP supports this with its three modules - Learn, Perform, and Engage. One particular strength of the platform lies in its ability to create learning paths and competency frameworks or even enable personalized learning through machine learning.
In Totara Learn, completion requirements can be set for each activity in the course (Scorm, Quiz, Assignment). Users have the option to mark the courses as completed themselves (manual criteria) or complete them automatically (automated criteria) based on the criteria set by administrators for the activities. At the end of the course, learners receive an overview of what they have already achieved and what is yet to be completed.
Courses in Totara Learn can be configured with restrictions, giving learners prescribed and controlled access to content. Fully adaptive paths are also possible, where different learners are presented with various activities and resources based on a set of criteria. By using these access restrictions, the interests and prior knowledge of learners can be taken into account when creating courses.
Totara allows the creation of longer learning paths through Programs and Certifications. These programs and certifications are organized into modules, allowing admins to determine whether learners need to complete one, all, or a specific number of courses in each set. The individual sets can be configured with "and," "or," and "then," making it ideal for onboarding programs. After onboarding, learners can continue with learning plans.
With Totara Perform, it is possible to regularly improve learners' performance through goals, OKRs (Objectives and Key Results), evidence, feedback, or competencies. Totara Perform enables competency-based learning through the creation of learning paths based on individual learners' competencies. These competencies can include soft skills such as communication, listening, teamwork, or specific skills related to a subject matter.
By assigning learning content and activities based on existing or even yet-to-be-acquired competencies, learners can work on their individual strengths and weaknesses. As Totara admins and managers, you can create learning plans for team members based on their prior knowledge and preferences, developing personalized learning concepts.
Competencies can be assigned directly to target groups, positions, organizations, or individuals. For example, if a group of employees needs the same competencies, such as all managers requiring a set of leadership competencies, this can be done quickly and easily. Users can also assign competencies to themselves. Progress in acquiring competencies can be continuously assessed by a manager.
Evaluation of employee performances by their respective supervisors can also be achieved through Totara Perform. At the end of the month, employees choose their assessor for their performance through a feedback form in the system. The selected assessor is then assigned the evaluation form, which is completed accordingly. The feedback forms with the responses can be exported, and employee performance can be regularly collected and analyzed.
A particularly powerful feature of the Totara Engage module is the Recommendation Engine, based on machine learning and artificial intelligence. This engine analyzes learners' behavior, preferences, and progress to generate personalized recommendations tailored to their individual needs, interests, and abilities. This makes it easier for Totara users to access relevant learning content and maximizes their development.
With Totara, you can empower your learners to progress at their own pace and according to their specific requirements, learning styles, and abilities. Discover together with LearnChamp how you can implement adaptive learning in your company.
