Learndash Adaptive Learning Pro

LearnDash Adaptive Learning Pro
With Adaptive Learning Pro, you can tailor a student’s education to their skill level, so they get the most benefit from your course.

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Add-on Requirements
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Current Version
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Last Update
5.8 or higher
WordPress Version
3.6 or higher
LearnDash Version
5.6 or higher
PHP Version
Add-on Overview & Features
The LearnDash Adaptive Learning Pro add-on puts flexibility at the core of your LMS site. Depending on each students’ existing skill level, you can adapt your course structure in a way that best sets each student up for success. By first determining students’ initial skill level through pre-requisite quizzes, you can then assign users at different course levels based on their performance. This way, students are placed on the right learning track from the very start, ultimately putting them on a better path to success.

Categorize your students by skill
You can assign different user roles to your students based on their performance on pre-requisite quizzes. For example, students that fail a previous quiz can be assigned to a beginner role, users with a grade between 75% and 90% can be assigned to an intermediate role and users with grades over 90% can be assigned to an advanced role.
Assign courses based on student’s level
Once students complete an initial evaluation and are categorized into different user roles, they can be assigned to different courses, based on their knowledge and skill level. By doing this, students are less likely to be overwhelmed by the content and assessments expected of them.

Configure the student’s level grading criteria
Once the student completes the quiz for the initial evaluation of the course level. The admin can set the grading criteria for the level from the following options i.e the final grade is the average (simple mean) of all quiz attempts, the final grade is the highest (best) grade of all quiz attempts, the final grade is the grade earned on the first attempt (other attempts are ignored) or the final grade is the grade earned on the most recent attempt only (other attempts are ignored) respectively.

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