Personalised learning
Discover how ProLearn can improve your educational contentIncrease the success of learning with ProLearn
ProLearn technology shapes the didactic centre of the CMS component within the Edu-Suite software. By combining the power of ICT and successful learning strategies, ProLearn enables the development of personalised learning paths, resulting in an increased efficiency of learning.
Meet ProLearn, the AI-driven adaptive learning technology from Edu-Suite, in more detail below. Find out more about its 5 elements, its structure and the advantages on this page.
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The 5 elements of ProLearn
1. DOING JUSTICE TO DIFFERENCES
ProLearn combines the knowledge of both individual students and lesson material to support not only the student but also the teacher. The optimal alignment of lesson material increases the learning output of the student.
2. WORKING EFFICIENTLY
ProLearn saves the results achieved and uses them to personalise a student’s learning path. The system’s profile of the student (student model, outerloop) becomes more and more specific. Next tasks will be scheduled until a student has achieved the final goals.
3. WORK IN STEPS WITH HINTS AND FEEDBACK
Within the ProLearn technique, the student completes a task in different steps. During these steps, hints and feedback are given (research shows that this is a very effective teaching strategy) that are personalised as much as possible and focused on the student’s specific mistakes. Research shows that this kind of intelligent learning platform is almost as effective as a human tutor.
4. PERSONALISED LEARNING
The ProLearn technique provides an precise overview of a student’s knowledge and skills, which creates a personalised learning plan customised to the student. For selecting the ideal next task and achieving the highest learning yield possible, the system works with clear dashboards to support the teacher.
5. MEASURING MAKES LEARNING VISIBLE
Measuring is knowing. The ProLearn technology collects a large amount of data regarding students’ knowledge and skills. Not only does it include the theoretical knowledge and results of the tasks, it also measures and analyses how long a student has been online and how long they have been working effectively.
All of this data is displayed in a digital dashboard, which allows the teacher to see students’ progress. It provides an overview of problem areas, which helps a teacher to keep control of the learning process. Last but not least, the test item analysis allows the teacher to increase the quality and reliability of a test if required to increase the learning output.
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More about: the student model
ProLearn builds a ‘student model’ by collecting, combining and analysing multiple data sources.
With the knowledge pieces from the student model, ProLearn’s algorithms forecast the next step in the student’s learning path. The data these knowledge pieces are being constructed from originates from both the innerloop and the outerloop.
More about: the inner- and outerloop
The innerloop consists of data generated by the student’s results achieved in a learning path. The ProLearn algorithm transforms this data into personalised continuation steps. If necessary, ProLearn will make adjustments when necessary based on hints and feedback.
The outer loop consists of data that is generated when the student is working, like for instance work speed and how many times hints are requested. The profile the system creates of the student therefore gets more and more specific. All this data is used to customise the learning path.
Data is collected individually and per group and presented on clear dashboards. This data analysis gives both teacher and student, the insights which help to increase the learning performance.
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