Individualized Learning Through Non-Linear use of Learning Objects: With Examples From Math and Stat

Abstract

Our aim is to ensure individualized learning that is fun, inspiring and innovative. We believe that when you enjoy, your brain will open up and learning will be easier and more effective. The methods use a non-linear learning environment based on self-contained learning objects which are pieced together by a Hyperbolic Graph, or by the students themselves. This learning system makes it easy for students to find a path through the course material which suits his/her personal learning style and which makes learning more motivating, and efficient, and which leads to better learning. The methods have been tested in two case studies. One was a continuing education course in statistics for a global medical company, and the other was a “big” - both in terms of the number of students and in the number of ECTS points - introductory course in mathematics at a major technical university. The continuing education course made it possible for the company’s employees, from many different parts of the company and from all around the world, to learn from the same course. For the university course we started with a pilot project where our methods were used during only one course week. The pilot was a success and we then used the experiences from it to reshape the entire course. This course has now been running for 5 years and consistently receives very good evaluations, both from students and teachers. A clear finding from the test cases is that our learning method creates more motivation and makes the students use more time on the course and prepare better for the lectures. An important discussing point is how much “free choice” is best for the learners. We believe that the possibility to follow your own learning style by choosing between different types of material is important and ensures better learning and more motivation for all students, and that for the best students it also gives courage to go beyond the curriculum.