Furthering the theory of Self-Organized Learning Environments - A complex system approach with big questions as the initial conditions catalyzing the self-organization of learners

Abstract

In an increasingly complex world, quality education should ensure that learners acquire knowledge and develop skills, attitudes, and values. Self-Organized Learning Environments (SOLEs) are a method for learning that supports all of the previously mentioned goals. The concept was developed based on experiments conducted outside of schools, which led to identifying learning as an emerging property of an inherently complex process.

Though SOLEs are nowadays used in schools worldwide as a complementary tool in education, the underlying mechanisms and the relevant conditions that lead to the success of SOLEs still need to be improved. The concept remains under-theorized which leaves it at the margins of education.

This thesis aims to harness the distributed knowledge and experience of practitioners using SOLEs and experts worldwide in the form of interviews and to take advantage of the information gathered by the startup StartSOLE in the form of a big question database. The interview findings suggest a framework to understand SOLEs in terms of a complex system, and the question database is analyzed to gain further insights into the features and quality of big questions.

In addition to that, the thesis explores SOLEs in terms of an Agent-Based Model. It shows that the Piaget-Vygotsky model for learning is insufficient to model the emergent features of SOLEs and that a different Agent-Based Model is needed to describe these.In specific, it makes the need for a further study of the fundamental interactions between participants in SOLEs explicit.

The thesis merges all insights gained from the mixed-method approach chosen for the topic in a Big Question for SOLEs framework that can support facilitators of SOLEs in defining a big question for their SOLEs.