Abstract

In context-based education, authentic situations ('contexts') are used as starting points for learning content matter ('concepts'). In this way, contexts provide significance and meaning to the concepts taught. The context-based approach has been investigated extensively in the field of science education.Context-based education has the potential to be a useful strategy in computer science (CS), in particular for teaching and learning of fundamental concepts. Initiatives like Informatik im Kontext confirm that context-based teaching and learning is a promising approach. So far, however, little research has been done on particular aspects of context-based learning in CS, such as the effective selection of contexts, principles for connecting concepts and contexts, and mechanisms for fostering knowledge transfer.This work-in-progress paper reports on an ongoing qualitative study on context-based teaching of fundamental CS concepts connected to algorithmic thinking. The study focuses on experiences and ideas of teachers, as they play a key role in the adaptation of contexts stemming from a rapidly changing field.We conducted semi-structured interviews with CS teachers on the above aspects of context-based teaching. The results reveal various ideas that teachers have on the use and effects of context-based learning and raises questions about the selection of contexts.

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