Deep Learning in Open Source Learning Streams

This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized and contrasted to the notion of functionalistic learning in a digital context. The mechanism that enables deep learning in this context is ‘The Open Source Learning Stream’. ‘The Open Source Learning Stream’ is the notion of sharing ‘learning instances’ in a digital space (discussion board, Facebook group, Twitter hashtags etc.). The ‘learning instances’ are described as mediated signs of learning expressed through text in the stream that is further developed by peers and by the teacher. The expressions of ‘learning instances’ are analyzed and categorized according to whether it expresses prestructural, unistructural, multistructural or relational learning. The research concludes that ‘The Open Source Learning Stream’ can catalyze deep learning and that there are four types of ‘Open Source Learning streams’; individual/ asynchronous, individual/synchronous, shared/asynchronous and shared/synchronous. The research also makes suggestions as to how teachers can make instructional designs that catalyze deep learning in a digital learning environment.