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Current instructional methods widely support verbal learning through linear and sequential teaching materials, focusing on isolated pieces of information. However, an important aspect of learning design is to facilitate students in identifying relationships between information. The transformation of linearity in teaching resources into integrated network models such as concept maps facilitates effective knowledge organisation by constructing relationships between new and existing knowledge. However, the manual construction of concept maps from teaching materials places an additional workload on the academics involved. Consequently, this research investigates the effectiveness of automated approaches in extracting concept maps from lecture slides and the suitability of auto-generated concept maps as a pedagogical tool. We develop a set of Natural Language Processing (NLP) algorithms to support concept …