The effects of reading prompts and of post-reading generative learning tasks on multiple document integration: evidence from concept network analysis

Learning from multiple documents is an essential ability in today’s society. This experimental study used concept network analysis to consider how reading prompts and post-reading generative learning tasks can alter students’ documents integration performance. Undergraduates (N = 119) read three documents about Alzheimer’s disease with one of two reading prompts (integrative prompts vs. detailed prompts) and then after reading completed a generative learning task (concept mapping vs. summary writing). Three days later they completed a delayed writing task and an inference verification test. Participants’ written texts were converted to concept networks to evaluate conceptual level integration, including the quantity of integration (measured by the proportion of integrative links), the semantic quality of integration (measured by the similarity of integrative links), and the structural quality of integration (measured by comparing network graph centrality). Results showed that the integrative prompts relative to the detailed prompts enhanced the quantity of integration but not the semantic and structural quality. Further, concept mapping relative to summary writing significantly improved the structural quality of integration. In summary, this study describes a new concept network approach for measuring different aspects of integration to advance theory and research in multiple document comprehension.