Search, sense making and learning: closing gaps
PurposeThis paper aims to discuss how search, sense making and learning have become more closely integrated, as search services have leveraged new technologies and large and media-diverse data streams.Design/methodology/approachThe paper reviews progress in search over the past 60 years, summarizes different theories of sense making and learning and proposes a framework for integrating these activities.FindingsThe arguments are supported with examples from search in 2018 and suggest that even as search becomes an automated process during learning, search strategies must continue to evolve to insure that complex information needs can be met.Research limitations/implicationsThe work is limited to search that uses electronic search systems. Implications include the need to understand that multiple levels of system inferences/estimates are used to present search results and that different kinds of learning processes are affected by search systems.Social implicationsThe importance of information literacy is implied.Originality/valueThis paper will provide readers with an understanding of how search services and systems have evolved and their implications for human learning.