Anderson and krathwohl's two-dimensional taxonomy applied to supporting and predicting learning during search

Abstract

There is a growing body of research in the Search as Learning community that recognizes the need for users to learn during search, but modern search systems have yet to adapt to support this need. Our research proposes three research goals toward addressing the support of user learning during search. Research goal 1 (RG1) introduces a more precise and reliable metric of assessing user learning. Anderson & Krathwohl's 2-dimensional taxonomy is used as a framework to develop learning objectives and assessment questions to measure user learning during search. Additionally, Anderson & Krathwohl's taxonomy is used as a coding scheme to outline the pathways users traverse along the way to a particular learning objective. Research goal 2 (RG2) investigates the prediction of learning objectives using behavioral measures. Finally, research goal 3 (RG3) proposes a search system that presents information relevant to the user based on their current learning sub-goal and scaffolds information based on the pathways they are likely to traverse given a particular learning objective.