User perceived learning from interactive searching on big medical literature data

Abstract

As in other fields, search engines have been heavily used as an information accessing tool for massive amount of medical literature data. This research investigates the user's learning during interactive searching process with the PubMed data, to find out what search behaviors would be associated with the user's perceived learning, and whether or not the user's perceived learning could be reflected in the existing search performance measures, so that such measures could also be used for indicating learning during searching process. The research used a data set collected by a research project on searching, which involved 35 participants at a major US university. The results show that the number of documents saved is significantly correlated with perceived learning for all search topics. None of the classical search performance measures is correlated with perceived learning. However, for specific topics, one of the performance measures, Recall, is significantly correlated with perceived learning. The results and the implications of the findings are discussed.