Project description

The Internet has become indispensable when it comes to searching for information. Such an information search can be understood as a self-regulated learning process: Users of the Internet are expected to construct knowledge from what they find in the seemingly endless sea of data. The SALIENT project contributed to a better understanding of search as learning and developed methods to support the acquisition of knowledge through the Internet using ranking and retrieval algorithms.

While previous research on information retrieval has focused on information seekers' information needs, aspects such as learners' prior knowledge, and their learning intentions have received rather little attention (Hoppe et al., 2018). The SALIENT project contributed to closing this gap and developed a theoretical framework model to describe information search on the Internet as knowledge search (search as learning). In cooperation with the German National Library of Science and Technology (TIB) and the research center L3S, methods were developed to predict learning intentions and existing knowledge from user behavior during an Internet search (e.g., Yu et al., 2018; Shi et al, 2020). These methods were used to support Internet users in their knowledge acquisition. Particular focus was placed on learning with multimodal resources (Pardi et al., 2020) and on the possible emergence of "false security" during such self-regulated learning processes (von Hoyer et al., 2019).

Cooperations

• Leibniz Information Centre for Science and Technology and University Library (TIB)

• L3S Research Center

• Leibniz-Institut für Sozialwissenschaft GESIS

Website

Project Website: SALIENT