Search Systems and Artificial Intelligence: Enhancing Searching as Learning Approaches to Counter Misinformation

Author:

Ghosh Souvick1,Gwizdka Jacek2,Lewandowski Dirk3,Reynolds Rebecca4,Rieh Soo Young2,Heck Tamara5,Imeri Aylin6

Affiliation:

1. San Jose State University USA

2. The University of Texas at Austin USA

3. Hamburg University of Applied Sciences Germany

4. Rutgers University School of Communication & Information USA

5. DIPF, Leibniz Institute for Research and Information in Education Germany

6. Heinrich Heine University Düsseldorf Germany

Abstract

ABSTRACTSearching as a learning process implies that learning occurs during a search process and might happens incidentally, influenced by the context the search takes place and the system that is used. Searching and learning are not isolated but co‐occurring events. Research investigates how search systems can be improved to foster learning processes, integrate information literacy enhancing methods and support user's sense‐making of information. Regarding the advancement of AI algorithms and their implementation in search systems, the concept of searching as a learning process can help to better understand human‐computer interactions and future information‐seeking processes. The panel advances current research on search systems for learning in non‐formal settings, with a focus on investigating the relation between searching and learning processes that influence people's understanding, assessing and use of information. It will focus on the contributions of information science research and the expectations of future searching behavior with respect to emerging advances in AI.

Publisher

Wiley

Subject

Library and Information Sciences,General Computer Science

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