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

作者：Souvick Ghosh, Jacek Gwizdka, Dirk Lewandowski, Rebecca Reynolds, Soo Young Rieh, Tamara Heck, Aylin Imeri · 发表于：Proceedings of the Association for Information Science and Technology · 年份：2023 · DOI：10.1002/pra2.859 · 被引用次数：3 · 研究领域：Misinformation and Its Impacts、Information Retrieval and Search Behavior、Topic Modeling

ABSTRACT Searching 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.