Document Type

Article

Publication Date

1-1-2025

Journal / Book Title

International Journal on Semantic Web and Information Systems

Abstract

This study examined how digital literacy influences user interactions with artificial intelligence–driven semantic search engines compared with traditional keyword-based search systems. The authors assessed whether an artificial intelligence–driven search enhances efficiency, query quality, and user satisfaction across varying digital literacy levels, in particular complex information retrieval tasks. Sixty participants, categorized into three digital literacy groups (beginner, intermediate, and advanced) on the basis of the European Commission’s Digital Competence Framework, completed six search tasks (three simple, three complex) using both traditional and artificial intelligence–driven search engines. Performance was measured by task completion time, query quality, and user satisfaction. Statistical analyses (analysis of variance, paired t tests) were conducted to compare outcomes across literacy levels and search engine types. Post-task interviews provided qualitative insights into user experiences.

DOI

10.4018/IJSWIS.380355

Rights

This article published as an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/)

Published Citation

Hu, B., Malik, I., Chen, Q., Xie, H., Sohail, N., & Attar, R. W. (2025). Bridging Digital Literacy Gaps With AI-Driven Semantic Search Technologies. International Journal on Semantic Web and Information Systems (IJSWIS), 21(1), 1-17. https://doi-org.ezproxy.montclair.edu/10.4018/IJSWIS.380355

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