An exploratory factor analytic approach to understand design features for academic learning environments

• Main Authors: Foo, Schubert, Theng, Yin-Leng, Lee, Shu Shing, Goh, Dion Hoe-Lian
• Other Authors: Wee Kim Wee School of Communication and Information
• Format: Conference or Workshop Item
• Language: English
• Published: 2009
• Subjects: DRNTU::Library and information science::Libraries::Information retrieval and analysis
• Online Access: https://hdl.handle.net/10356/91366; http://hdl.handle.net/10220/6128
• Institution: Nanyang Technological University

Subjective relevance (SR) is defined as usefulness of documents for tasks. Using digital libraries as examples of IR systems, this paper enhances objective relevance and tackles its limitations by conducting a quantitative study to understand students’ perceptions of features for supporting evaluations of subjective relevance of documents. Data was analyzed using factor analysis to identify groups of features that supported students’ document evaluations during IR interaction stages to provide design implications for an IR interface supporting students’ evaluations of documents. Findings seemed to suggest an implied order of importance amongst groups of features for each interaction stage. The paper concludes by discussing groups of features, its implied order of importance, and support for information seeking activities to provide design implications for IR interfaces supporting SR for academic research.