Date of Award:
5-2011
Document Type:
Dissertation
Degree Name:
Doctor of Philosophy (PhD)
Department:
Instructional Technology and Learning Sciences
Committee Chair(s)
Mimi Recker
Committee
Mimi Recker
Committee
Andrew Walker
Committee
Anne Diekema
Committee
Doug Holton
Committee
Xiaojun Qi
Committee
Nicholas Flann
Abstract
This research examined teachers' online behaviors while using a digital library service—the Instructional Architect (IA)—through three consecutive studies. In the first two studies, a statistical model called latent class analysis (LCA) was applied to cluster different groups of IA teachers according to their diverse online behaviors. The third study further examined relationships between teachers' demographic characteristics and their usage patterns. Several user clusters emerged from the LCA results of Study I. These clusters were named isolated islanders, lukewarm teachers, goal-oriented brokers, window shoppers, key brokers, beneficiaries, classroom practitioners, and dedicated sticky users. In Study II, a cleaning process was applied to the clusters discovered in Study I to further refine distinct user groups. Results revealed three clusters, key brokers, insular classroom practitioners, and ineffective islanders. In Study III, the integration of teacher demographic profiles with clustering results revealed that teaching experience and technology knowledge affected teachers' effectiveness in using the IA. The implication, contributions, and limitation of this research are discussed.
Checksum
7e969a994203488030dc13b5f89c753f
Recommended Citation
Xu, Beijie, "Understanding Teacher Users of a Digital Library Service: A Clustering Approach" (2011). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 890.
https://digitalcommons.usu.edu/etd/890
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Comments
This work made publicly available electronically on April 11, 2011.