A web service framework for embedding discovery services in distributed library interfaces
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Characterizing user behavior in online social networks
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Does the technology acceptance model predict actual use? A systematic literature review
Information and Software Technology
Customizing science instruction with educational digital libraries
Proceedings of the 10th annual joint conference on Digital libraries
A typology of young people's Internet use: Implications for education
Computers & Education
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With the growth in operational digital libraries, the need for automatic methods capable of characterizing adoption and use has grown. We describe a computational methodology for producing two, inter-related, user typologies based on use diffusion. Use diffusion theory views technology adoption as a process that can lead to widely different patterns of use across a given population of potential users; these models use measures of frequency and variety to characterize and describe these usage patterns. The methodology uses computational techniques such as clickstream entropy and clustering to produce both coarse-grained and fine-grained user typologies. A case study demonstrates the utility and applicability of the method: it is used to understand how middle and high school science teachers participating in an academic year-long field trial adopted and integrated digital library resources into their instructional planning and teaching. The resulting fine-grained user typology identified five different types of teacher-users, including "interactive resource specialists" and "community seeker specialists" This typology was validated through comparison with qualitative and quantitative data collected using traditional educational field research methods.