Leveraging student course enrollment data to infuse personalization in a library website

Abstract

Purpose -The purpose of this paper is to describe the benefits of integrating personalization within a library web site and presents methodology for achieving this goal within an academic setting. Design/methodology/approach -The project documented in this study explores the use of student course enrollment data as the basis for creating a personalized library web site. Off-the-shelf, open source applications are used in conjunction with existing university data to deliver a final product that offers an enhanced user experience for the university community. Findings -Adaptive personalization is increasingly commonplace on the web. Academic libraries have a unique source of existing data that offers the potential of adding personalization to the library web site. At present, the personalization of library online services remains largely unexplored. This project illustrates one relatively low-cost method to help libraries interested in creating personalized web sites. Practical implications -This paper provides a guide for libraries interested in the implementation of personalization within their web sites. Originality/value -The project described in this case study is highly unique within libraries. The paper outlines the feasibility and technical requirements associated with using course enrollment data to add personalized content to a library web site.

Analysis of EZproxy server logs to visualise research activity in Curtin’s online library

“…In the United States, Coombs (2005) reports how the SUNY Cortland University used the EZproxy dataset to gain insights into online collection use. Chan (2014) discusses how student course enrolment data was merged with the EZproxy dataset at California State University to develop personalised e-library services. Lewellen et al (2016) describe how the University of Massachusetts Amherst used the dataset to investigate the use of e-books compared to print books.…”

“…Adding academic faculty information to the EZproxy dataset, such as student enrolment data by academic staff, by faculty, or by discipline area, would enable insights into information behaviour and resource use by these faculties. When we began this project we considered adding which faculty the user who sent a request came from, to see how different faculties used the online library, and if there were any major differences; however, as this data was not requested at the very start, we did (Chan, 2014;Coombs, 2005;Grace and Bremner, 2004) using EZproxy datasets indicate that different faculties use the library differently, with each having preferences for databases and eBooks, and different levels of use. Having such information would enable the provision of targeted e-library services like those reported by Chan (2014), and Grace and Bremner (2004, p. 164): for instance, the development of personalised library websites/portals for different disciplines.…”

“…When we began this project we considered adding which faculty the user who sent a request came from, to see how different faculties used the online library, and if there were any major differences; however, as this data was not requested at the very start, we did (Chan, 2014;Coombs, 2005;Grace and Bremner, 2004) using EZproxy datasets indicate that different faculties use the library differently, with each having preferences for databases and eBooks, and different levels of use. Having such information would enable the provision of targeted e-library services like those reported by Chan (2014), and Grace and Bremner (2004, p. 164): for instance, the development of personalised library websites/portals for different disciplines. Chan (2014, p. 453) reports how California State University San Marcos Library merged its student course enrolment data with the EZproxy dataset 'to develop a system that automated the process of connecting users with the library resources most relevant to their research needs', reporting that such services offer 'simpler pathways for accessing online resources and enrich the overall user experience'.…”

“…A literature review shows how other academic libraries handle their EZproxy data logs. Academic libraries from the UK (Sharman, 2017;Grace and Bremner, 2004) and the USA (Chan, 2013;Coombs, 2005;Lewellen et al, 2016) report their experiences working with EZproxy, how their findings assisted in improving their service and understanding of the usage patterns of their electronic resources. The Open University library reported using their EZproxy server data to evaluate their electronic resource subscriptions comprehensively and monitor resource usage trends by staff and students; the findings enabled them to measure the performance of their library services, and led to the development of performance indicators to measure their service quality and patron impact (Grace and Bremner, 2004, p. 164).…”

“…Scholarly findings about visualisations based on EZproxy data have been traditionally static 2D or at the most 3D graphs, as in the work by Bhaskar et al (2014), Coombs (2005), Chan (2013), Grace and Bremner (2004), Lewellen et al (2016), Murphy (2013Murphy ( , 2015, Morton-Owens and Hanson (2012) and Sharman (2017). Dynamic visualisations are uncommon in this field, but Archambault et al (2015, p. 1) argue that a framework for meaningful data visualisation has merit:…”