Leveraging student course enrollment data to infuse personalization in a library website
Summary (2 min read)
Introduction
- While academic libraries have previously offered customizable web sites, adaptive web site personalization through the integration of student data remains unexplored.
- This case study describes the implementation of a system that utilizes student course enrollment data to create adaptive personalization within the context of an academic library web site.
- Major challenges in the implementation of adaptive personalization include the development of an appropriate user model and accurate analysis of user browsing data.
Project outcomes and requirements
- The overall goal of the personalization project was to enhance the research experience and create a more user-centric library web site.
- The primary outcome was to develop a system that automated the process of connecting users with the library resources most relevant to their research needs.
- In order to maintain data security and user privacy, it was critical that the system utilize a reliable and secure user account management system.
- Users would not be required to create accounts, selfselect subjects areas, or login to additional systems.
- Lastly, it was essential that the system utilize existing open source applications and that it would not require significant investment of programming resources.
Developing a data model
- The effectiveness of a personalization system is dependent on the acquisition of pertinent user data and utilizing that information within the framework of a data model.
- To create the cross-references between courses and library primary subject areas, the authors setup a database table to link all course numbers with their relevant library subject areas.
- //drupal.org) is an open-source CMS offering a combination of features that make it an ideal candidate for building a web site personalization system, also known as Drupal (http.
- Within the context of the node system, it is possible to designate any number of node types, each with its own configuration and set of fields.
- While Drupal is capable of securing that type of information, those elements of user data provided no added benefit to the personalization system.
Importing user data
- Developing an efficient and sustainable process for loading student enrollment data into Drupal was critical to the project.
- In each of those modules, the import process includes uploading the data file, matching the file columns to fields, and automated batch-processing of data.
- By not requiring expertise in the areas of programming and database queries, this module helps reduce the cost of building and maintaining the personalization system.
- This module’s ability to interact with the campus LDAP system ensures sustainable and efficient management of user accounts within the library web site.
- Users must be able to view personalized data within existing Library pages while also having access to a personalized profile.
Project assessment
- Several assessment methods for determining the effectiveness of personalization are in-use or planned.
- This is useful for measuring when and where their users elect to visit Library e-resources.
- For the personalization project, this method of click-through tracking is offers data on whether users clicked on personalized e-resource links.
- Preliminary analysis of the usage data collected via the tools listed above indicates that students are using the personalized links on the Library home page.
- The use of course guides can vary greatly among academic departments.
Future directions
- The next phase of the personalization project will expand its scope to include a number of enhancements.
- One of these enhancements will add personalized elements that focus on specific user groups such as faculty, graduate students, and extended learning students.
- Faculty feedback has indicated that they would like to have easier access to the web site tools that they use most.
- This might include personalizing the homepage by adding links to forms that are for faculty-use only.
Conclusion
- For academic libraries, student course enrollment data is a vast source of existing user information that offers great potential for the personalization of online systems.
- Libraries and their parent institutions have made very limited efforts toward developing systems that integrate this user data to build intelligent web sites.
- It enriches the user experience while requiring no additional steps from students.
- A personalization project of this nature is an investment toward developing more user-centric library web sites and online services.
- This project brings into focus and opens the door for further investigation into the potential benefits of leveraging course enrollment data to enhance the delivery of library information resources and instruction.
Did you find this useful? Give us your feedback
Citations
78 citations
Cites background from "Leveraging student course enrollmen..."
...…have focused on customized information goods, such as recommendation systems (e.g., Parsons& Ralph, 2014; Ho& Bodoff, 2014; Lee, Jen-Hwa Hu, Cheng, & Hsieh, 2012; Zhang et al., 2011) or the information exchange environment and customized websites (e.g., Chan, 2014; Thongpapanl & Ashraf, 2011)....
[...]
4 citations
4 citations
Cites background from "Leveraging student course enrollmen..."
...Chan (2014) in turn put forth an interesting solution concerning the adaptation of a library’s web page to the needs of the users....
[...]
References
48 citations
43 citations
"Leveraging student course enrollmen..." refers background in this paper
...This investment has led to a great deal of research focusing on the assessment and improvement of academic library web sites (Brantley et al., 2006; Kim, 2011)....
[...]
42 citations
"Leveraging student course enrollmen..." refers background in this paper
...oft-cited benefits of personalization (Ketchell, 2000; Kumar and Benbasat, 2006; Liu, 2008; Wang and Yen, 2010; Lee and Cranage, 2011)....
[...]
...Improving web site ease-of-use and reducing information overload are two oft-cited benefits of personalization (Ketchell, 2000; Kumar and Benbasat, 2006; Liu, 2008; Wang and Yen, 2010; Lee and Cranage, 2011)....
[...]
39 citations
"Leveraging student course enrollmen..." refers methods in this paper
...The adaptive approach might also incorporate analysis of a user’s browsing and purchasing patterns (Forsati and Meybodi, 2010)....
[...]
39 citations