Recommendations Improve the Search Experience (RISE)
Lead institution: Open University
Project home page: http://www.open.ac.uk/blogs/RISE/
That recommender systems can enhance the student experience in new generation e- resource discovery services.
This hypothesis was chosen quite carefully for a number of reasons. We've only recently implemented our Ebsco Discovery Solution aggregated search system so we are still in an evaluation stage and are really still assessing how students at the OU will get the best out of the new system. We have a particular perspective at the Open University in that the use that students make of our search systems varies widely from course to course. So we will particularly want to look at whether there is variation between the levels of students in their reaction to recommendations.
There is also a discussion of the method for evaluating the hypothesis .
It has shown that recommendations can be made from EZProxy data, that users like recommendations and that overall there is a value in showing recommendations to users of new generation discovery solutions.
As a distance-learning institution, students, researchers and academics at the Open University mainly access the rich collection of library resources electronically. Although the systems used track attention data this data isn‟t used to help users search. While library loans data was made available through the JISC MOSAIC project there is no comparable data available openly of e- resource use. RISE aims to exploit the unique scale of the OU (with over 100,000 annual unique users of e- resources) by using attention data recorded by EZProxy to provide recommendations to users of the EBSCO Discovery search solution. RISE will then aim to release that data openly so it can be used by the community. The project will also test the feasibility of deploying recommendations in the OU Google Apps environment and potentially into the institutional VLE by building a library search and recommendation Google Gadget.
The overall objectives of the RISE project are to:
- Establish a process to collect and analyse attention data about the use of electronic resources from the EZProxy proxy referral system.
- Create a recommender service using attention data to answer questions such as ‘people on my course are looking at these resources’
- Identify metrics to detect changes in user behaviour as a result of service use.
- RISE will create a personal recommendations service, MyRecommendations for OU users of the EBSCO Discovery Solution (EDS).
- It will explore issues (of anonymity, privacy, licensing and data format/ standards) around making this data available openly and will aim to release it openly so it can be re-used by the wider community in innovative ways.
- RISE will use the EDS API to create a Google Gadget for the OU Google Apps environment and will aim to test in the OU Moodle Virtual Learning Environment (VLE) using features developed by the JISC DOULS project.
- RISE will evaluate the pros and cons of providing recommender data to students of an e- resource discovery service.
- Overall RISE will provide the wider community with an example of the benefits to users of discovery solutions of using e-resource activity data, will aim to make that data available to the wider community, and will provide a tool that can be adapted and reused.
- Process EZProxy log
- Provide course based recommendations
- Provide relationship based recommendations
- Search term based recommendations
The project suggests the following further work.