Assuming my projects haven’t been cut out at the final acceptance stage because I haven’t yet submitted a revised project plan,
As OU courses are increasingly presented through the VLE, many of them opt to have one or more “Library Resources” pages that contain links to course related resources either hosted on the OU Library website or made available through a Library operated web service. Links to Library hosted or moderated resources may also appear inline in course content on the VLE. However, at the current time, it is difficult to get much idea about the extent to which any of these resources are ever accessed, or how students on a course make use of other Library resources.
With the state of the collection and reporting of activity data from the VLE still evolving, this project will explore the extent to which we can make use of data I do know exists, and to which I do have access, specifically Google Analytics data for the library.open.ac.uk domain.
The intention is to produce a three-way reporting framework using Google Analytics for visitors to the OU Library website and Library managed resources from the VLE. The reports will be targeted at: subject librarians who liaise with course teams; course teams; subscription managers.
Google Analytics (to which I have access) are already running on the library website and the matter just(?!) arises now of:
1) Identifying appropriate filters and segments to capture visits from different courses;
2) development of Google Analytics API wrapper calls to capture data by course or resource based segments and enable analysis, visualisation and reporting not supported within the Google Analytics environment.
3) Providing a meaningful reporting format for the three audience types. (note: we might also explore whether a view over the activity data may be appropriate for presenting back to students on a course.)
The OU Library has been running Google Analytics for several year, but to my knowledge has not started to exploit the data being collected as part of a reporting strategy on the usage of library resources resulting from referrals from the VLE. (Whenever a user clicks on a link in the VLE that leads to the Library website, the Google Analytics on the Library website can capture that fact.)
At the moment, we do not tend to work on optimising our online courses as websites so that they deliver the sorts of behaviour we want to encourage. If we were a web company, we would regularly analyse user behaviour on our course websites and modify them as a result.
This project represents the first step in a web analytics approach to understanding how our students access Library resources from the VLE: reporting. The project will then provide the basis for a follow on project that can look at how we can take insight from those reports and make them actionable, for example in the redesign of the way links to library resources are presented or used in the VLE, or how visitors from the VLE are handled when they hit the Library website.
The project complements work that has just started in the Library on a JISC funded project to making journal recommendations to students based on previous user actions.
The first outcome will be a set of Google Analytics filters and advanced segments tuned to the VLE visitor traffic and resource usage on the Library website. The second will be a set of Google analytics API wrappers that allow us to export this data and use it outside the Google Analytics environment.
The final deliverables are three report types in two possible flavours:
1) a report to subject librarians about the usage of library resources from visitors referred from the VLE for courses they look after
2) a report to librarians responsible for particular subscription databases showing how that resource is accessed by visitors referred from the VLE, broken down by course
3) a report to course teams showing how library resources linked to from the VLE for their course are used by visitors referred to those resources from the VLE.
The two flavours are:
a) Google analytics reports
b) custom dashboard with data accessed via the Google Analytics API
Recommendations will also be made based on the extent to which Library website usage by anonymous students on particular OU courses may be tracked by other means, such as affinity strings in the SAMS cookie, and the benefits that may accrue from this more comprehensive form of tracking.
If course team members on any OU courses presenting over the next 9 months are interested in how students are using the library website following a referral from the VLE, please get in touch. If academics on courses outside the OU would like to discuss the use of Google Analytics in an educational context, I’d love to hear from you too:-)
eSTEeM is joint initiative between the Open University’s Faculty of Science and Faculty of Maths, Computing and Technology to develop new approaches to teaching and learning both within existing and new programmes.