 Hello everyone, I am Pauline Rooney, and I work in e-learning development with the Dublin Institute of Technology. OK, so to date our work in learning analytics has mainly focused on the VLE, which is Blackboard and DIT, and primarily at the module level on our postgraduate programmes within the Learning, Teaching and Technology Centre. For example, TELTA, our acronym for our fully online module on Technology Enhanced Learning and Teaching Assessment. So the data that we would have looked at today would include things like number of student logins, time of logins, resources accessed, student assignment submissions, student grades, digital badging or achievements as Blackboard calling. And our objectives in doing or looking at this data were threefold. Firstly, to identify at risk students and affect appropriate intervention in order to ease attrition and to support students through their learning. Secondly, to get an insight into students' online behaviours and their working practices within the VLE. And thirdly, to determine if there was a correlation between their online engagement within the VLE and their learning outcomes. And we haven't completed the empirical research in that area yet, but our initial glance at the data would seem to indicate a positive correlation between the two. So opportunities, first of all, and many of these we've already touched on this morning, but there's obvious potential for easing attrition by identifying at risk students, particularly in the earlier stages of a course, and there are also opportunities we find for empowering students. As part of our learning analytics work, we provide students with reports on their engagement, with analytical reports on their engagement in the online environment, and also anonymise summaries of their peers' engagement. And by doing so, we hope to give them an insight into their learning practices and also to allow them to compare how their own learning practices relate to their peers. And surprisingly, many students are surprised at their reports. There are also a lot of opportunities for cross-functional or departmental collaboration with a view to aggregating data across systems and departments within the institution. I know many of us have already touched on that this morning. But there are obvious challenges. First of all, access. We have access to the VLE data. That's straightforward. But accessing data across different systems within the institute, for example student registrations, is challenging at the minute, because we don't have aggregated systems at all. There is no synchronisation between those systems at the minute. Secondly, while we have access to the VLE data, making sense of that data in Blackboard and interpreting it requires additional analytical tools for which Blackboard charge handsomly, which has budget implications, resourcing implications. Secondly, there are challenges with regards to the collaboration across departments. I'm sure we're all familiar with those types of challenges. They're not only technical very much. Collaboration is challenging on many levels. There are resourcing issues. In order to progress our work in this area, we're really at the tip of the iceberg. In order to progress our work, we need time and we need staff to be able to focus on this as an institutional priority. We also need professional development for staff. That's one of the things I'll talk about in the next slide. We need to be able to educate staff on how to collate data, how to make sense of that data, and how to use that data to inform their own practice and to support students. That leads on to the final point. I think it's a challenge for all of us within our own centre is to remain data informed as opposed to data driven, whereby we're using the data to inform our practice and to ultimately enhance the student's experience and to enhance their learning outcomes, if you like. Keeping in mind that the data is only one part of a picture and that it's not the be all and the end all, if you like. What next steps would I like to take? First of all, I'd like to develop a DIT code of practice for learning analytics, which I think would be an important foundation for learning analytics practice across any institution, across the sector as a whole. It would, again, importantly take into account the legal and ethical issues which we're all grappling with. Secondly, I'd like to support the cross-functional collaboration, which will be necessary to develop the infrastructure and to share and aggregate the data across the institution as a whole. Finally, I'd like to initiate some kind of professional development for staff. Again, we're sitting on a mountain of data, but it's about basically helping staff make sense of that data. Again, I'm talking very specific at the minute, but helping students make sense of that data and use it to inform their own practice and to support students as they progress through college. Thank you.