 Hello everybody, my name is Vasim Akhtar and I am Head of Computing Faculty in Griffith College and I am Program Director for Masters in Big Data Management and Analytics. I supervise a number of data analytics projects and final year dissertation and I always use the domain, the data from higher education sector. I am almost about to finish my MBA with UCL at any moment. I am just checking emails, you know, any moment I will get the results. So this is kind of my PhDs in Computing Science but that MBA is in Higher Education Management. Now as part of that MBA I reviewed almost all GISC supported business intelligence and analytics projects in various UK universities. I reviewed a large number of dashboards as part of that work in many US universities also Purdue University Signal Project. I think everyone has looked at that. I have then completed a 360 review of GISC supported BI project in University of East London and the impact of the dashboards and that project on the local and wider community. I have completed a full consultancy project for a Russell Group University in the UK that how they should implement evidence based management. Basically they already have a GISC supported project there, they have some dashboards and now they want to take it to the next level. So that was my consultancy project. I keep engaging with IT services in Griffith College as we are developing and experimenting with various dashboards. My personal interest now is the moment I get that email from UCL that it's over. After that it's in institutional research. It's basically institutional effectiveness and mainly integrated institutional effectiveness that how we bring those models there are various areas and I'll come back and talk to you about those things. Again modeling individuals career development and progression and program level, department level and faculty level and then institutional level integrated effectiveness. Now opportunities exist on all levels. You are talking about monitoring individual students' performance, you are talking about the performance of a program, you are talking about performance of a faculty, a department and you are talking about strategic performance at institutional level. So there are opportunities. It's about developing right evidence base and presenting that at right time. Now it has already been said in various presentations, higher education institutions, we collect large number of data. And I think most of us after exam boards when we ship all the assessments to those containers over there and then some other dumping grounds, I should not be using that word but anyways so we collect all data that is there. So how we can actually use that data and create and develop evidence base that we can use to perform better at all various levels, challenges and then something that was actually said by the previous speaker at the end of the presentation. Now common vocabulary, common terms are coming out. Higher education institutions, complex organizations, small, big, no matter what size is there. These are complex organizations. Information and data exist in silos. This is my data. No matter how you do the integration, you will find somewhere over there in that corner that has his or her spreadsheet, no this is my data, I manage this process. Now if you want to bring that information in, so then the issue of data ownership, issue of personality class, I actually when I said that information and data exist in silos, I actually typed something else and then I removed with various attitudes. So various kind of attitudes towards information, ownership and that. And this research and this work is inherently multidisciplinary. How you deal with the challenge of multi-disciplinarity, that's another question. If you have people who are coming from teaching and learning, background and their areas are more like social science, the way they see information and if you have someone from IT services, they only design databases and provide you their view of data is totally different. So how you bring them together. So in my consultancy project, I think there was one chapter that focused on how you develop cross functional, multi-departmental, I came up with a very last term and I put it in the bowl, teams, how you do that, so these type of things. Another thing is we all do similar things, but we are unique also on many levels. So should we look for common vocabulary, should we strive for standardization or should we embrace diversity. So how we manage that, okay, measurability of learning outcomes, now thematic way, in a thematic way, in a descriptive way, we all measure learning outcomes, okay. But can we develop rubrics that can be then transformed into scorecards, okay. Now I want to talk kind of a data type of language here. So basically you have graphs, okay, a student, rather than you go and telling students where you are, what is your performance, student can see a graph, okay, that I have met that many learning outcomes of this program. So there are total 30 learning outcomes, I am there, this learning outcome, can we just get the data, we do this on a piece of paper when we evaluate this that this learning outcome have met, but can we do this using graphical kind of dashboards and all this. We all sit in exam boards, the academics who are sitting here with tons of kind of, you know, papers in, you know, in our hands and going through each student's performance. Can we have dashboards and all this. So improving and maybe reviewing the measurability of learning outcomes will actually give us that kind of ability to present that as kind of, you know, in dashboards, okay. Bringing people together, it's a right, it's step in right direction. Let us move on to next level. Setting up interest groups, maybe creating opportunity to work together, an annual conference, a publication. Okay, now another thing I just said a couple of seconds ago that like we do similar type of work, but we are unique also. We need to develop glossary of terms, we need to come up with definitions. When I did my, these just supported projects, I think there were 18 different universities. You go to one institution, their definition of engagement is slightly different than in other universities. Now, maybe this is the way it should be, but can we come up with a common theme and then we give that common theme to the various institutions, okay, and practitioners that you take it from here and then you build upon that, okay. Your engagement definition for your particular program in your environment could be slightly different, but you will get a common base. The problem that I have observed during my research is that that common base does not exist. People have a totally different view that what is engagement and sometimes I was surprised also. So, what should we measure? How we measure that, okay, a basic, you know, so what should we measure for student expectations? Student, we live in a very interesting age, okay, it's not that just measuring student expectations, sometimes managing student expectations is also a bigger challenge when student come to you with the expectations that you say that no, you have to do this thing to get the degree, okay, so this is part of the program, so how you do this, okay, right evidence base, right set of indicators, maybe this is where we can collaborate, okay, and then how these indicators kind of relate to each other, retentions. Retention is the biggest, it's a huge problem, particularly in my faculty, computing science, if you go in any institution, what retention indicators come from science programs, mainly from computing science program, that is a challenge for us, but sometimes reasons are so interesting, we did a survey, okay, a student left the program six weeks into the program and said, no, it's not for me, I'm going to open up, you know, a bicycle repair shop over there, so nobody told you before six weeks that this is not for you, and you just realize it, so basically, you know, where is this, you know, information, there is another thing that STEM careers, that's another area that, you know, people should move more into science education and all this, so there was a research done that in an area where there were regular STEM related seminars, any person who had attended just two seminars, there was 80% more probability that person will go into STEM careers, okay, so managing expectation, information, what they have before joining the college, okay, that has a huge impact on retention also, we need to develop common vocabulary, we need to develop common glossary and all this, okay, I think this is the next step that we should take, that's me.