 The project today comes from Big Bang Analytics and they partnered with the Ministry of Education. Big Bang is a Victoria-based company whose goal is to help owners of big data access that data and make better informed decisions from it. They are eager to grow their business based on this project and they're looking forward to offer solutions to multiple markets based on their business intelligence needs. So, I would like to call up Robin Quinn and Chelsea Shalifor, Director of Analysis and Reporting at the Ministry of Education to join me on stage. So, I'm Robin Quinn. I'm a co-founder of Big Bang Analytics based in Victoria, a women-founded tech company which makes us a little bit off to the side, but very proud to be here. And I'm Chelsea Shalifor. I'm the Director for Student Outcomes Analysis and Reporting with our Education Analytics Branch in the Ministry of Education. So, one of the things we do at the Ministry of Education, as was mentioned in government, we collect a lot of information. We collect a lot of information about students and particularly we collect information about student outcomes. And with that information, we do a number of things, but one thing we do is we also share that information back with school districts. So, they give us information. We correlate it all and put it together and then share it back to them securely. And how we've been doing that, securely because there's a lot of personal identifiable information about students, individual students. So, we're very careful of how we share it. And so, we do it through SharePoint and we do it with Excel spreadsheets. And what we've found is that while we know there's really powerful information, there's a lot of information within that SharePoint site and in those spreadsheets. It doesn't seem to be used by districts very much. And we also know that we've really had a big disconnect with what school districts want from us around that information. What do they do? What do they need with information? And how can we help them to access that information? So, the other piece we also know anecdotally was that regardless of what they weren't doing, they were very frustrated with the SharePoint and the Excel spreadsheets. They required a very advanced tech type of data analyst to access it and school districts don't hire those people by and large. They maybe have one or two, but it's not an area that they have a lot of expertise in. And so, largely this wealth of information was being ignored. Yeah. It wasn't a very user-friendly system. So, for us, knowing the predictive power of that information and the wealth of resources of the data that was there, the mission for us is to really give superintendents a tool that can help them understand trends and patterns with their students and specifically on the outcomes of their students, how they're doing today, are they on track to graduate, that kind of thing. Giving them data in a format that they could actually apply and use in day-to-day operations versus a special request. So, one of the kind of foundation elements of our proposal was recognizing that a lot of technology and IT projects fail. And that's actually the basis of the startup and residence program in San Francisco. For us, we looked at it from the user perspective is that if you didn't talk to users about what you were designing as a solution for them, you were missing the point. So, we conducted in-depth interviews, user consultations with our five school districts that were part of the pilot project. And we asked them, what is it that you're looking for? How would you use this data differently? And that's, I just want to put a plug in here, we did this because of timing issues in the school year. We did our consultations in September, so we had nine weeks. And I should point out when we did our original inception, it was very telling the fact that when we looked at all this data that we had, and they said, what do you want to tackle first? We had no idea. We went, I don't know, what's most important? We couldn't really say and we went back and forth with a number of different ideas. It was very telling about how disconnected we were with really what school districts were using most. But we got great insight from them and we really took that. And Big Bang Analytics did an amazing job transforming that insight and their frustrations and their interest into what you see now. One of the things that they really wanted, first and foremost, we took a whole bunch of their feedback. And one of the things was to compare how they're doing against an aggregated provincial model. So what you see visually is their ability now not just to look at a spreadsheet with their data, but also to see the green line is their data. The gray line is the provincial data. So that's your provincial average as a whole. And that allows them to really see where they stand and what specific kind of elements should they be considering when they look at all this information. So just if you drill down and just to note some of the things we tackled, we looked at a couple of our six-year completion rates so that identifies our students graduating within a six-year period. We looked at the foundation skills assessment and specifically focused on grade four and grade seven reading. And so the first dashboard had all of that in one spot. You could see all of those different elements. Then if you drill down, here we're looking specifically into completion rates. And while it's much more simplistic than the big spreadsheets, they were like A to Z column. There's lots of information. None of that information is lost. It's now more dynamic. So now you have the same information visually represented and you can go and toggle over pieces and see the same information you had, but it makes sense. It's clear and you can pick out the things that you need. The other piece is custom filters. So what you see over on the side here, and this was a piece of feedback we heard, the province reports this information on student outcomes in a very prescriptive way. And for school districts, what they were looking for was a much more flexible way to identify certain cohorts of students for their needs. So we would report on all students. They only wanted to know about a subset of students at times. We would report specifically around, you know, all male-female. They would just want to pick and choose depending on their needs, depending on how their planning is going or interventions. They wanted to be able to select and deselect a number of different parameters around those students to get into how are the outcomes for this particular segment of our students doing. And then maybe tomorrow I need to know about a different segment of our students. And so this allows them to do that again without having to understand pivot tables and data selecting, which all of us in the data world like, but not everyone does. So it basically became very user-friendly to select the filters that you needed for that particular search. And you could drill down as specific as you needed to in those subpopulations. So essentially what we wanted to do was give the superintendents, but also teachers and principals an opportunity because this is what they asked for. When do we need to help? How can we help if we don't know where our students are at that space and time? So this particular visualization is allowing them, by student, and the data here is mass, they would see names. And they would say, you know, is this student at risk of not graduating? And then they can plan and they can set up some sort of intervention or action based on the information that they can see without having to go and try and gather up information or ask someone in IT to go in and check on a data source for them. So this to us was really the prime kind of answer to our user consultations is how can we use this data to help improve student outcomes? That's the bottom line. And so where do we go from here? Well, we are actively involved in our users and we've had a really good time working together in the co-development side of this thing. So, and I think that our first presentation when you said, you know, hey, it was great to say something we're doing is going to have an impact on people, on kids. So that is important to us. So we have the workshop sessions happening in December and January because we all know it's lovely to say fabulous technology. Here you go. Use it. Not going to happen. So we are going to go out with our pilot school districts and work with the users. So there won't be like one person who knows how to use this. It'll be a group of people. That's our goal. We're going to keep asking for feedback from everyone. And that includes the admin assistant who helps the superintendent track some information down. We know who the real users are and we recognize that. We're going to look at integrating new data sources into this next iteration. We're going to be building predictive capacity. So that means instead of looking at a situation where where can we help, we can kind of predict that the student might not graduate. We're going to look at even more predictive capacity. And I personally like to thank Chelsea and our team at the Ministry of Education for being so welcoming and patient with us as we go. Can we do it now? Can we like we want to do it now? And so they calmed us down and said, no, that's not going to happen. Well, and likewise, thanks to Robin and Katie for speeding us up because that's one thing I guess we seem to like to take our time. And the agile approach is fantastic in seeing results quickly and really getting to work on that iterative approach. As Robin said, we were able to build it with a pilot group of districts. We were able to take it back to those districts and some of them, you know, looked at that and gave us their feedback. And they were immediately excited and had far more questions and wanted to do even more. The first time you show them something, they went, this is fantastic. Can we go here, here and here now? So it's going to be a really great ongoing project. Thank you very much. That is fantastic. I, similar to the all day demo inception meeting I mentioned for the ARCIT project, we spent a day drinking coffee and working through and had a few moments where we decided, what are we really doing here? And we didn't decide, we called it. And it's so awesome to see how far this has come and see, yeah, definitely the lessons on all sides.