Maine Narrative: Using Data to Tell a Story in the Pine Tree State

A Date with Data

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### Episode Transcript ###
00:00:01.66 >> You're listening to "A Date With Data" with your host, Amy Bitterman.

00:00:07.48 >> Hey, it's Amy, and I'm so excited to be hosting "A Date With Data." I'll be chatting with state and district special education staff who, just like you, are dealing with IDEA data every day.

00:00:19.64 >> "A Date With Data" is brought to you by the IDEA Data Center.

00:00:24.71 >> Well, welcome to "A Date With Data." On this episode, I am joined by a whole group of folks from the Maine Department of Education, and they're going to be talking about how they have been working to improve their IDA data quality and also really use their data to tell their state story, so I'm so excited to have all of you with us. And I'm going to start things off with Erin Frazier, the State Director of Special Services, birth to 22, and she's really going to kind of set the stage and tell us about Maine's IDEA data priorities.

00:00:57.05 >> Well, thank you so much for having us. I have to say that I brought my entire team here because we all have a place in data, and we are very excited about data. We have a lot of XM and enthusiasm about how we are moving forward with our data journey, and just to set the stage a bit, I came to the Department of Education right before the pandemic, and so about 4 months before the pandemic, and so my first 2 years were really focused on that crisis that occurred in education and specifically in special education, and so it's been more recently that we've been looking at data and looking at our SSP/APR data to look and goal-set for our state. We want to use data effectively in Maine to tell the story off special education in our state, especially the story of inclusive education and how we're doing with least restrictive environment, and we are just very, very excited about all of the data and how we're going to be using it moving forward, so with that said, that sets the stage for you. I'm going to pass it to my Data Manager. My team will introduce themselves as they speak.

00:02:09.13 >> Hi, so I'm Shawn Collier. I'm the Data Manager. A lot of my work has been guided by a pretty powerful quote by Emil Faber, who, as you may know, is the founder of Faber College if you've ever seen the 1970s movie "Animal House," the famous documentary on college life.

00:02:27.61 >> Right.

00:02:28.85 >> And so in the beginning of the movie, we see this picturesque view of the campus, stately buildings, and then the camera pans onto a statue of Emil Faber and then focuses on his famous quote that's inscribed below with the profound words that he intended to guide all the students who passed through the halls of Faber College, which is, "Knowledge is good." So with this profound quote ... Okay, so it wasn't a documentary, and I'm making a joke, but it actually does relate to my work and my focus, so for my part, I'm primarily focused on the most fundamental aspects of building a healthy data culture, and I think there are two main areas. One is data quality, and the other is data use. So my background in cognitive psychology research and teaching, because of that, I look at my work through kind of a research and science lens for the most part, so I see data quality and data use as relating to two main research areas that they call basic research. Sometimes it's called pure science. And the other is translational research or applied science. Basic research is understand what is. What exists in the world? How do things work? So this is the Emil Faber "knowledge is good" level of focus.

00:03:45.76 This is where we want to ensure that the data we gather and report are accurate, and so this is where we put a lot of work into data quality, and then we have the data-use level, which is translational research or what they call applied-science level where we look at how the data can be applied to improve outcomes, and translational research data use has to build on the pure research that focuses on data quality. So the data-quality level is my primary focus right now, and this involves a number of things. We're critically reviewing our trainings. We're looking at the needs of folks in the field who are entering and coding the data. We're critically looking at data definitions to make sure they're clear, making sure they're communicated in those trainings, and we're trying to be more proactive looking at the data that's being collected as it comes in. For instance, we're starting to be more proactive about looking at those year-to-year differences and following up with the districts instead of waiting for OSEP to issue those year-to-year reports. There's also a lot of focus right now on using those IDC data protocols to make the data processes explicit. I think this is one of the most single most best things we've done at that fundamental level. They're really great tools. I think we have all the 618 data collections documented using those protocols now.

00:05:09.21 >> Great.

00:05:09.50 >> And we'll be working to add to our APR indicators next. I'd also like to include in those protocols how the various data sets are used. For instance, a lot of child-count files are used for disproportionality, and I think that even if most people involved in those protocols aren't directly related, involved in those analyses, it's a stronger data culture when everyone's aware of their use, and some might even be prompted to think of ways they can contribute to those analyses in their own role. Let's see. The data protocols have been especially helpful because we have a lot of new folks on the data team. We have a brand-new [Indistinct] Coordinator who's climbing a really steep learning curve, and we have a brand-new position also, Data Quality Coordinator, and that person's role has been great at revising the trainings and has been laser-focused on data quality. So, yeah, with the help of a lot of talented folks, we've been building a data culture with a strong focus on data accuracy and reliability.

00:06:15.74 >> Wow. Well, it sounds like there's a lot of really great working going on, and I liked how you talked about the kind of the quality piece, but then it's really a building block to data use. You really have to have the quality there in order to have usable, meaningful data.

00:06:31.32 >> Oh, absolutely.

00:06:32.89 >> Thanks, Shawn.

00:06:34.25 >> Next, we have Tracy Whitlock. Go ahead and introduce yourself, Tracy.

00:06:38.47 >> Hi, Amy. Hi, everyone.

00:06:39.83 >> Hi.

00:06:39.89 >> I'm Tracy Whitlock. I coordinate special projects out of the Office of Special Services and Inclusive Education. The work I do includes our math project, which is part of our ESEP. We do PBIS work, transition work, dyslexia work, but our biggest work and projects that we're doing right now relate ... All of those relate to data, but in particular, this one is focused on data. I can't help but think of Shawn and, "Knowledge is good." For me, I think college movies ... I can't help but think about "Monster University" instead and just keep saying that we're okay, but okay with data and thinking about, what is that we know about the data that we have, and what do we do with it? So we can talk about the data. We can look at the numbers. I think in state government sometimes and in other organizations we might admire the data, admire the issue that you find, but what do you do with it? And so one of the things that we're really trying to move towards is thinking about in particular our LRE data, so we're looking at how our data has remained flat over the past 10 years, and so if we know that from the data, what are we going to do about it? Do we just say, "Well, that's the number, and we're not going to do anything about it?

00:07:56.54 We're just ... have conversations about it, or what programming are we going to put together?" So under Erin's direction, we are working on developing inclusion programming, so with our LRE data thinking about, what is going on in the state, and how do we support the SAUs' ... In Maine, they're called SAUs ... districts to develop their LRE practices so that when they are working with individuals, with students and faculty and staff, how do we get them to be thinking about inclusion? So that is one of the big areas that we're working on related to that. It's also thinking about data. Think about data in terms of the data that we get from our process of, what are our indicators? But there's another level of data that we get as well when Erin has weekly meetings with every special-education director in the state, and we hear what they're having to say, that we are having conversations with our partners out in higher education and in other organizations working with our Maine Parent Federation to find out what's happening with families. How are they feeling about what's going on in the state? So I think for me ... I know Shawn has really fancy words for it, but I kind of call it hard data and soft data, so we have the hard data that we get from Shawn and from the data team, but then there's that soft data. What are we feeling? How are things going in the state?

00:09:22.99 Going back to the idea of inclusion and really working on our LRE data and relating that also to our transition data and thinking about, what does transition need to look like? In Maine, we just in the past year and a half hired a transition specialist, and it has just changed the way we're thinking and having conversations with the field about transition, which ties back again to our inclusion work of, if we're not including kids when they're in preschool, we're not including them in elementary school, middle school or high school, what happens to those individuals, those students when they go into employment? They don't have those opportunities because they've never engaged, or they've had limited engagement with typically developing peers, so Erin will tell you that these are civil-rights issues, and we are passionate about changing our LRE numbers, and again, we have the hard data and that soft data to really have conversations about, how do we have kids included in every single aspect of school? And that's really what our focus is right now and so that they can be included when they transition into adulthood and postsecondary opportunities and employment opportunities and the like.

00:10:32.35 >> Thanks, Tracy. I can't wait to hear ... Are each of you going to have a movie that you're going to use to associate with your work and data? I hope so. I'm excited to hear the rest.

00:10:42.17 >> Well, let's hear from Leigh, who is very excited about dispute resolution. She gets very excited about the data and dispute resolution.

00:10:51.39 >> So hello, everybody. I am Leigh Lardieri. I am the Dispute Resolution Coordinator on the team, and much like what Erin said, the question that intrigued me the most was the one that was asked about, what are you getting excited about? And it's everything. And when I work with the team of people that I'm with, I think of "Rudy," the movie with the college reference to Notre Dame and football and the fact that the character was so passionate, and he had a goal in mind, and he met his goal, and it's just a wonderful, positive story. And so what Erin asked us to do within our individual teams was to talk to our colleagues, my two colleagues on my team, and talk about what data priorities we had within the team, so I'm going to briefly share the three we have for dispute resolution, and then I'll break each one down briefly knowing that we have to stay within a time frame. So the first of our data priorities is to use the dispute resolution and technical assistance data that we collect to help inform the technical assistance including ... That would include day-to-day and protracted technical assistance and professional development offerings by our special projects team members and our federal monitoring team members in connection with dispute resolution. We're really reaching across to Tracy's team and to Colette's team and sharing this information.

00:12:27.96 The next one would be to further explore the relationship between our facilitated IEP program and dispute-resolution filings at the LEA level, so this facilitated IEP program in Maine is still in its infancy. It's a little bit over a year old, and so we're really still looking at whether or not it might be too early to tell, but we definitely can extract some things from it that I'll describe in a few minutes. And so then our third data priority for the future is to use dispute-resolution data related to filed requests to inform regulatory policy changes, so that's a really ... a bigger issue. And without ... I would ... Again, I'll say, without Erin's support, without the support of the team, I don't think we could've gotten to this place as quickly as we have. So I'll talk a little bit about the dispute resolution, the TA data we're collecting, so not only do we utilize what is typical of what due process has to provide to OSEP in terms of the data that we collect every year, but on top of that, we have developed a system where when every single one of our colleagues on our team is on phone duty and collecting information from the field, we are putting that into a database, and it updates in real time, and as we're talking today, 512 communications, either phone calls, emails, have been documented in that database.

00:14:07.28 >> Hmm.

00:14:07.47 >> And the trends that we're getting from callers and stakeholders in the field, emails we're getting from them report concerns about their children with autism getting services or ADHD, their children who have behavioral issues and parent-school communication and staffing shortages. Now these folks are just calling for technical assistance. They don't necessarily turn into requests for filings for due process. Some of them do, but the way that I look at it as a big picture is, when folks make requests to our office and they file requests in Maine, it's roughly about 100 requests a year, and that's combined, and then our number of FIEP requests added to that. So right now, we're almost ... When you combine all of that, CIs, mediations, hearing requests and then your FIEPs, we're about at close to 140 cases right now, but when I look at the cases, those individual cases kind of tell you the weather in those communities or those districts, but if we want to look at the climate around the state, then we need to really branch out and look at those TA calls, and that's giving us kind of a pulse on, what are people thinking? Why are they picking up the phone? Why are they sending us these emails? And so now we're really gathering that information, and we're able to combine that with what we already have, and it's just creating added value to the data we already have and informing what our next practices are going to be.

00:15:56.53 So when we move on to the facilitated IEP program specifically, questions are ... that come up for me are, which LEAs are using facilitators? Are the results favorable as reported by the participants? Because we do ask participants to fill out evaluation forms. We never ask them for any specific information about what's discussed at those meetings, but just in general, how did this process work for you? And then really to look at, is the use of the FIEP program in specific LEAs correlated to a reduction of requests for complaint investigations, mediations or due-process hearings? And so we're going to be looking at connecting those dots to see if it's having that impact. And as I mentioned before, it might just be too early to tell, but over time, we can certainly start to look for those trends, and so what we're essentially doing with the phone calls and those emails is we're really taking that qualitative information that is coming through having a phone call with a parent, giving them space and time to talk because, as you only imagine, as you can only imagine and you already know, they're calling because things aren't going well for their child and their family, and so you're taking that qualitative data, and you're quantifying it in a usable form, which is updating in real time in that everybody on this screen has total access to that because we keep all of this data in one place in terms of access for all of us as team members, so we can pull it up quickly and talk about it.

00:17:46.53 And then for the future, just looking at and monitoring bills, people on my team are much better at doing that stuff in the legislative stuff than I am, and so I look to their expertise, but that's just another point, an important point for us to be able to use the dispute-resolution data to inform regulatory and policy changes.

00:18:10.75 >> Wow, you seem to be doing a whole lot with that data and collecting a lot of it, so I'm excited to hear what you learn from some of those analyses that you have coming up.

00:18:22.46 >> To access podcast resources, submit questions related to today's episode or if you have ideas for future topics, we'd love to hear from you. The links are in the episode content, or connect with us via the podcast page on the IDC website at ideadata.org.