MAYRA DIAZ: Thank you, Holly. And good afternoon, everyone. Thank you for joining us today for the DataVista 3.0 webinar focused on the California Adult Education Program dashboard. Next slide, please. So before we get started, I'd like to briefly introduce today's presenters. First off, my name is Mayra Diaz and I serve as the program lead for the California Adult Education Program within the workforce and economic development division at the California Community College Chancellor's Office. 

And we are joined by our partners from WestEd, Debi Pezzuto, Senior Program associate. And Adriel Garcia, program associate with WestEd. Who have been deeply involved in supporting CAEP implementation, data analysis, technical assistance, and DataVista development. Next slide, please. This work truly reflects a collaborative statewide effort, and we're excited to share today's information with you all. 

Today's session is really about helping all of us better understand the story our data tells, not just for reporting purposes, but for improving outcomes for adult learners across California. We will be walking through how CAEP data is collected, integrated and displayed within DataVista, and will also demonstrate how local programs and consortia can use these tools to support planning, accountability, and continuous improvement. So we appreciate your time and partnership in this work. 

There is a quick overview of today's agenda, in which we will be providing some background and context around CAEP and the importance of statewide adult education data. And we'll conclude with live demonstrations, and leave time at the end for questions and discussion. Next slide, please. All right. So the work we are discussing today is grounded in legislation and statewide collaboration. 

Following AB 104, the Chancellor's Office and the California Department of Education were tasked with establishing common accountability measures across adult education systems. That included developing shared core metrics, common assessment practices, measures of effectiveness, to be used in reports to the legislature, and data sharing agreements that allow us to better understand student outcomes across systems. This collaboration laid the foundation for the integrated data environment we now see within DataVista. 

It has also created a more unified and transparent approach to measuring adult learner success statewide. Next slide, please. So why is this data important under the California Adult Education Program? At its core, data helps us establish a common language around student success. It helps us answer important questions such as, who are we serving? What outcomes are learners achieving? Where are there gaps or opportunities for improvement? 

And data also supports accountability and transparency across our consortia. Most importantly, it allows us to make more informed decisions that strengthen services for adult learners within our regions. Ultimately, the goal is not simply collecting data, it's using data to improve learner outcomes and strengthen pathway to education and employment. Next slide, please. All right. Going to hand it over to Debi. 

ADRIEL GARCIA: I'll go ahead and actually take this one. Mayra Hi, everyone, I am off screen right now. I am feeling a little under the weather, so I just wanted to mention that I'm not going to be on screen, so you won't see my face. But I am here, promise. Thank you, Mayra, for setting up the background as to why we're paying attention to the California Adult Education Program Data. And really, some of the legislation that was pulled from earlier years to set the precedent for having this data available and how we utilize it within DataVista. 

I'm going to cover various aspects on this CAEP data that's really going to have the framing of what it's utilized and how it's utilized, or how it's flowing throughout DataVista itself, the platform that we utilize. So you'll see me go across various aspects within DataVista. I'm actually going to toggle between our PowerPoint and the website itself. 

And then a little bit later, as you might have seen in the agenda, we do have Debi who's a partner here at WestEd. We'll go through some use cases specifically, but I'm going to go directly into certain spots as to where to highlight some of this CAEP data and go over some of the more recent updates. I'm going to continue into some information that you all might be familiar with. 

For those of you that might have utilized DataVista, or for those of you that might be in the field that have had some time here, these are really the data sources that we're utilizing for our California Adult Education Program scorecard. There is a couple of other information such as, National Student Clearinghouse at UC CSU transfer information that gets some information for our post-secondary outcomes, such as transfer matriculation. But these are the core ones. And maybe these are a lot of the aspects that you all might be familiar with. 

For a lot of the metric makeup that we have within DataVista, we're utilizing-- again, I mentioned some other aspects when we're thinking about transfer, such as National Student Clearinghouse. There's some UI wage data that's utilized for employment outcomes. But when we're thinking about the realm of metrics, such as, participants, such as reportable individuals, we're taking this information from CASAS and Chancellor's Office Management Information System. 

So a lot of this information is being melded together to represent both of these sources and how you're seeing the data represented within DataVista. As far as a flow standpoint, this is really how it's being produced into this product that all of you might utilize that's publicly available. So we're getting information from K-12 adult schools, from CCs, it's being integrated into the sources such as CASAS TOPSpro, Enterprise, Chancellor's Office Management Information System. 

And our metric development team churns, and creates this information, and produces the metrics that you all see utilizing these two sources. So while some other sources, but when we're thinking about the data and how it's represented, this is really how we're seeing these outcomes being part of what is represented on the dashboard. So this information is joined together, coded together to have a representative of students across both of these systems. And then we're seeing these aggregated counts and records being produced in DataVista. 

So everything-- for those of you that are familiar, you've heard this many times before. But for those that aren't familiar, this is all publicly available for suppressed data. We're never going to get into the specific student identifiers that you'd see on this dashboard. But a lot of this is aggregated so that if there's any point in which we're having low counts of students, we're going to suppress that, so you won't see some data points. 

But we're matching our records across these two sources, utilizing a method that our metric development team has-- name, first name, last name, gender and date of birth-- to reduce the deduplication and capture outcomes, such as post-secondary transitions, or affordable individuals, or cases like that. And then, as I mentioned earlier, there's a match that's occurring with this UI wage data. And I'll point out in a couple of slides, some of the outcome metrics that you'll be able to see to be able to have this understanding of what your students and how their journeys are going on. 

But that UI wage data is being supplemented into this matching process, into this data metric curation process to be able to see all these outcomes, some get pushed to the CAEP Leg report. And a good majority of this is, again, how we mentioned and see it publicly available on DataVista. I do want to-- i've heard this question, and actually, Mayra has brought this to our team every now and then. So I thank her for plugging this in. And I want to show you all a little bit of the technicality. 

And I'm not going to go super deep onto it, but I'm going to give you all, one of the tools that we utilize within DataVista to be able to understand what are these data sources coming from, and how are they melding, and what is the curation in terms of MIS elements or maybe CASAS TOPSpro elements? So currently, where I'm at within our website-- and I'll go back one, but for a lot of my demonstrations that I'm going to put, I'm going to jump directly to the pages just because we have, again, a publicly available dashboard that has billions and billions of records displaying metrics across various Chancellor's Office in California Community College system outcomes. 

So we're today focused on CAEP. There's other information focused on SWP, SEP. We have information focused on K-12 SWP, student athletics. A multitude of information. So when you see and when you experience DataVista, there's a lot of churning of data that's occurring. So just giving you all that context as to why I'm jumping directly. Debi, a little bit later, will demo some of the exact navigation, starting from landing on the page, to getting to the views. 

I'm going to skip a little bit of that right now, and I'm going to focus on our metric definition dictionary, which is located at the top. And for those that might be familiar with launch board in the past, we had metric definition dictionaries in the form of Word documents. And they give all the background information, all the notes, source element information, construction of how a metric is created and calculated, all within a long document. And we've made it a web page. 

So again, I might be saying seeing information that's familiar to a lot of people, but what I'm going to do is, when you're looking at CAEP adult education learners, we utilize a lot of codes to identify our student groups. For all of you here, you want to know that anytime there is a metric that ends in A, that is for all of you, for adult learners. So I want to give you all a little bit of the background, and maybe you can find some usefulness in doing your own exploration. 

But I'm going to give a quick and dirty right here on what I mean by having this CASAS TOPSpro information and data source melded with this COMIS information here. And what I'm going to focus specifically on-- i should have just typed it in, but I'm scrolling right now. I'm going to our reportable individuals. So our reportable individuals-- as you can see, I'm not going to read the whole note here. 

But for those of you that are familiar with this metric, the way that it's being visualized on DataVista is being calculated in two ways. So we have these various TOPSpro Enterprise data elements. And then we have these COMIS data elements. And there's a specific calculation that is going on. So we have our students, 16 plus, with one or more hours, that's one of the criterias. And then enrolled in either of these. So you're going to see this and then all these ors. So if you're not in ESL, you're maybe an ABE, or an ASE, or CTE, et cetera. 

But this is one of-- these are the main criterias and then this is the varying other criterias that are allowing you to be counted from the TOPSpro Enterprise viewpoint. So that's one half of this. And then there's the COMIS calculation part of it, which actually has very similar starting criterias. We're seeing 16 plus. We're actually seeing a student that has a non credit enrollment not in supervised tutoring or study skills. 

And again, COMIS, we're coming from the Community College Chancellor Office standpoint. So you're thinking of the CC system. TOPSpro Enterprise, you might be thinking of adult school system. Various other ways. I'm sure you all are maybe a little bit more attuned to some of the details in those differences. But pointing out the CC side of this, having all of those similar criterias, it's either one of these or ABE, or CTE, or workforce prep. 

There's a couple of other different criterias for COMIS. We have a couple of top codes that are flagged as vocational or occupational Sam codes. We count those students too. So I'm utilizing this quick and dirty to give you this framing of, this is a large universe of students with varying criterias that create our reportable individual. So if you're just looking from one of these data source standpoints, either TOPSpro Enterprise or COMIS, you might see a little bit of misalignment, because we're melding these two together. 

I do want to say, I am joined by a couple of other individuals on our team. I do want to point out one of them who works very closely alongside us in our metric development team. His name is Eric Cooper. We are going to get into some of the data questions, and I do see a couple questions in the Q&A, which I haven't looked at just yet, because I am sort of presenting and navigating this right now. So I'll get to them in just a bit. But I wanted to give you all some of that clarity or at least attempt to give you all some of that clarity so you can do your own digging and understanding. 

How are my TOPSpro Enterprise students then being melded with some of these COMIS students? So I'm going to return back to our slide deck, and I'll get to some of the questions in a bit. And I believe I might have some support from others on our team as I mentioned answering some of these questions in the chat. But that is the start of this data flow and integration for our capable students. Now on the next slide, the data is the matrix. The CAEP information is going to hide this alignment with WIOA. And I'm going to again, jump to DataVista in just a bit. 

But we have all this information available to all of you. It's found in very particular ways, but definitions of reportable individuals and participants. I just gave you one of the definitions for reportable individuals and how that's constructed with that CASAS and COMIS melding. They're very similar method going on with those participants. There's barriers to employment for reportable portable individuals. 

And I want to mention, there are a variety of barriers of employment. I'll showcase them in just a bit in this next slide, and I'll show you where to locate those. But those are only going to be represented counts of students that are experiencing those barriers of employment. So if you're trying to get an overview of, OK, I have a student, that might be flagged as foster youth and I want to know some other outcomes. There is a little bit of limitation that we have. I might be corrected by some of our metric development team individuals. We can go into that. 

But on the dashboard itself, we're going to see represented records of students that are with these flags. When it comes to outcomes, might be a little bit of a deeper dive. But I can at least get you what we have flagged throughout the years at various locales, who has been labeled as foster youth, or who has been labeled as low literacy or low income. We do have that, and I'll showcase that in just a bit. There are outcome metrics. 

So we think of a lot of some of the outcomes. And I have them in just a few slides, such as completed a post-secondary credential, things like received a non-credit CTE certificate. But because we are doing some of this melding with the COMIS. If you're thinking from a TOPSpro Enterprise standpoint, and we're doing this melding with the COMIS data source, we also are able to look into for some of these students' outcomes, such as earning an associate degree, or students that attain the chancellor's office vision for success. Those are outcomes that are available. 

Now, we have alignment with our six AE programs. I will go into-- so it's technically, seven AE programs, but on DataVista, the way we have-- the construction, it's going to show six AE programs, and then there's like a caveat where you actually have to search for a metric that's going to have workforce, apprenticeship. I'll get that specific metric in just a bit, it's in a few slides. But that is available. I am saying six here. All of you might be like, oh, there are seven. That seven is available. It's just constructed in a little bit of a different way on the platform. 

And then just alignment with other key success metrics. I know we don't-- it's separated. It's been past for quite some time now, this move over from launch board. But back on launch board, there was student success metrics. And it showed all those students in terms of various outcomes. So we did maintain some of that alignment for these CAEP adult learners. And that's why you see some of these metrics, such as non-credit workforce milestone, that's available within this student group specifically. Remember, I'm saying those A students that's available within all this. 

So you can search for a lot of this information that I'm displaying right here on this screen. It's really accessible in that metric definition dictionary, which is why I was starting off with that to set the surface-- set the table, I should say, and you can all see and do your own exploration. But this is where the alignment with WIOA and CAEP exist, and how DataVista is creating that. So I'm going to step into these in just a bit. 

And I'm going to start off with our barriers to employment. Again, this is going to be specifically for our reportable individuals. I know you know, sometimes we're thinking about reportable individuals or participants. I'm specifically focusing. And the way these flags are available on the platform are specifically going to be available for our reportable individuals. We're going to have two of them. So it's flagged in the selected year or if ever flagged. So I'm going to jump again. I'm going to go back to our platform. 

Debi's going to show, like I said, in a little bit how I got here, but I'm on single metric view for those of you that might be familiar with this. And by default, if you have no selections, you don't switch with any of the locales or AE programs. You just click on the tile and you access here, you're going to hit reportable individuals. Now for all these barriers to employment information, you can see the trends. If I go into the drill down-- and give me one second, I think this has to reload. I was on this for quite some time. Again, billions and billions of rows and records. 

So I'm going to keep saying that every time something goes slow. Billions and billions. We're going to go to the drill down. And only for this metric specifically, we're going to have these barriers to employment. So if I am interested, and let's just say flagged in the selected year, I'm looking for some of our migrant farm worker students. And this is going to be statewide right now. So I'm just going to look and display this. And we're seeing a little bit over the various years because we just got 24-25 data few weeks ago. We have these outcomes. 

So that's one thing I just wanted to mention where you can access some of these barriers to employment. It looks like we're taking a little bit of a dip on 24-25 after hitting somewhat of a peak on 22-23, 23-24. Obviously, there seems to be a rebound for reportable individuals as our migrant farm workers in our system. Again, this is being taken from both of those data sources. And we can go into-- that was displayed within that MDD breakdown. But that is available if I wanted to look at everything for barriers to employment flagged in the selected year. 

I could select on this blue button. And I know it gets a little bit crowded, but I'm just displaying some of the information here so that you all can see. It seems like our ELL learners were having a little bit of a plateau from last year to this previous year, maybe a little bit of a dip. Very close, but we have increased post COVID steadily, and now it seems like there's a little bit of a dip for those-- or I should say a little bit of a plateau for those ELL learners. So that is available there. That's flagged in the selected year. 

Then I can just put, if ever flagged-- and I was talking about foster youth earlier. For those individuals working at various institutions, curious about some of these specific barriers, this information is available here. So again, I'm just looking at the counts of students. I'm not looking at students that we have different metrics, such as, like we said, outcomes, aspects in terms of persistence. This is just going to be a little bit limited to the count. So at least you'll get an overview understanding of, OK, who are my institutions serving? 

So giving you all that primer so that you can do this exploration. I'm going to try to be broad and then very narrow in some of these demonstrations. So I'm going to-- this is a broader, although we consider single metric to be one of the more technical ways to dive into the data. We do this exploration and demo fairly frequently, but I'm going to hit on some other tools that you can see that can maybe make some of your analysis somewhat beneficial. 

I want to say that in some of these features that I'm going to display in just a bit. We are also looking to continuously improve. So one of the things I really like doing is comparisons. And actually, I probably want to showcase this really quick, since I'm already on here and I have it loaded. But let's just say, I'm going to stick with statewide. So I'm not picking on a specific institution right now. Maybe in the future, if any of you are willing to look at your data live, please let us know so I can do that. 

But I'm going to stick statewide, and it's going to have a lot of the outcomes right now. But I'm going to look and compare. And let's just say, you're at one of your institutions and you want to look across reportable individuals, or maybe you want to look at multiple locales across these reportable individuals. If you're in the context of-- let's not say you're an institution leader, but let's say, for example, you're working for a regional consortium. And maybe, for the most part, a lot of you all know who works where, in terms of, oh, I know my colleges that I serve. 

But let's just say you want to, for example, hypothetically, take the position of somebody at a consortium, and you want to do some local analysis to look at barriers to employment across different institutions. So for one, I actually put myself in a situation every now and then because I don't know all of the geographic locations of everyone that you all serve. But we do have resources to support. So I'm actually going to duplicate this really quickly. I don't know if I need to do that, but-- yeah, I'm going to do that, because I want to pull up this CAEP Learner Agency Crosswalk. 

As Learner Agency Crosswalk-- which I'm going to-- i thought I had it downloaded, I apologize. I'm going to download it and I'm going to bring it over. Give me one second. It's going to give me all the information about our consortiums and their institutions that they serve. OK. So I'm going to do this. And I'm sorry if I'm throwing everyone off a little bit, but I wanted to just show this activity as we're going through this right now. I'm going to display my resource on my right hand side of the screen so that I know. And I'm just going to start with at the top. 

I'm going to look at two of our institutions right here, Lompoc Unified Adult Education and Alan Hancock college, both in the Allen Hancock Community College Consortium. And I'm going to go back to our comparison view. I'm sorry if this looks a little squished, but please just sit tight while I do this little demonstration. So I'm going to click on those reportable individuals because I'm curious for our barriers to employment. 

Let's say I'm just curious about our foster youth. And our foster youth are if ever flagged. So it's not even about a particular year that I'm looking at, it's just, if they were ever flagged as foster youth. So I'm going to select this. I'm going to stick on all. And I'm going to give you all this caveat. And I don't want to go too deep into it. But I would recommend. And it's going to be a little tedious. We do have another functionality that this might be easier, but it's going to require you to join tables. But that's something we can also explore in the future. 

But I'm going to stick with all, because it's going to give me all my selections. And if you're on a PC or if you're on a Mac, you're going to want to be able to locate your command or your control button, because you're going to do multiple clicks and multiple selections, because I'm looking at two institutions. I'm going to look at first, Allen Hancock College. So I'm going to scroll down. And I know it's very small, I apologize. Let me see if I can maybe zoom this in a little bit. I think I can zoom in, but it's going to go. Yeah. zoom in. I'm sorry. Let's zoom in. 

OK. I'm going to stick right there. Lompoc Unified is going to be an adult agency type, whereas our Allen Hancock College is going to be a community college. So I'm going to scroll down. And I know this because I know the makeup of this, but I'm going to give you all some of the details. Our college is going to be the CC district. So Allen Hancock College, whenever you see college, it's going to be displayed there. Then our institutions are actually going to be our adult agencies. 

So we say institution-- and I know you all might use adult agency a little bit more frequently-- but we say institution because in this selection-- as you can see, I'm hovering and it's showing an institution-- we actually have K-12 schools also identified here. Again, we're going to continuously improve on this. So we'll create some better indicators of institutions/K-12 school-- just so you all know-- or maybe/adult, so that way you all know. But I'm going to pick on Lompoc Unified, right here. I'm going to command, select it. So I'm holding command and I'm selecting it. 

And then I'm going to go up. I'm going to go up to the college. So once you hover, you should see in just a bit, it's going to start saying college. Scroll up. So college, and then I'm going to select Alan Hancock, which will be all the way at the top. Bear with me for just a little bit. Allen Hancock College, I've selected both of those. I'll select all programs. 

And then this is where I'm going to get into those drill downs. So flag-- they're only going to be available for 200. But I'm going to select-- i wanted to look at foster youth, so I'm going to say flagged, if ever flagged foster youth. And I think this is beneficial again, if you're taking that role as a regional consortium lead, or you're just wanting to get a regional overview, you don't have to look at consortiums, you can look at by macro regions if you wanted. This is what's being represented. 

I know you all are seeing like, oh, there's inconsistent lines. And that's because our data is being suppressed. So we're having less than 10 students in these certain cases. So 13 is above our 10 threshold. So it seems like in the prior years 16 to 17, 17 to 18, 20, 21, and so forth. You all can read that from here. This would be Lompoc Unified is dropping under 10 participants in terms of foster youth reportable individuals. Again, this is meeting that if ever flagged as foster youth criteria, and then that criteria reportable individuals. 

But I just wanted to showcase that really quickly, just so you all see the functionality. It is at times-- it could be a little wonky, but I'm trying to give you all some of the caveats that you all can be aware of as you're doing some of this across region analysis and aspects like that. I'm not going to take up too much time. I'm going to go through some of the rest of these. I want to show some of the 24-25 data like we had mentioned at the start, but giving you all this 101 background of the data that we have available. 

I'm going to continue. These outcome metrics. Again, I mentioned this a little bit earlier. So we had a lot of alignment with WIOA and CAEP. And the uniqueness of being able to meld two data sources, such as CASAS and COMIS gives us the ability to look at outcome metrics that actually sometimes occur, whether it's at the institution level or at the CC level. So again, aspects like meeting that chancellor's office vision for success is available for these students. 

And again, just getting you all familiarized, we, as a DataVista support and technical assistance team, speaking like number-letter association. So I would always say, 619A is our attain chancellor's vision for success. So just getting a little bit of familiar with that. And you can find what number/character combination is attributed to what outcome in the MDT. But these are some of the outcome metrics that are associated. 

For our participants, I was talking about reportable individuals earlier, we're now talking about participants, creating that nuance. We have information available across all six programs. So ABE, ASC, CTE, ESL, CSS, and AWD. Pre-apprenticeship, which we were just talking about, is actually a subset of CTE program. And I'll show you where to find that right now. But for these six programs-- and again, I'm going to jump back to DataVista in just a bit-- but for these six programs, all of these metrics are available across all six programs. 

So participants who took courses in more than one program area, or students with one to a level instructional contact hours. That's going to be available for all of these six programs. Now, there's one caveat. This will be fixed very soon. But there is some limitations. This is actually a bug on the database at the end. 

So nothing wrong with the data, just more so like the creation of how some of these metrics are displaying some of these subgroups, such as career technical education, programs for adults with disabilities, and our child school success break. I should say, those programs currently are having this bug where they're not displaying metric information. So all these metrics that I'm listing here, if you were to select one of those and select one of those programs, you're going to have some limitations in seeing actual data for that. 

There is data there though. There is-- and there's 24-25 data there. There's 23-24, so forth, and so forth, if you go back. But I'm just giving you all, a take behind slide if you wanted to look into CTE, ABE, ASE, any of those, that is located right into-- i think I lost my Chrome-- that is located-- let me go back, actually. Actually, I have this loaded already. Let's see. I'll go back one more. It's going to be located in the program, E program area right here. 

So this is-- i have obviously selections right now, so I need to go back to overall so that we can see all the programs repopulate. And I think I'm looking at reportable individuals. So there is some limitations on that. So information is going to be-- let's just select CTE. This is one of the CTE subprogram pre-apprenticeship information. 

So we have the AE programs. Let me display them, sorry. Click on participants. Should populate right here. I think I'm having some load issues. OK, let me see. If I reload this. Reload it here. Give me one second. And then I'll note the exact metrics for that seventh pre-apprenticeship program. 

DEBI PEZZUTO: Could you zoom in a little bit too for us, if you will. I think it was zoomed out when you were looking at the comparison view, but we-- maybe even just a little bit more. Thank you so much. 

ADRIEL GARCIA: So this is where the six programs are. If you wanted to go into this Information on reportable individuals, which is our default. So 200, what I was just displaying with those barriers to employment. Information on these AE programs isn't available. But everything else besides 200A-- well, the metrics that I displayed earlier in that slide deck are going to have. So if I looked at information, let's just say, for ABE students, let's look at students with an enrollment in an adult education program who received services. And I'm going to speak in number letter combo right now. 

So that's 201A. Display that for these students. And again, I'm looking at ABE individuals. We'll have that information. Now that pre-apprenticeship, if you wanted to locate what some of that information was, I'm actually going to go back to the dictionary. I'm going to filter by our adult learners. We'll look at-- they are a subset of this 123A which is our career technical. So the pre-apprenticeship is going to be a subgroup of this CTE program disaggregation drill down. And that's going to be 124A. 

So we're going to have the ability to look at participants who were in workforce prep, participants who were in pre-apprenticeship training programs. If you want to search for 125A and 126A. Now I hesitate to show that right now because we are having issues with the CTE drill down, viewing some of that data. It will get fixed and our metric development team has worked on it, but currently, right now, there's a little bit of limitation at looking at that. 

So we're not going to display it for those cases. So you all know whenever we release, I think we should be releasing that update in terms of that fix, either very soon or we're going to have another release for database, the 3, 1 that's going to bring a new metrics. And at that time we'll have that as well. So I'm going to go a little bit quicker. I know we spent some time going around DataVista to showing some functionality. 

We got new data. We got 24-25 data. But that doesn't mean that all of our metrics got 24-25 data. Aspects like if I go really quickly, which you'll see-- actually, I'll stay on this slide, I'll stay on this slide. So we have information that's on our keep scorecard, because I've been showing you all a lot of the single metric, showing you some of that information. We do have some information that does lag a little bit. 

There's some information that's provided for awards and employment for 24-25 data. And that's employment two quarters after is available. I think we have our information on students that obtain the GED is available for 24-25 data. But then some information such as, employment four quarters after, or transfer is not really going to be available for 24-25. So you're going to have go back a year. And then, additionally, there's some information that actually isn't going to be able to populate until 22-23. 

So in general, this information is actually across DataVista is like the year. But in some cases, because we need either time for participants to matriculate, time to obtain employment outcome data, there's going to be some information that's a little bit lagged. So this is another take behind slide, so that all of you can see this. And I'm going to get into at least what is available right now for 24-25. 

I'm not going to read through everything. I'm actually going to be quiet just for a little bit, because I've been talking a bunch, and that way you can see. So we have everything in circle is stayed within five years. Everything that's in arrow up is increased within 5%. Everything it narrowed down is decreased by 5%. So giving you all some time to read through some of this. 

So for 24-25, it seems like a good majority of the progress from and this is a statewide view, so statewide. You can look at your own locale, and maybe Debi will possibly demonstrate single or CAEP scorecard in just a bit. But you can get an overview from a general standpoint of, OK, what's stayed within 5% from the previous year? From a statewide perspective, it seems like our students, just in terms of reportable individuals, participants, immigration, integration milestone, that's all staying within the same realm. 

There's a 2% year over year difference, 3% of four, but nothing meeting that past five threshold. We're seeing some increases. Those that completed an educational functioning level gain. Those that completed a non workforce preparation-- non-credit workforce preparation milestone. Those are increasing. It looks like the educational functioning level gain is actually increasing by 10% over year. So that's actually very exciting. 

And then we are seeing a decrease. And maybe this is where I tell all of you to go back to your institutions and just look at your local data. What did your outcome look like for individuals that earned an award? Diploma, GED, or high school equivalency. What is going on with those students? What are some of the barriers? This could be potential signage for you to take back to your institutions, work with your teams. And from a statewide perspective, are we with the trend of dropping and earned an award, or are we above the trend, or are we remaining within 5%? 

That's the usefulness of the CAEP scorecard. There is that new 23-24 data which I was just showcasing. So on your left hand side right here, this is the same scorecard I was just showing. If you go back a year, you're going to see some new populated matrix. So we're going to see those transitions to post-secondary coursework and some of that employment data. So annual earnings, median, median change in earnings. 

Looks like the only one that decreased this past year, was median change in earnings actually by 13% year over year, which is very interesting. And median annual earnings are staying within that same 1% increase, so within that 5% threshold. But employment is increasing. Transition is increasing. Those are positives to at least think about. And then one more year back. One more, one more. 

We're going to have our 24-25 data again on the left hand side. And now everything's going to populate. And we're looking at those that earn a post-secondary credential. So we're actually lagged because we're giving people-- students I should say-- time to complete that information, hence the time lag. So there is an increase in our adult learners that are earning a post-secondary credential statewide. And then employment four quarters after exit. That's actually an increase of 9%, same with two quarters after exit. 

So seems like there is some traction going on there. I'm not going to paint the story that this is the case across all regions within California, or even all institutions at all. But from a high level, statewide view, this is going on with some of our students. And I think it's then-- which Debi will showcase in just a little bit-- up to you to utilize your data. Utilize DataVista to then look at my analysis. Is my institution on par with this trends in the analysis of what's going on at the statewide level? 

And maybe you don't even want to look at the statewide level. Maybe you want to look at the macro region level. I think that's another smart thing to do. It's going to have the context of your region. So giving you all of this information, and I'm essentially teeing it up a bit for our last portion to go into some demo cases. So thank you everyone. I'm going to pass this over now to Debi. 

DEBI PEZZUTO: Thank you, Adrian. And I'm going to have you stop sharing so I can share my screen. Nothing over here. So as Mayra said earlier, my name is Debi Pezzuto. I'm the senior program associate for adult education, post-secondary education, and workforce development at WestEd. Sorry. Clearly, I can't talk and do things at the same time. Anywho, so I, along with Megan McBride, are part of your CAEP professional development team and we work alongside the DataVista team. 

And one of the things that we do is we provide regional trainings, and walk you through DataVista. Anytime you need it, we provide one on one support. So for some of the questions in the Q&A, I actually put my email address. I think it's on the last slide. But you can reach out anytime that you need help. We can set up a one on one for you or a one on one for your team. Walk through everything that I'm about to do, or anything that Adriel did. We can drag Adriel along with us to show you what he was talking about with the comparison view. 

And we can just expand on what you're looking at, what's going on with your agency, your institution or your consortium, and dig into the data bit more with you. [CLEARS THROAT] Excuse me. So first, we are in DataVista, and where we go first, typically to look at the-- well, not typically, every time when we want to look at the CAEP scorecard, we go right to reports and insights. 

Come on down to the CAEP scorecard down here at the bottom. And you'll notice that every page that you're on-- here, we go. I'm going to have to scroll. But I'd rather you guys be able to see the numbers. Are we looking good? OK, no comments are good comments. On the right hand side, you'll see the toolkit that has the metric definitions. So any page that you're on, you can open this up to take a look. 

To increase the page space, I get rid of the toolkit, as does Megan. If you can't see this, maybe Holly shout out or Mayra shout out, let me know. In here on the scorecard, we are going to first look at participants. Anytime that you hover over, you can see the percentage, you can see the raw numbers. And then you can also drill down by the locale. So you can look at region. You can also pull up your individual institution, or community college, or your consortium. Have fun with that. You can look specifically at the AE program that you're focused on. 

but for today's purpose, I'm going to look at statewide and I'm going to look at everything. I want to click on participants, [CLEARS THROAT] because I want to see how we did post COVID. Looks like we are bouncing back. It's been a little bit slow. I know Adriel pointed that out on another metric. We're seeing that slowing down, but still, we've reached and exceeded our pre-COVID days. So I'm happy. I'm sure you're happy. 

Again, we can look at locale. We can drill down by the AE program. We can also look at age, ethnicity. We can look at a few different factors. We can look at all of them together. I'm not going to rehash that. Adriel showed you a minute ago. But I do want to show you, when you look at options, you can look at the table. I like this view personally because even though I can hover over and see the percentage, I like it when I can see this as a table. This is great for a screenshot. 

I know you all are starting to work on your annual plans and we're all looking at our data, so if you're looking for a quick screenshot, it's there. The technical definitions are always on the bottom no matter where you are. And now, I want to go back and look at earned an award. We want to see how we're doing with our GED and high school equivalency. It looks like we're down a bit. Because I didn't put my table away, it stayed up. If I want to remove it, I can just by going here. 

And again, if I want to just look at-- maybe I just want to see what the ASC numbers are. I want to see how many of these ASC students have completed their GED or high school equivalency, or maybe my adult basic education students. Oh, they're up a bit. Interesting if you want to pull this information, and doing a screenshot isn't giving you the quality that you're looking for, you can also extract it as a PDF and print it. This will give you a high quality PDF version. 

Now, let's go back. If I click the back button on my browser, it will take me all the way back to the beginning, which is fine, I can get back. But if I use the back button here, it just takes me one step back, so I don't lose all of the things I've been looking at. I also want to look at transition to post-secondary coursework. But you notice, there's nothing there. And this is where those lagging metrics come in. 

So we need to go back a year to 23-24. I can look at any of these years in here. When I click on transition to post-secondary coursework, I'll be able to see all of the years. But in order for me to click on it, first, I have to go to 23-24. Ta da! There she is. Transition to post-secondary coursework. [CLEARS THROAT] OK. Not bad. We're getting stronger. We have not exceeded our pre-COVID years, but I like that we're seeing a steady increase. 

If I were a consortium director, I'd like to see where my consortium's been going and where we can improve. Again, all the same features for every page that we're on. I apologize, I'm going fast, because we're running out of time. See, I did it. I hit the back button. That's all right. I can always find my way back. I am not smart enough to break the internet guys. 

OK, this last one I want to show you. I went to the scorecard, but actually, I want to go to the single metric view, because I want to look at transition to non-developmental coursework. Because I'm curious, say, I'm a consortium director and I'm curious, I want to see how many of my students are actually transitioning to non-developmental college coursework. You can either go back to the main page on DataVista, or you can come up here to the drop downs and select single metric. We're going to find our CAEP adult learners. 

Close my toolkit, because I have ADHD and that's too much information. And we're going to give it a second to load. [LAUGHS] There we go. Again, we have the same options where we can pull up the table. But if you notice on this, I don't have any of the raw numbers, or any of the data up here, that I can see on this. So when I go to options, I'm actually going to say, show all labels, because I like to see the information right there for visual. And I'm also going to show the table. [CLEARS THROAT] 

Now when we're in single metric, this is where we can search for the exact metric that we're looking for. We come down-- let me close that menu-- when we come down over here to metric, you can type in anything. You can be a scroller or a searcher. Megan is a scroller. I'm a searcher. If you know the number of the metric that you're looking for, great. If you want to see participants, just put in 202 and you can find it. If you're looking for a non-developmental college coursework, you can put in non-development. I put in non dev and it popped right up. 

But for our sake, I know that it's 637. There's a lot of information, so sometimes it takes a minute. Transition to non-developmental credit college course. [CLEARS THROAT] Excuse me. And that has exceeded pre-COVID days. That's fantastic. I want to see what's happening with our denominator too, though. I'd like to see, there may be an increase, but see, it's still at 7%. So technically, it stayed the same, but the number of students has increased, so that's good. 

You can play around with this and search for any of the metrics that you're looking for that are specific to your annual plans or if you're just curious. There's also the compare option. If you need assistance with that, let us know. And for the single metric view, you can actually pull it as a CSV file and save it as an Excel file. So that you can see all of the information, take a screenshot, use it wherever you need it. You can also do a PDF, which is a really nice view. 

Now, we looked at the data. The metric definitions dictionary, right here at quick view. So if I wanted to see what this non-developmental metric was, I could pull it up. Ideally, [LAUGHS] maybe say, I want to do two of two. You can also scroll down and see why there's no data. For some of our smaller consortiums, agencies, institutions, you might not have any data or you may have gaps. And that is because anything under 10 students is going to be suppressed. So if you have really small student population, that's why you may have some information missing. 

Although if you notice something that's odd or out of the ordinary, you can contact the DataVista team. Eric, put in the contact information in the Q&A, but I can also put it in the chat. So you're having issues, here it is. datavista@cccco.edu We've got all of the C's. And if you're looking for some one on one assistance, if you'd like to share this training with your team, and you'd like us to come talk to them via Zoom, you can call us anytime or email us at any time, and our information will be at the end of the slides. So now I'm going to stop sharing and send you back over to the always lovely, Adriel. 

ADRIEL GARCIA: All right. Thank you, Debi. I'm going to close us out. But I did see one question, so I'm just going to address this real quick, because I know we're going to get into the Q&A portion anyway. Multiple selections. And you're saying, multiple criteria. And I believe I didn't create this caveat at the start. But you can select multiple criteria. And by criteria, I mean select multiple drill downs, multiple programs. Right now it's only one program. But you can select multiple programs if there's more programs and multiple locales, as I was displaying. 

You cannot select multiple metrics in the comparison view. So it does have to be one metric at a time, which I know can be tedious and I understand that. However, that is why we actually-- and I didn't get time to demo this. We have five minutes left and I still am trying to find some time to answer some remaining questions. I apologize. But I'm going to point out one more thing. To be able to do a multiple metric analysis and have it visually available to CO, what was 202A? What was 201A? You're actually going to want to utilize our bulk data download. 

Now, the bulk data download can give you every view on DataVista. You're probably all interested in the CAEP scorecard and the CAEP snapshot, which is our CAEP adult learners. Again, I'm trying to give you all the terminology so that you're putting two and two together. CAEP snapshot is going to be that single metric CAEP adult learners. The CAEP scorecard is going to be the scorecard that Debi showed. 

So you you could do that. You could select multiple years if you wanted to. And it's going to give you all the drill downs, all the locale that you select. So you can again, when you're looking, let's say you're at an adult school. You want to do institution because it's not going to say adult school, it's going to say institution. Just get familiar with that terminology. And then you're going to want to get-- so it's going to download. It's going to give you a CSV file. You're going to want to take whichever locale you're looking at. 

If you're just worried about your locale, let's just say you're at Antelope Valley College. I'm sorry if I botched-- messed up the name. I believe its Antelope Valley College. And you just want to look year over year for multiple years, and you want to look at general admission or CAEP adult learners, you can do that here. The usefulness in this is you're actually able to get a CSV of a certain locale, certain year, certain view, and then append it. 

And this isn't going to be the same data. This is K-12 school. So I apologize. I had an example already. I lost it. I don't know where it went. But I do have another example. I'm going to-- and I saw the visibility from terms of accessibility small font. I know, I'm sorry. I don't have-- I usually Zoom out so I can see everything. So I apologize. But you can get your data, get your CSVs, append them. 

You don't have to join them because they're not different files. All the drill downs and the segregation, then columns in this table are going to be the same for the next file. Unless potentially, you download K-12 schools, which might-- or I should say, K-12 SWP, which might have different information, which would be a little bit of a hard comparison, but doable. In that case, you would join, but you would append your data. I'm sorry, I'm getting off topic. You would append your data. 

So in this case, I'm looking at a school. And then at the bottom of the information-- at the top, I have the county. And then you can go ahead and create some pivot tables from this information. So right now, I'm looking at just K-12 schools. And this is another quick and dirty, so I apologize. This isn't the same one that I had up, but you can see in the K-12 SWP report, we have our metrics labeled as titles instead of numbers. So this is showing all the metrics on one graph as opposed to how we've seen it in the scorecard view, with the indicators up and down. 

This actually displays them visually in terms of bar graph. I could do a line graph too if I wanted to, but I wanted to answer that question by saying, you can't select multiple criteria. And I think your meaning criteria by meaning metrics. But the other criteria you can. But in the bulk data download, it takes a little bit more technical support. And we can provide that. You can do that. So long winded answer to say, no but yes. And I think are there any other questions? Team, I'm inviting everyone else and on the team right now to answer any other questions that we might have been waiting. I know we have a minute left. 

MAYRA DIAZ: Thank you, Adriel. It looks like a lot of the questions that came into the Q&A have been answered. Please continue to reach out if there are any additional questions that we can either answer in the next minute, or feel free to email. One item I wanted to bring up was-- especially in this space, we're very well familiar with the CAEP fact sheets. We are working on getting those updated now that the latest data, fiscal year 24-25 refresh is available. 

So we are working with our partners at WestEd to update the fact sheets. Please stay tuned. We will announce once the fact sheets have been updated and released, and there will be an additional webinar to walk you through. We're really excited. There are some really great enhancements that are being incorporated into the fact sheets, so stay tuned for that. Any other questions? 

It looks like it is officially 1:00. So just want to thank you. And as we conclude today's webinar, continue to thank you for the work that you do to support adult learners across California. The work happening within our consortia, adult schools and community colleges is making a meaningful impact in communities throughout the state. We really hope that today's session provided useful information and practical tools that you can take back to your local programs and teams. 

If additional questions come up after today's session, please feel free to email the DataVista contact that we have listed below for additional support. Megan also, or Debi also, mentioned that there are office hours available. Please reach out if you want some one on one assistance and navigating DataVista and trying to access your local data. And lastly, thank you, again, for your continued partnership, collaboration, and commitment to advancing adult education in California. 

HOLLY CLARK: And if you would like to save the chat, you are welcome to click the three dots in the upper right hand corner of the chat box and choose save chat, and that will allow you to save all of the links that were provided. Thank you, Mayra. Thank you, WestEd team. And thank you to the attendees. I hope everyone has a great rest of rest of your day. Bye bye. Oh, it does not work. I will save the chat. Let me do that now. I have saved the chat and I will email it out to everyone who is in attendance. Thank you for letting us know. Bye bye. 

DEBI PEZZUTO: Thank you, Holly 

HOLLY CLARK: Oh. Bye bye.