Lisa Le Fevre: Thank you so much, Mandilee. And welcome, everybody. Welcome to our webinar, a resource refreshed, the updated CAEP fact sheets for three-year planning. This webinar is actually the first of two webinars on the CAEP fact sheets. It serves to update you all on data that has been refreshed within the sheets, and also to provide a reminder on how the fact sheets can be used as a resource to inform three-year planning processes.

And that's going to be coming soon. And guidance has been recently put forward. So again, this is part one. There is a part two on Monday. Today's session is going to focus on not only introducing you to data updates, but we're also going to engage in a whole group walkthrough of data elements found within the sheets.

Of course, like Mandilee said, we welcome questions as we go and we seek to invite deeper inquiry in your experiences as well. So this is an engaged session. I'll quickly go over a few introductions, which is the next slide, please.

So again, I am here from WestEd. I am Lisa Le Fevre. I am a senior program associate. I'm also a research manager. And we're here, along with my colleague Greg, to support the adult education field through our work with CAEP. I'm going to pass it over to Greg just to introduce himself quickly.

Greg Hill Jr: Thanks, Lisa. Hi, all. My name is Greg Hill Jr. As you can see, I'm a senior research associate. I focus predominantly in post-secondary and adult education, and quite often using data to inform program planning and identify and address gaps in equity. And so glad to be here. So glad to see all of you here as well.

Lisa Le Fevre: Great. And as always, I love to and really need to thank and recognize the Chancellor's Office CAEP team, Mayra Diaz, Cora Rainey, and of course, the CDE team, Dr. Carolyn Zachry, Diana Batista, Neil Kelly, everyone who supports this type of work to ensure quality adult education.

Now, I'm not sure if anybody is in attendance today from those teams, but I'll give a quick pause in case. And then obviously, I really extend a lot of my gratitude to both Mandilee and Holly from SCOE TAP. Their team is always organized and provides us with stellar support so that we can hold these sessions with grace and efficiency. So thank you.

Now we're going to move on to the agenda. So today's session, we've done our welcome. We are going to go over soon our goals. And we do have a poll. So that's going to be fun. But then we're going to take a look at what are the CAEP fact sheets, what changed in the fact sheets and what didn't. So again, this is a refresh. They haven't changed significantly, but it's a data refresh.

And then we'll explore how to use the CAEP fact sheets and the tabs and data. Obviously, we'll end with a discussion and closing. But again, we invite questions as we go along.

Our main goals then on the next slide are really to give you an introduction to the updated data in the fact sheets. And this is for data use and to help with your planning that's down the road, also to increase understanding about the elements that comprise the CAEP sheets.

And finally, give us all an opportunity to explore and ask questions about the sheets together in real time. We will have a session too, where we go deeper. And we are available for support so please just text me, email me here and we can set up some sessions. So next slide.

OK. Here we go. We have a quick poll, and Greg is going to help me with this. And the poll has three questions. The first is really asking about how new you are to the planning process, what is your comfort using data to inform adult education programming, and then your experiences with the fact sheets. So, Greg, let's launch this poll.

Greg Hill Jr: All right. So you should have a prompt on screen right now. OK. Got some. There we go. Some answers coming in. We got 25%, 30% responses. Interesting.

I don't know if you can-- can you actually see this happening in real time or are you just sort of--

Lisa Le Fevre: No.

Greg Hill Jr: Bated breath. OK. Yeah. So just a few more folks then. So we're about 60% response. See if we can get that a little bit higher. Some effort. Good. Good. We're at about 70, 75, which is about where we're saying, OK, this could be valid.

But that's just as many as possible. OK. 80%. Can I get 85?

Lisa Le Fevre: Can I hear 90?

Greg Hill Jr: 90. Can I get a 90. Yeah, exactly. Just a couple more trickling in. So I'll give you just a couple more seconds here. And then we'll move. All right. So I'm going to end the pole at 85% response rate. All right.

Now, I will share the results. OK. Can you guys see this? Can you all see it?

Lisa Le Fevre: Very good. So we have a good over half of everybody here. 51% feel somewhat comfortable with pulling data, different types of data. I love seeing that 20% feel very comfortable. You're going to be our helpers today for sure. And then we got a little handful here that are somewhat in uncomfortable.

So we're here today to offer you some of that support. Feel free to reach out and we can always provide extra support as needed. The experience with the-- this is interesting, Greg. Experience with the fact sheets, we've got basically-- it's almost level across the board.

Some people use them regularly, occasionally, aware of them, but haven't used them, and are not familiar. So we are going to be here today to bolster, perhaps, we can help people with using them.

Greg Hill Jr: Yeah. I might also add here what you're mentioning about level of comfort. It's about a third are saying here that they don't feel even somewhat comfortable. And if you add that with the somewhat, that's a lot. And so I really appreciate everyone's candor here.

And think a lot of that probably has to do with that buff. What is it? 42% of you are new to this process, which suggests to me either you just became directors, in which case, welcome. Or you're new to this process because you've moved into a new role or are performing some new function with the consortium that you're working with.

And so I think then yeah, this is perfect. I think this is a nice mix. And hopefully, everyone will get something beneficial from it. And just to echo what Lisa said, all of you who really understand it are really use this fact sheets, and are not new to this process will really want to lean on you to share your experiences and insights.

Lisa Le Fevre: Perfect. Thank you, Greg. And thanks, everybody, for the poll. Now, just when you think we've asked everything about you, we do have one more question, and that's on the next slide. And we're going to do a waterfall for this one.

So I'm just going to read you the question. Take a quick second to think about it. And I'm going to do a count of three to just chat your answer. So for those of you who have used the CAEP fact sheets. How have you incorporated them into your adult education and three-year planning process?

So I'm not the one who wants to lead answers, but some examples are data informed decision making. Have you used them for that? So I'm going to count to three. 1, 2, 2 and 1/2, 3, go for it. Chat your answers and we're going to just shout out.

How have you used them?

Greg Hill Jr: I can only assume. There we go.

Lisa Le Fevre: There we go. To identify regional need. That's what we got. Set and goals. Goal setting. That's a perfect one. Let's get a few more here.

Greg Hill Jr: Good. Understanding adult populations within the region, absolutely. Sort of goes to what we put in there, of course. Yeah, good overview to begin. So setting the stage.

Lisa Le Fevre: Wonderful. All right. Exactly. So these are some-- look at this. One more here.

Greg Hill Jr: I'm waiting for you, Emma. I was waiting.

Lisa Le Fevre: There we go.

Greg Hill Jr: Yeah. Good. Very good. Good. Yeah, absolutely. And it helps really as a direct-- can directly contribute to the plan itself.

Lisa Le Fevre: And so I think these are all valid reasons for using the CAEP fact sheets. It is a resource that's out there. And that's what we want to just put forward. It's not the only thing out there, but it gives you, as many of you have mentioned, a baseline, a process to go back to take a look at, to kind of recontextualize with your local data, to use it to think about what might be needs for demographic populations involved.

And we're going to cover some of these today. And so I'm going to start and tell you a little bit about what are the CAEP fact sheets. It's an overview for some of you. And then Greg will be moving on to more.

So the CAEP fact sheets. There are resources to help a consortium plan and assess community based and local programming and services. Now the key elements covered in the sheets provide readily and easily accessible data on a consortium's demographics and that sort of information, comparisons between demographic data for a consortium, and transitions data and key labor market data.

There are also kind of two student stories for some of you who are familiar with the tabs that are on these sheets. And these stories were developed as an example profiles, if you will, of the adult education learners we encounter and we strive to serve.

Of course, there are many different profiles. And when the sheets were created, these were just two that become conversation pieces to help us keep in mind and be student centered. Now, what else are in the sheets? There are, again, that ability to compare data. You can do a step by step view of transition data. And of course, with the student profiles, that gives you the illustrations.

The sheets were then designed to provide key data to inform CAEP three-year planning and also for multiple purposes and uses. You don't have to just use them for three-year planning. They again are organized by the four tabs. And we will drop a link to them so that you'll be able to see them, which includes that population, demographics, the adult Ed comparisons, the transitions, and labor market information. They pull from different sources, which Greg will cover.

Finally, as a starting point, you can use these for the planning process or come back to them for continuous improvement, so that you can do needs assessments, so that you can do consortium planning conversations.

You might want to go to them to explore data to gather insights and information, and then obviously, so that it can help you with that data informed decision making or planning. So now that this is just a quick overview, I'm going to turn it over to Greg, who's going to dive deeper into the refresh.

Greg Hill Jr: Thank you, Lisa. All right. Actually, it's funny. I was right about to ask you, Mandilee, or somebody, to put in the new path.

Mandilee Gonzales: Yep.

Greg Hill Jr: Both work. I just put it in chat. But to avoid confusion, I think you can use the one that I just put in chat. Because as you could see, the path to it was a little out of date.

So OK. What I'm going to go ahead and do is just jump in and share my screen and walk you through that way a little bit. Let me just first make sure that we've got the-- there it is. I don't think I closed my window, but OK. Let's just hop in. So I'll share. There. So can everybody see this OK?

Lisa Le Fevre: Yes.

Greg Hill Jr: All right. So beautiful. OK. So for all of you who've seen these before, I'm sorry. I'm apologizing. So wanted to sort of walk people through quickly how to navigate the sheets and then how to make meaning out of them.

And so first and foremost, up at the top, we've got six tabs. Four of them contain really actionable information that is current and up to date. The other are student stories. And then of course, what's new in 2024.

And so in terms of what we've updated just really quickly, for those of you who are familiar with this, we've updated the census data with the 2018 to 2022 five-year-- actually it should be 2017, American community service data, which is, for the record, the latest at the time.

Public use microdata samples are record level samples of the US census data that researchers and savvy, people who like to crunch numbers, can utilize to create estimates that are unique and can't be found in the published tables. Neat.

In order to get things to the-- so our estimates were accurate or as accurate as they could be, we used the latest 2020 decennial data to interpolate into your consortium regions. I say this and for those of you have no idea what I'm talking about,, for those of you who work in regions that where the boundaries do not correspond to counties or groups of them, then you'll appreciate these efforts.

So labor market information has also been refreshed to the 2023 data. We pulled this from Lightcast, which is informed by US Bureau of Labor Statistics. And then transitions data, a demographic data and transition data have been updated, although they do feel a little bit out of date still. But they are updated to the latest data that are currently publicly available at the level of detail that we've included here.

The demographic data is '21-'22. Transition data is '20-'21. There is a difference in that time span because transition data always lags behind. Because people have transitioned. But anyway, so jumping back, we'll go ahead and just start with our first sheet here.

I'll just grab my notes. Well, actually, no, before that-- forgive me. OK. So every single one of these tabs has some option to filter for your specific region. In the case of the population demographics tab, you also have the ability to use this at a glance row or whatnot. These icons to filter all of the visualizations down here as well.

I don't know who annotated the screen, and that's totally fine. But just a reminder, that's not actually on the fact sheet. There's a question in here, Jason, and I will actually try to address that briefly. OK.

As you can see, some of your core demographic components are listed here. Some of those, at least the ones that are most important to adult education planning. Yeah. Yeah. Sorry. I'm being distracted there. But OK. As you hover over these visualizations, you get some additional detail, provides the data, the percentages of the population, which is the ACS subgroup, as well as the number.

Yeah. If you filter by any of these, it'll also adjust all of the visualizations here. And so I'm going to go ahead and just show you a little bit what that looks like. And I'm going to draw on LARAEC for a sec. I live in Los Angeles, so I'm grabbing LARAEC.

As you can see, about 4 million are potential students. Adults over the age of 18 live within the LARAEC region. Roughly 42% are Hispanic. About 70% 60%, 69% have less than a bachelor's degree. But 41% have not attended college in any capacity, whatsoever.

So first, is there anything else that jumps out to-- well, no. Pause that. Let me answer the questions in chat. So Jason asks, given that the 2023 ACS release is scheduled for next month, can we expect an update with this data?

So I'm assuming that what you're describing is the published release. Are you talking about public use microdata or is it updates to the published tables? And feel free to just come off mute if that's helpful, Jason.

Audience: No, I was just looking at the release schedule. And like the initial one year estimates are going to be released next month. And then the five-year palms is going to be December 12. So I'm just wondering, are we going to have that in time for when we start our three-year planning so that we could use the most, most, most up to date data that's available for when we look at our regional need.

Greg Hill Jr: Excellent question. So in general, I advise strongly against using the one-year [inaudible] data. I mean, and they do too, frankly, the census does too. It's like you really only want to use that if you really do need the most, most up to date data. But even then, it's not necessarily going to be the most accurate.

Generally, five-year is going to be overall paint a more accurate picture. I don't expect we'd be able to make those updates by-- yeah. I mean, certainly not next month. I would also add that census has been notoriously bad as of late in actually sticking to those release dates.

And so I doubt that there would be an opportunity to really make those updates before-- yeah. I mean, in the next year, exactly. But I suppose you certainy do could reach out and you can see. My experience actually, though, truth be told is that you won't find significant demographic shifts from just one year to the next.

I mean, generally, demographic, regional changes happen in 5 and 10 year cycles. And all of the projections or all these estimates are estimates. So what the US census does for those who aren't necessarily familiar, is there's a 2020 decennial counts. Everybody gets some very specific data points.

And then throughout years that follow, the next 10 years, they send out different surveys to smaller subsets of the population that they then use to create and modify estimates for their published tables and COMIS data.

Anyway, so it's always better to have just the longer view. There's another question, Suzanne asked because the lag is hard to use fact sheets that are [inaudible]. Yeah. I assume some of that is yes. You're talking about the enrollment data, I think is where it's going to be most pronounced. And I fully agree with you there.

And I think one of the things that we like to emphasize, and we'll hear, is that this shouldn't be your only source of truth. And there are some principles here-- Harpreet's asked a question, and it's so smart. I want to address that in a minute.

Great question. Does it make sense to look at previous year's fact sheets to help figure out trends? It can be, yeah The one thing I guess-- I don't think there's a significant risk to that. And I mention it because when using census data, there's always like margins of error.

And oftentimes, you can see what looks like a trend, but isn't actually statistically significant. It's not a real trend. But we're just talking-- if we're talking about high level numbers, I think that's perfectly fine.

But yeah. So I think that's a good idea. And reach out if you want to talk more about that. And Harpreet, I do want to address that, but bear with me first. OK.

So looking at LARAEC here, sort of anything jump out to you? Anything notable? There are researchers asking smart questions.

Halfway, I'm going to ask somebody in a minute, but I'll let you off the hook this time. But then I'm going to apply pressure. So let me ask you a different way. What questions-- I would love to hear some of the questions that you might formulate that this sheet might also help to answer.

So what questions, specifically, as a question-- Rick, yeah, go for it. Go ahead and come off mute.

Audience: I mean, for me, it's the intersectionality of limited English near poverty and no high school diploma. So to what degree-- when we start removing those factors or i.e. Like for my adult schools, we're not concerned necessarily with anybody who's got a bachelor's degree and above, and for some colleges, we are, depending on upskilling and stuff in Silicon Valley region. But that's hard to capture from this. It's mostly just overall population demographic stuff.

So to be able to draw the line between the obvious intersection of barrier to employment, which is the LEP and no high school diploma, that is, in and of itself, going to be highly correlated to the poverty estimate. So that's more of just like it's not even necessarily a additional degree of freedom. It's mostly just helps to tell the story when you compare that to the other extremely useful, which I'm stoked you added the living wage calculator.

Because just like looking at aggregate California and then looking at my region, it's $6 higher in my region it is in-- yeah. So this is always very helpful. But to answer your question, that would be like I would basically immediately start drilling into the intersectionality of LEP and no high school diploma.

Greg Hill Jr: I actually have that down as my example too. So Rick is not a shill, I promise. That is really helpful. Thank you. In fact, if we look at it here, this is particularly valuable. So if we're thinking about,

OK, what is the proportion of folks who have less than a high school diploma or what proportion of those who are in limited English households or rather have limited English skills have less than a high school diploma?

And you can see, not surprisingly, is that there is a strong correlation. If you don't have English language proficiency, it's unlikely that you have particularly high academic achievement, all right, our educational attainment.

Likewise, I like going the other direction, well, of those who don't have high school diplomas. How many speak English less than well? 50% or so. And so what that tells you, like in the LAERIC region, at least, is that if you're designing programs, you want to be designing them with that population in mind.

So roughly half of those, who you might want to bring to your program, may not have the English language skill yet to actually succeed in a high school diploma program without some kind of support or adjustment for those linguistic differences.

And so absolutely, that, to me, is the sort of thing that I find most useful. And frankly, one of the reasons we use data as opposed to just the published tables.

You can, of course, poke around and do even more here, like unemployed. I like to look at unemployed against educational attainment and sort of compare with the overall as well. But oftentimes, you can already see make some inferences there. But what is kind of interesting is you can see some variations in ages.

I haven't spoken extensively about the race, ethnicity, distribution, but this is important for equity. And I think in particular, when using the other tabs, it's really important to have some of these data in mind, specifically for the populations of interest. So what I like to do is just kind of download the overall or whatever I'm looking at so I can have it on hand. And you have it on hand.

Quickly, I did want to add one more thing. You can do that easily just by clicking here and then getting a PDF. If for some reason, you click on a thing and say keep only, and you want to go back, there's a button here that says Reset.

Before moving on to the next tab, there are a couple other good questions here.

Lisa Le Fevre: And Greg, all these questions have that thread of equity you're talking about. So Lucy says here, what correlation is there, if any, between not in labor force and below high school? Janice is looking at have our regional demographics changed? And if so, how can outreach programs shift accordingly?

And Molly-- are there concentrations of no diploma within our consortium where efforts can be concentrated? And then how do the workforce participation data compare to the efforts of our AJCCs? And can we collaborate better?

So it's all these different lines of inquiry that ultimately are speaking to how do we build equity, how do we build success for our learners.

Greg Hill Jr: Absolutely. And I really like-- so a couple other questions here. How have they changed? Absolutely. And echoing that question about correlation, if any, between labor force and less than high school diploma, so yeah, absolutely.

What's kind of curious is it's not as-- their levels of educational attainment are kind of predictable if you look at unemployed. What is really interesting to your point, though, too, is the proportion-- where did that go? Workforce, oh, there it is. Sorry, high school, high school. There we go.

That with less than a high school diploma, actually, that roughly 50% are not in the labor force, which is not the same as unemployed. But that does raise a really interesting question-- why? And if you look here, well, at least a quarter of them or so are over the age of 65.

And so that winnows it down just a bit. The thing that this isn't telling you, is anything about underemployed. And so that is one of those areas you want to really engage with your partners. And that's one of the comments here mentioned. Yeah, Molly mentioned here. Concentration of those where efforts can be concentrated. How does the workforce participation data compare to the efforts of our AJCCs? Absolutely. Use this, bring it with you, print it. Talk with your AJCCs. Absolutely.

Beautiful. Good. Thanks, Rick. [inaudible] employment. I want to say, I don't think it includes exited the workforce. I think it's just-- or as such. I'd have to look at the dictionary but [inaudible] really provides just-- I'll check, but I think it's really just these three. It's employed, unemployed, or not in labor force.

I don't know that it provides additional detail. But yeah, that's a great question. And so I would absolutely-- everything you see approach with some measure of scrutiny. And it's not that it's wrong. It just may not be right for what you're doing.

And so on that, let me go to the next one here. So this tab shows the comparison of our current demographic information in the lounge board against some of the demographic data that we just saw.

Now, you're 100% right. All of you who were like, hey, this data is old. That's true, but it's unlikely, and depending on the size of your consortium, that proportionally the makeup will change.

For all of you you've taken a statistics class, I mean, the way that we think about proportions and representativeness is if you had a big bucket of soup-- a big pot of soup, and then took a cup and just dipped in randomly, as long as it was pretty well mixed up, then you should have roughly the same proportions of like chicken noodle, noodles, carrots, whatever else, presuming that they're not radically different sizes.

But the smaller that pot gets, the less is in it, then the less likely what you pull will actually be representative. And so it is true that if your overall numbers are smaller than what you would anticipate, you might want to begin to-- or if your enrollment overall smaller, you might want to approach this with some measure of caution. Yeah. Thank you, Susan. This is recorded too. So it's bucket of soup.

So approach that with some caution. And so I'm going to-- I really don't want to say pick on whatever. Actually, I have great love for that. And that's why I'm using it. There's some more questions. I want to try to address those.

But really quickly, looking at LARAEC, we see some variation. Some of these variations may not matter, not in a meaningful way. But what we want, however, is to at least ensure that there is equity of access. And so there are different types of equity. There's outcomes and access are different. And so access is who's getting it, who's showing up, who's enrolling.

And as we can see, at a really high level, that there's a really significant enrollment in LARAEC by Hispanic populations, which is vastly, vastly outnumbers the proportion overall in the region.

Is that necessarily a problem? No. I mean, it depends on why they're enrolling or why they're not enrolled. But I'm going to pause because there is one more thing I want to share here. Let's see if there's any other questions. Good, good.

Cindy asks the question. What's the best source for current data by local, county, region by occupation that will help us determine the high impact city areas in need opening sustainable income? OK. That is-- and so great to see you, Cindy. That very much gets to one of the other-- well, that's it.

So yeah. I mean, Lightcast is what to use. And the labor market information here is from Lightcast. There are cautions, and I realize we're running sort of short on time. I have cautions here about using all of these data. And I think labor market data in, particular, gets misapplied by very well-intentioned people who aren't looking granularly enough.

And so the really quick thing I would say is whatever Lightcast says, talk to somebody who's actually in your region doing that work to find out whether they agree and identify what trends they're seeing.

Because it can say that there is a strong need for welders. And so you could run out and start developing a welding program. But if you're welding for-- if you're in a machine shop welding, that is a different set of skills than, say, if you are the welding need has to do with, shipyard, or even the Navy hires welders, and where you're like welding stuff underwater.

And so like there are nuances there that you want to try to separate. And I know, Cindy, you are particularly good at getting a good sense of what is in your area, that sort of asset mapping thing.

And so that's why you want to partner these things. It's what is this data point say? What do these people say? And try to work together to refine what's true, what the needs are for your specific local needs.

Just because data is saying this thing doesn't mean that your experience, what students tell you is any less valid. It's equally valid. It's just it provides a different lens, greater nuance. And you want both.

Lisa Le Fevre: And Greg, like you mentioned, when we get back to the slides closer to the end of the presentation, you have some considerations, limitations that you'll run by.

Greg Hill Jr: That I will absolutely run through at lightning speed because I'm going to try to get through these. So one of the nice things here for this tab, even though, yes, it's a low date, is that you can show some comparisons by the different demographic groups.

And so being able to say, OK, how does my enrollment proportional to the rest of the population in any way? So a lot of Hispanic here, pretty low Asian population in my CTE programs. Again, is that a problem?

Well, I mean, it depends. And I think this is-- and this is one of the cautions that I have later. So if you're thinking about-- this is where the dangers are. So if you're looking at something like, and I'm just going to use Asian population here, they're not representative here, we need to really start doing some outreach with Asian communities. That's great, do that.

But I'm also keenly aware that the funding you have for adult Ed is a zero sum. So like nobody's getting more and money based on the enrollments you get. It's your money is largely fixed. And so you have to make the best choices you can for how to prioritize where the needs are.

And so absolutely, outreach, equity, good. But if I'm looking at CTE enrollment, or better yet, let's say adult secondary education enrollment, where the numbers are even much different, 1.8% versus 10.7%, this is only a problem if you have educational levels of attainment among Asians that are particularly low.

And so what I would want to do in your shoes is take a look at population demographics for those who don't have a high school diploma. Does that, for your specific region, and say, OK, 6% have less than of Asians within the community have less than a high school diploma if we've got our ASC, which would be presumably, this is the current enrollment.

Well, is there an equity? A little bit. But it's not as pronounced as that. So just want to approach it with some caution and think really carefully about your denominator. Who you're comparing to?

And so getting back to something Harpreet asked about intersectionality. That is not a thing this does as well as I would love it to do. Because case in point, yeah, you might find disparities among some subgroup populations, but you won't know that-- but you'd want to be able to drill into other components. So like for example, educational attainment, there are usually variations in gender.

So if you have, among African-American populations, you see an equity gap in terms of enrollments there, well, is it an equity gap among African-American women or African-American men? And so I'll talk more about that really briefly.

And I do want to just echo what everybody is saying in response to Cindy's questions. Absolutely, workforce development board has a lot of great information, but it's just really think you want to-- there's nothing that replaces the community engagement. Because these are the people who, in your communities, are going to hire your students. They are the ones.

And depending on what you're training them to do, they may not have the same level of economic, social mobility, at least to start. And so you want to be able to also build the path to an actual job with an actual person.

So anyway, all right, moving really quickly, adult Ed transitions here, similar kind of a thing. Allows you to drill down and make some comparisons. I should add that the percentage here is the percentage of those who have achieved this outcome as opposed to just the overall.

And as you can take a look at this statewide, it's always going to occlude some things. And so you're going to see more greater variation among your individual regions, lots more are transitioning to CTE.

One of the things that I like to do when comparing proportions this way is to look within the groups. So are there some populations that are performing at like less than 80%, as well as the highest performing subgroup that can also help to identify some gaps.

But also, this can tell you a little bit about variations on who's-- in this case, its numbers aren't particularly significant, but it's interesting that women seem to be transitioning at slightly higher rates than men. But they're not transitioning into non-developmental college courses. This is only 1% So I wouldn't make any major plans on it. But it's something to look at and drill into with your local data.

Cindy asks, how are these transitions determined self-reporting other? I'd have look into the data dictionary to be sure, but it's not self-reported. It is a match of some kind that happens with the community college MIS data and TOPS Pro. Having said that, it is a fuzzy match. A lot of schools don't provide a Social Security numbers. And even when they do ask for that information, if you're dealing with non-native speakers of English, who are recent immigrants, they may not tell you the truth about that or they may avoid it altogether.

So lastly, labor market information. No, I'm going to stop here. Allows you to drill into the macro region, microregion, and a specific county. Some of your consortium regions span more than one county. And so this can be useful for you to just compare and get a better sense overall.

One of the things I like to do is really focus on typical level entry level of education. So, OK, if you're trying to plan for jobs for students who are getting some kind of certificate, then I might filter on that and say, OK, well, as you can see, health care, social assistant, no grand surprise, that's going to be very high. Fastest growing is also that. However, I would also add that while this doesn't tell you-- here it is, good.

[inaudible] jobs, median hourly is $15, living wage is $25. That could be a problem. I will say, however, that not in every case is a disparity in living wage and median earnings in issue.

It just depends on-- because there are also jobs that have for which there is a social good. Or in the case of home health aide, it's often a job that, again, non-native speakers of English can gravitate toward and be a really valuable second job for households.

And so just other considerations, I will allow you to explore student stories on your time. What's nice is they do present a couple different profiles that can be useful for helping to inform people about the differences in the adult populations.

So I'm going to stop sharing my screen there and ask Mandilee--

Lisa Le Fevre: Or Holly.

Greg Hill Jr: Or Holly.

Mandilee Gonzales: I got it.

Lisa Le Fevre: OK.

Greg Hill Jr: I actually accidentally closed it on my end.

Mandilee Gonzales: You're good.

Greg Hill Jr: If you want to skip through all that to the considerations one. So yeah, this is a super fly by on these things. But at the very least, maybe these will float around in your head and you can say, what did you mean by that later. And I'll be glad to answer.

So you heard me talk a little bit about choosing the right denominator. And so if you're doing proportionality, what you would do is compare, OK, what the two percentages. It's really important that if you're looking at enrollment or performance really too, what you choose as that denominator can lead to very different interpretations.

And so think back to those with high school diplomas versus the overall population. Regional variation. I don't know if any of you've been to the Kern County consortium, but that is an enormous area.

And so it includes Mammoth in addition to Bakersfield. The needs in Bakersfield are going to be very different than the needs in Mammoth, but we're only drilling into this level of detail. And so you're going to want to explore what regional variations there might be in your locale.

And sometimes, they're not as pronounced and may really rely on local knowledge. Like in Ventura, for example, there is East and West County and there are differences. And you wouldn't know that, by looking at it, but there are.

Intersectionality, this is the question Harpreet asked about people's experiences are shaped by multiple factors. And so the educational needs and outcomes for like Hispanic women might vary from those of Hispanic men.

And so this is where you want to drill in and try to get more granular data where you can and leverage your TOPSpro data, leverage your MIS data to see performance in more granular ways as a counterpoint to what you're seeing here.

And I would also add, if you don't do that, you kind of risk what's running into what's called a Simpson's paradox problem, which is where there is a trend that kind of appears in different groups of data, but disappears or reverses when the data are combined. So you can Google it or ask me about it later.

Integration, which I'm really saying is don't use data from a single source. Integrate different sources of data. The point one of using data ever is comparison. Single data points mean nothing, unless you're comparing it to something.

Asset-based inquiry, try to focus on your strengths too. So it's not just gaps, but who's doing well? How can we build on it? Always be aware of the data limitations. Are there gaps? Are there potential biases?

For example, undocumented immigrants are almost always undercounted, particularly in rural areas. Yeah. And so timeliness, we've kind of addressed as well. Sometimes data available doesn't truly reflect the needs, the characteristics of the community. And so you want to, again, make sure that you're trying to have more integrated approach.

And then lastly, and this is a kind of part and parcel is that community partner engagement, that, what you're seeing with people. It's not an either/or, it's a both and. And these fact sheets and all of these resources are meant to be inputs, not answers. And it is your job to coordinate and utilize these things effectively and responsibly. And it's our job to help you do that. So OK. That's everything I got.

Lisa Le Fevre: Thank you, Greg. That was fantastic and wonderful. And thank you to everybody for engaging with your questions. We're going to move quickly to the next slide. We have just a few minutes just to see if there's any other questions or take one or two that we might want to answer now.

Again, we're going to have another session on Monday that we're going to dive deeper in this. You're all welcome to it. And we are offering support. Thank you for those who reached out already. I will follow up. But let me just ask, does anybody want to ask a burning question either about the CAEP fact sheet or how you think you might use it?

Great. OK. Is there anything in chat there? Let me see. Great. OK, great. So we can move on to the next slide. And again, please join us for our next session. But here's the information to both the fact sheets. And there is a CAEP fact sheet how to guide. These are the URLs for both.

Again, once these slides are remediated, they will also be available to everybody. So that's useful to know. And then moving on to the next slide, we do have a second webinar coming up, which is part two. We're going to do some more deeper dives here into the fact sheets. That's at 10:00 to 11:00 on 08/19.

We also have two asset mapping sessions. So Greg noted that community partners are important and doing asset-based inquiry is important. The asset mapping series will help us think through some of that. The first one is kind of an intro to asset mapping, which really has an emphasis on community-based asset mapping.

And then there's the second one, which goes into it further. And we're going to take into consideration the three-year planning process for CAEP. So those two are on the horizons. Again, if you're looking for some support, we can give some half an hour support sessions on these things. Please email me. And we can set up some time.

Yes. Part two will be shared also. And I am going to move to the next slide real quickly. And again, you can feel free to contact us. It concludes our session today, though, I'm going to turn it over to SCOE TAP.

Again, thank you for the engagement. Thank you for attending. Feel free to reach out to us. We're always around. And also, we do have a link that's is SCOE TAP is going to talk about, which is an evaluation. We use these to inform where we move forward.

So for example, if you have any sort of burning question for the next session, throw it in there. We'll try to get it in and answer.

Greg Hill Jr: So really quickly, and thank you all for the great and kind words. We put the fact sheet help link in chat. And so yeah, I think I can grab that brief in just a second. There are a couple comments indicating that the asset mapping aren't listed on the site yet to register for.

And so there we go. Good. And so presumably, that will be addressed in the next few days. So if you aren't seeing it, please reach out and we'll make it happen. Yeah. It's scrambling some of the timing for this is not what we would like. So thank you. All right.

Mandilee Gonzales: All right. Thank you so much, WestEd team. As always, it's been a great session. We had a lot of robust questions, as well as discussion. And we do appreciate you walking us through the fact sheets.

Everybody that is on the call today, thank you so much for joining us. We do appreciate you taking time out of your day. As mentioned, and mentioned, again, the evaluation really does inform how we move forward, how we support you, how we continue to bring that professional development to meet you where your needs are. So make sure you let us know exactly how the session went for you, how we can improve or how we did good.

We will be seeing hopefully most of you on the 19th. And stay tuned. You will see all of the registration links on our events page. Thank you, everyone, and have a great day.