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Hi, everyone. And we're going to get our screen back up here really quickly. So good morning, and welcome to our session on the CTE Pathways Mapping-- Avoiding the Road to Nowhere. This presentation is about the work we've done it WestEd to deepen our understanding about how courses and classes offered by adult schools and community college non-credit providers align with the local labor market information. And it's to really to ensure that students have the opportunity to build skills that lead to living wage jobs in your local region.

So I am Blaire. I'm a Senior Project Manager at WestEd. And while I'm new at WestEd, career pathways has been central to my work as an adult educator. I've taught. I've done research. And I provide a professional development on career pathways and transitions for a very long time. In fact, I was in the classroom when some of the first workforce programs came into play. But now I'm going to turn it over to Allie to introduce herself as she's really the one who's steeped in this work, and she's the backbone of what you're going to hear here today. All right, Allie?

Yeah, thanks so much, Blaire. Hi, everyone. Good morning. Thank you for joining us today. I'm a Program Coordinator here at WestEd, and I've been working on this data project in adult education, collecting all of the CTE courses and programs for adult education providers. And I also work on a lot of our T14 pathway mapping work that looks at alignment between high schools, community colleges, and the labor market regionally in California and Nevada. And I also work quite a bit on the K12 Strong Workforce projects.

Thanks. Can we go to the next slide? So just a little bit about us-- we are the Postsecondary Education and Workforce Group. And our interest is really in ensuring that adult learners and non-traditional students can access educational opportunities, whether it's through adult schools, non-credit community college programs, and/or other postsecondary opportunities, such as apprenticeships or transferring to four-year colleges or universities in meaningful ways, which allow them to achieve their educational and their occupational goals. So ultimately, we're looking at increasing the economic mobility for low-income families and communities. Next slide.

And some of our lines of work-- you can see them here. We do, for example, this is the K14 career and tech ed mapping. We are working on launch boards and dashboards, informed planning and decision making, such as the adult education pipeline or the community college pipeline. We delve into data by asking or identifying questions that help administrators, instructors, researchers think about the pathways, who are there serving, what's working well, and what might need to be strengthened or possibly bring up some questions, and then move to a solution process.

So including things such as identifying a root cause or viable explanations for the trends that have been identified. So we really look at supporting people in the field by developing data tools, assisting in implementation, and leading conversations for data-informed conversations that lead to educational success and, as I said on the previous slide, economic mobility.

So today, these are the topics we're going to run through on the California Adult Education Program Outcomes. We're going to look at the Mapping Project. We're going to look at what undergirds that, the purpose, methodology, and structure, what we learned doing this project, and then we're going to look at the Data Tool. And Allie's going to do a live demonstration.

So please write your questions-- any-- in the Chat. And we'll either address them directly or save them until there's a good break in which to address them. The other possibility, as we were told on the front end of this presentation, is the Q&A questions that located down at the bottom of your screen. Next slide-- I am going to turn it over to Allie, who can talk a little bit more in-depth about the project, and its purpose, and all the things that underlie it.

Yeah, absolutely. So this really started with us looking in-depth at the launch board. And the launch board shows adult students who complete a CTE course or program but no really details about what type of program. And there's no consistent data source for that detailed information. And we really wanted to understand what existed in the field currently, what's being offered, and how that maps broadly to the labor market.

So we're really focused on understanding the continuum of courses offered by adult education and on-credit providers in California, looking at the relationship between adult education credit programs and regional labor markets in California. And our goal is to support local pathway development, both for consortia and administrators at adult schools and how to better track pathway data for students.

So this is one of Randy's favorite charts that I also like to bring up because this is a manual process of mapping out how adult education connects to community colleges. And part of our goal and working in this data dashboard and collecting all of this data is to find ways of making this pathway mapping a little bit easier-- finding ways of connecting these programs in a way that can be, maybe not automated, but a little bit easier to search for, and create a framework that allows other people, other administrators, other researchers to align data and think about pathways throughout the system.

So a little bit about the methodology of this project-- we started out with a small team of coordinators and research assistants looking at all of the course catalogs for adult education and noncredit. So we took a sample of about 15 colleges in California and 20 adult schools and looked at what was in the course catalogs and developed a field structure based on that-- what we thought would be feasible to collect and what would be valuable information for the field.

And then we went out, and we searched through all the websites, all the course catalogs to look for those programs of study and the course titles, course descriptions-- all of that good stuff. We downloaded the college noncredit information from COCI, and we used employment data from EMSI. The next step was really to classify everything. We looked at what was common. We looked at common courses.

We looked at how those aligned or maybe didn't align to occupations and occupational titles, such as the SOC codes-- the Standard Occupational Codes-- and looked at how those related to college programs, both noncredit and credit, and came up with a classification system for adult education courses that I'll get into shortly.

And we also conducted 14 interviews, just a few brief interviews across the region. We wanted to get, as much as we could, a little perspective from different adult schools across the state to enhance our understanding of what we were finding in the course catalog. And then we developed these data tools out of the work.

So in the main data set for adult education, these are the fields that we collected data for. We have all of the courses and schools segmented by region. And we developed a number of course groupings. So all of the data elements that are in the green area of course groupings-- those are classification systems that we developed to understand and help find a framework of mapping adult education courses to community colleges and to the labor market. All of the course characteristics, alignment with CC, and certificates, and apprenticeships-- those data elements were taken directly from websites, course catalogs, brochures-- anything we could get our hands on that had any kind of information about specific courses or specific programs that were being offered in California.

We conducted most of this field scan between August, 2019 and February, 2020. So we were hoping to get a pretty good sample of what was being offered in the '19-'20 year. Although, of course, we know at the start of 2020 in the spring, there were quite a few courses that were impacted by COVID. Although we didn't have a great handle on how those were being impacted, we did collect some limited data about how courses were revised, or canceled, or rescheduled.

So we scanned 521 institutions, including every CAEP consortium member and additional community college providers relevant to the study. Among those, we found 225 agencies that provided CTE and workforce preparation courses. So from those 225 agencies, there are over 7,000 course offerings between community college, noncredit, adult education, and other agencies, such as ROPs and community-based organizations. So there's a lot of good work going out in the field. We found so much CTE education. And we know that there's more out there that we probably missed in the course catalogs. And so we know that there's a lot of really interesting work going on.

These are our main classification types. So as we were looking through and doing an analysis, once we had gotten all the courses together and all of their course titles and descriptions, we looked through our data set and tried to figure out a way of classifying all these courses and understanding how they fit together, especially understanding some of the qualitative information we have from the field.

So the first classification is the occupational training program. And these were courses or programs that we found that were very much teaching towards a specific identified occupation. They often had a certificate or a state licensure associated with them. They also often included work-based learning. They usually had a higher level of instructional hours-- over 150 hours. And their course descriptions usually noted pretty specific occupations. For example, a medical assistant-- that was a full program and was intended to get a specific occupation of medical assistant.

Those were pretty common, but the most common classification we found where these occupational skills builders. They were a little bit more amorphous or harder to put our finger on in terms of how they specifically aligned to each other. But what we found is that many of these occupational skills builder courses included a specific skill or certificate of completion. So it's really looking at something like QuickBooks, or Adobe Professional Certificate, or some very specific skill in an occupational area.

They usually had a intermediate level of instructional hours. Some of these included recertification for professional occupations, or refresher courses to help people get up to speed, or learn new things that were coming out in their occupation. They were generally geared towards an industry but, , perhaps not an occupation. For example, a QuickBook certification course might be targeted towards office assistants as well as general business managers or even, perhaps, within the health field or in other fields where there might be assistants who are doing both medical procedures and working in the front office.

So they didn't align to a specific occupation, but sometimes they aligned to specific industries. And the course description was often very focused on the skills-- the specific skills that were being taught and how it related to multiple occupations, or how it could be applied to a specific industry. And these were the bulk of the courses that we found. There were a few career exploration courses. These were pretty short. They usually said career exploration. They were usually targeted towards a specific industry and had a pretty low level of instructional hours.

Separately, we found a good amount of workforce preparation courses. And we define this roughly aligned to the WIOA title II definition-- so basic skills unrelated to a specific industry or occupations, such as keyboarding. Sometimes they were basic soft skills, basic certificates per the WIOA title II guidelines, and generally had a low level Instructional hours.

Once we got all those classifications together and understand the different types of courses and programs being offered, we started to align those to the occupational clusters. So there are 23 major occupational clusters. And we Additionally grouped these into what we call Meta Clusters.

We did this because we noticed that there were quite a few courses-- for example, in the business meta cluster, there might be courses that are related to or specifically targeted towards office and administrative support occupation, but those courses often had skills that were related to those three other SOC clusters in those financial operations, management operations, sales and related occupations.

So we wanted to develop a overarching framework that allowed us to look at common skills between courses that would help an individual or student move through a pathway, move between industry sectors, and understand how they could build a career for themselves.

So here, we're getting into some of the more detailed data. What we have here in the blue is for each meta cluster, the percentage of occupational training courses is in blue. And in the orange is the occupational skills builder courses. So health was the closest that had the most occupational training courses.

It was a 50-50 split. But most of the meta clusters we looked at had the vast majority of their courses were occupational skills builder courses that were really targeted towards helping students who were already in a specific occupation and wanted a promotion or maybe wanted to change jobs or change companies, get a very specific skill in a specific area, so they could continue on with their career.

Of the workforce preparation courses, we found most of them were Microsoft applications, basic computer skills, and general workforce readiness. Of the career exploration courses, the vast majority were in the field of health. Very few other sectors had career exploration courses that we could find. Although, we understand that some of the career exploration might be embedded into other programs or other areas or might be workshops or events that weren't clearly detailed in course catalogs. So this is just a brief overview of what we found in terms of standalone career exploration courses.

Hey, Allie?


Let me interrupt really quickly. There is a question in the Chat that where they asked, what was the education level of the skill builders? Was it some college?

So those were just the adult education courses. So the occupational training programs were really just training programs in adult education.


Yeah, so they don't have a some college-- they don't have any college requirement, necessarily.

Allie, this is Randy.


So what I would say about the skills builder courses is they're not really organized by, I would say, educational level related to occupation. They're really just discrete skill sets, like medical terminology, that people find valuable. And so they enroll in it because it's something they feel like can actually make them more employable. So they aren't necessarily directly organized always by a particular educational level or type. So they may be more-or-less sophisticated, even though they're more one-off courses or standalones often.

Yeah, exactly. So what we worked on after that is we started to compare the grain size and comparing courses to noncredit and community college CT offerings, occupations based on education level, and segmented the data statewide and into regional views. So we realize that this is a little bit of comparing oranges to apples. But it is the most nuanced grain size that we could get to for most of this data. So we're looking at those adult education CT offerings in terms of specific courses. We're looking at non-credit programs, and we're looking at community college awards-- so the number of degrees offered. And we're looking at occupational annual openings and segmenting that data into different views.

So I know we got to a couple questions, but I wanted to pause again and see if there were any additional questions about the methodology before we move on.

Allie, I don't see any meaning in the Chat or the Question and Answer feature.

All right, well, let's keep going then.

Oh-- so there's a quick question from Neal. Could you use this data to build sector pathways?

Yeah, I think so, especially if we're looking at a meta cluster view, I think that might be a helpful way to understand how courses that were previously siloed might actually relate to each other, which was the intent of that framework. So that is my hope for this data.

Yes, and to tag on to that, at least the data that I've been looking at and playing with it-- it's really interesting, and it could really inform both building into particular sectors of building on those sectors and then as well, looking at the skills and understanding how a sector has lots of different occupations or how skills can move between sectors, so that learners could also look at more expansive pathways or meandering pathways. There is another quick question. Allie, where is the data available?


Oh, sorry-- I see you answered it. You're faster than I am. [laughter]

No worries. So yeah, we will demo the dashboard that we created out of this. There will be a link in the Data Element section or the Data Sources section that links to the full adult education Excel data set. And we'll send a link to the dashboard to everyone once we demo that.

Do you have data that shows if the meta categories are tied to local workforce development board info?

No, we didn't go that deep into this project. Although, that would be an interesting next step.

As a side note there, we did approach the state workforce board about pulling data from them for this study. And they actually didn't classify the provider types in ways that actually made the data useful to incorporate.

Thanks. So I'm just going to touch a little bit on the high-level warnings and also how this work is supported by other work in the field and research. And I just want to take-- as you can imagine, the amount of work that's gone into-- the detailed work that's gone into putting together this dashboard and the multiple uses of it. We touched a little bit on how you would build some pathways. But there are a lot of other ways that you can use this also to look at career counseling, I would say, for adult learners.

So basically, what was found in analyzing this data is that regions across California-- as Allie noted-- that there's a mix of occupational training courses and skill builder courses as well as the different sectors. One of the interesting pieces is that at least a third of the adult education schools, they don't have any courses clearly listed on their website or associated brochures.

And the implications of that is it makes it difficult to align pathways to identify clear transitions between both the adult schools and the community colleges-- noncredit, but also with credit programs-- and then as well as limited or information that's not clear on services that are offered by the different schools. And then it's also unclear from websites and course catalogs whether the CTE courses had integrated learning, whether they were matched up with basic skills, ESL-- if those are matched and integrated.

And then as far as what the usefulness of this, beyond what's already been identified, is that the small amount of research in the field supports this need to begin to build and make the pathways clearer to students for transitions to employment or postsecondary opportunities. So are more delineated. So that the research is showing that well-articulated pathways are found to assist nontraditional students and adult learners to attain certificates and transition to credit-bearing courses. So both noncredit and credit certificates as well as transitioning into other aspects of postsecondary opportunities.

And then lastly, that it's really important to align competencies that allow those skill builder students to return for additional courses and into credit-bearing classes. And then I said lastly, but actually, I have one more lastly-- that the way the clearly articulated pathways and the way courses line up or classes, regardless of what they look like, align with occupations, when they are informed by labor market data that it appears as though it leads to stronger labor market gains for students so that the wage increases and the job stability are higher for those students who are able to initially see and learn through their classes. There are different opportunities, and that those opportunities actually align with the labor market data. Next slide.

So as Allie said, she's going to do a Data Tool demonstration, which is really fun. And as we go through this, we're talking about the importance of it. But also, thinking about how you might envision using this information-- would you use it for program creation, modification, would you use it for student counseling? Feel free to write in the Chat what you're thinking about as well as if you have questions, put those in the Chat also-- and the Q&A is available.

And then Neal, you have a couple of questions. How do you see this platform working with Centers of Excellence? Is this something that can help the CAEP consortium with identifying regional labor market info by industry sector? I think that that will be yes. You can certainly chime in, Allie, but from what I can tell, yes, I think it's a really essential tool for helping consortium identify the regional labor market by industry and also how courses are aligning with that as well.

Yeah, yeah, I definitely agree. And I really hope that the field takes this information and some of these frameworks and really runs with it and enhances and develops more nuance in how we're classifying different courses and how we're mapping them to the labor market. And that would be awesome to see.

All right, so we'll get into the statewide meta cluster summary real quick. The dashboard started because we had made these initial graphics segmented by each meta cluster for the entire state of California. As you can see in some of the detail, we have the adult education training courses, the noncredit training courses, community college credit awards, and then the labor market data in yellow.

And we have, at the bottom, all of the occupational skills builder courses. So these were static graphics that we had created based on all of our data. And we thought it would be really cool, is if we could make this interactive and figure out a way to segment it by region, and give it a little bit more depth. So that's what we did. So these static graphics were our model for developing the dashboard itself. We have a little bit more detailed view of the adult education occupational training is in blue, community college noncredit in gray, the college credit awards in green, and then the annual openings in yellow-gold.

And in these, we also included some examples of the occupational support courses. So we really only focused on aligning the more rigorous, specifically, occupational-focused training courses to the labor market because the occupational skills builders were really supportive courses. But we included those on the dashboard as well. And I'd be interested to hear from you all today and from the field what might be more interesting ways we could include occupational skills builder courses and the dashboard and make them maybe a little bit more clear, or find ways of segmenting them to make them a little bit more searchable.

So here's the dashboard. I will drop the link into the Chat real quick. And then we'll get into the live demo.

All right, so here's our dashboard. Can everyone still see my screen of the dashboard on Google?



Awesome. So when we first get to the dashboard and we're looking at it without selecting a metal cluster or without selecting a macro region, we're looking at all of the data across the entire state. So the first thing we'd want to do is really focus on a specific meta cluster. The dashboard is designed to really look at occupational training programs and annual openings related to that meta cluster.

So I'll pick health. It's often one that has quite a few programs. So now, once we've picked a meta cluster, we're looking at the entire state-wide view. And this cluster will-- this filter will filter all of the charts as well as the occupational skills builder courses. So now we're only looking at all of the training programs and skills builder courses related to health.

I'm currently in Oakland, so I'm going to look and see what's going on in the Bay Area in my local region-- understand a little bit more depth about what's happening here. So now this macro region has filtered all of the charts. And it's also filtered all of the occupational skills builder courses. So now all of the data on the dashboard is looking at everything related to health in the Bay Area. We can see in adult education training programs, there's quite a few programs in medical assisting, phlebotomy, pharmacy. Interesting, there's some different community college noncredit courses.

There's a lot of EMT, medical assistant, home care aide. So there's a little bit of difference here between adult education and noncredit. Community college credit awards-- there is dental assisting, medical assisting, biotechnology, psychiatric technician, vocational nursing. So that's interesting. We've got a pretty wide spread of different occupations across the educational spectrum.

Over here, on the right side, are the annual openings by occupation. And we've segmented these with some additional filters, so you can go in and get some more nuanced data for those annual openings. So in the Bay Area, I want to just look at the self-sufficiency hourly wage. So I want to look at occupations that only meet the self-sufficiency wage for the Bay Area, which is $20 an hour.

So now we've got that filtered. We're just looking at those self-sufficiency wages. And I also really just want to look at middle-skill occupations. So these are the Centers of Excellence-defined categories for occupations. Below middle skill is usually just a high school degree. Middle skill includes some college, no degree, a postsecondary certificate, or an associate's degree. And then above middle skill is really focused on bachelor's degree and above. So I'm really just going to focus on these middle-skill occupations that meet a self-sufficiency wage.

So we can see that most of the annual openings here in registered nurses in the Bay Area. There's also quite a bit in medical assistance, dental assistance, licensed practical and licensed vocational nurses. So it looks like the educational system, for sure, on the medical assistance is meeting the need in the labor market, which is pretty awesome. So these filters here in the orange will just filter this occupational data.

As we go down, we can look at all of the specific skills build our courses that are related here. There's a lot in medical assisting, patient care, medical records. And we've segmented all of these occupational skills builder courses as they relate to general pathways as well.

So down here is the Data Sources and the Data Update Request form. Here is the adult education noncredit data that we've pulled directly from course catalogs. And you can access the full Excel document through this link here. It'll take you to a box folder where you can download the Excel file of all the adult education courses. And we've also included a short survey form here for you and your school or your district to ask to update any of the data in the Excel document.

So if there's anything that looks off, if there are a bunch of courses that you think are missing, if you have some suggestions about classifying courses in a different way, you can enter a form here. And we will hopefully respond to you pretty soon, and talk to you about your specific situation, and get that data updated for you. Are there any other questions about the dashboard? Anything else?

So looking at the Central Valley Fresno area-- so these are just the macro regions as of right now. We haven't done a deeper dive into the subregions yet. But that would be an interesting next step here. So we can look at a Central Valley Mother Lode as a whole. And one of the things is the self-sufficiency hourly wage is really focused on specific regions.

So you'll have to uncheck this in order to get that labor market data as you move between regions. So then you can do the self-sufficiency hourly wage for Central Valley. So I had to uncheck the Bay Area self-sufficiency hourly wage in order to see the labor market data.

Yeah, so feel free to email me. I'll drop my email in the Chat. If there's anything that looks off, or if you have any additional questions as you're perusing later, and you are welcome to submit a form and ask for an update for the data.

Allie, can you just go back there? People are asking if your school wasn't included, how do they do that? Can you just go over the form really quickly?

Yeah, absolutely. So you would enter your full name, organization, what school you're with, and your email. And you can, if you want, talk about what specific school you want to update data for and then some comments regarding your data update. And I will get back to you via email that you submit in the form, or you can email me directly if that would be helpful. Generally, I would wait to collect a few updates. It's a manual process to update the data in the Google dashboard. So if I have a bunch of requests coming in, I'll deal with all of those, and then update the data on a monthly or quarterly basis on the dashboard.

A couple of questions-- one is what does it mean if nothing shows up? And that's, oftentimes, the fact that sometimes you have to refresh your screen to pull the data back in. I know that that occurs for me unless there's something else that's going on. Allie?

Yeah, if there's no data showing up in a specific chart, it could be that there's no courses associated with that meta cluster in a particular region, or it could be just a refresh error as well.

The other question is that when you choose one meta cluster, or will it only show state data? Yes, unless you choose a region, and then it will localize to that region.

Yes, exactly. And you could, if you wanted, you could select multiple. So you could go here, and select IT and Engineering as well as Business. So you could look at two meta clusters maybe somewhat related to each other. And then look at a particular region. So I'll look at the Bay Area again.

You could also, maybe if you are looking at the Bay Area, and you also want to look at North Far North, you could select two regions at the same time and look at how those regions are together. So you don't necessarily have to select just one meta cluster or one region. You can select any combination that you'd like. Any other questions coming up?

They want to know if we'll do more webinars on this. And I believe the answer is yes, we're putting together a schedule and thinking about how we should move this tool more fully into the field. So we'll, I'm sure, advertise that and broadcast that through the CAEP newsletter and other sources once we get us a generalized schedule filled out. Otherwise, you can always contact us and see if we can put something together for your region.

Yeah, so there's a question about LMI for adjacent states and regions. As of right now, we don't have those embedded into the dashboard in any way. So we'd like to hear from you guys a little bit on those reflection questions we talked about earlier and how you would envision using this information. How would you use it for program creation, modification, or maybe student counseling? You can write in the Chat. And let us know how you think you might want to use this data moving forward.

So the courses that show up for-- one of the questions that popped up in the chat is, are the courses that show up for community colleges also adult ed? So those community college courses are noncredit. And we've separated the noncredit from the credit courses.

So someone said that they could envision using it for student transitions work. I think, absolutely-- and particularly for planning for those transitions and informing career pathways and explorations, and looking for different positions and jobs, or the postsecondary opportunities that need to follow. It might be because in some of the learnings that the pathways aren't necessarily well-articulated as being familiar with what's going on in your region, both from the course offerings as well as the occupational data, and then being able to inform conversations with that as well.

Connie says she would like to do a teacher training on how to use it incorporated into some of the classes. Yeah, that's a fabulous idea, Connie. Oh, interesting, Margie says for recruiting students. I think that that's a really smart way, especially recruiting them into a pathway that you can demonstrate the end goal, but also in looking at different skills that your students may need.

Yeah, I think that's really interesting about recruiting students. One of the things that's come up in a lot of different conversations regarding transition more generally is students' perspective in decision-making, that too many options can be really overwhelming, and there are students who aren't really sure where to start looking for information.

And I think as we're in the midst of this COVID pandemic is making sure that information is clear, concise, easy-to-find, and structured in a way that helps students make decisions. So it's not overwhelming and all over the place but really clear and organized, I think. And especially online, as more people are investigating things online, that's been in a lot of our conversations as well.

And I'd also make a plug for, I think, Neal, it was you who noted that a lot of the adult education students fall into the lower skill or below the middle skill categories. And then so it's also a good way to look at-- so you've got these occupations that students can go into. What are the transitions they need to have? And what are the educational levels? And build in some stronger integrated educational programming that could speed those lower learners up into some of those middle skill positions and occupations. Yep, apprenticeships, pre-apprenticeship efforts, exactly.

Trying to get through. Looks like the Chat has slowed down with all these great ideas. I hope everybody was able to catch them as you went through them. Yes, I think-- Kim writes, you should probably use this information for a variety of reasons, including those listed. Precisely, I think that's the point, is that this tool is so useful in multiple different ways, whether it's recruiting, whether it's for program planning, for program offerings, student counseling-- that they're really-- it's a very useful tool.

But it's also the work in identifying what's going on in your region and aligning among the different organizations and institutions that are offering these different educational opportunities. All sorts of programmatic information from where they could be used, like Perkins regions, strong workforce.

Yeah, Judy says, maybe it could be used for the Perkins regions while completing the comprehensive local needs assessment and Perkins application for the next round. That's really interesting. I'd love to hear more, Judy, about if you do end up using the tool, how you use it in those applications. Great. Well, thank you guys for all your ideas. They've given me some more ideas. And I look forward to hearing from you all about making sure that the data is clean, and up-to-date, and doing all the things you need it to do.

Allie, can I add one thing real quick?

Yeah, of course.

I just I just put something into the Chat. And I just wanted to punctuate this. So we are having some early conversations with a couple of different regions about how to use this tool and the data sets to inform stronger regional pathway planning with colleges and adult educators. And we are very interested in taking it into the field in a very interactive way to support your local planning process.

Secondly, we're having some early loose and dangerous conversations with the San Diego region about what it would mean to use the data to inform more adult learner friendly visualizations that help them understand career pathway opportunities, not just within their local adult school and college, but within a regional context. And so we are very interested in people who want us to work with you. And that's a big part of our scope of work this year, is how do we take these things in the field and make them more effective? And I would highly invite you to reach out to us if you're interested.

I'll just put the contact information-- I'll put it in the chat.

Great. Well, thanks, Randy. That was a great segue into our next steps here, is really releasing this information into the field, doing some more professional development training, and getting the work and this dashboard out into the field. So please contact us and let us know if you'd be interested in exploring this work a little bit more in your region.

Allie, there's a quick question-- where can someone get the college credit data?

Yeah, so I downloaded that from LaunchBoard actually, I believe. But you can also access it through DataMart.

A little bit of time left if anybody has any more questions, or we can--

[audio out]

Yeah, Neal says using this tool as a way to leverage a variety of funds and sources to create those pathways. And that's apprenticeship RFA will focus on adult ed pre-apprenticeships. Yeah, pre-apprenticeships are really moving into the forefront as a strong educational programming option.

Margie, if you just want to let me know or Allie know that you want to join that San Diego work, we'll put that up. Out emails are in the Chat. I'll put them in. Let me grab them. I'll put them in again. Or Randy, if you have Randy's email. Margie, can you see them now? Blaire, you need to make sure that panelist and attendees are selected, not just panelists.

Oh, that's-- yes, OK. There we go. Margie, can you see that now? That's why you couldn't see the link either. [chuckles] OK, it's so simple. It's a literacy issue that I have, right?

That means all my brilliant responses, I don't think, went out to anyone.

But they were brilliant.

They were brilliant, but we can just live in the knowing of that. I just posted Randy's email in the Chat as well. Thanks, and Allie posted, as you can probably all see, the dashboard link. Super. I think if there are no other questions, or if you don't want to revisit anything, I think we can say all is well and good and give you a few minutes back in your day. Thanks, Connie. It's artillery. It's what happens when you--

Actually, it's artiller.

It is artiller.

It is? OK, so I had it right. Thank you.

Unless they felt like they wanted to cut the end of my last name off.

Well, they do the same to Allie's name.


All right, Bur, I get the joke. It's been a joke since I was in youth bowling league.

So presenters, are you good? You have a lot of time. [laughter]

Well, I think we covered the information, Allie, unless you feel like we need to revisit, or if somebody would like us to revisit something, as you said, we certainly have the time. But it's also-- we don't want to keep people here if we feel like we've covered the information, and the conversation can be continued on at somewhere else. OK, yes-- can get lunch ready before the break in lunch session. Allie, how often is this updated?

So I haven't made an update yet. We haven't had anyone that's really contacted me with a lot of details to be updated. But if I did get a lot of requests for update, I would collect all those. And depending on how many requests, maybe update on a monthly or quarterly basis. But just for the 2019-2020 year. At the moment, there isn't any plans to do the next year of all of the courses.

Yes, we will upload the slide show and the recording. That will be done in a couple of days, I believe, is the time it takes to do the recording. And then I think that we'll provide a link to the presentation.

Absolutely, yes, all information will be made available on vFairs site as soon as the CAEP TAP staff get it. So on that note, folks, my name is Melinda Holt. I'm your tech host. And I'm going to remind you that there's a lunch session as well as one more session after lunch. So we have another question from Neal.

So we didn't actually contact specifically adult schools to get our course information. We looked at catalogs and websites. But in terms of the few interviews we did, no one refused to give us an interview.

Nobody refuses. There you go. [laughter] All right, I'm going to go ahead and in the meeting. Please remember to fill out the evaluation after you hit that Continue button. And have a great lunch. Bye bye.

All right, thanks, all.

All right, thanks, you guys.