Sudie Whalen: Thank you, Renee.

Jay Wright: Hey, hello. OK, I'm just getting this on my screen, and I guess I'll just double-check. Does everybody see the PowerPoint on your screen right now? Here, I'll go to the cover to make it a little bit better. So does everybody see that on your screen? I've got a double screen, so I've been known to have that a little bit off in the past. So I'm just making sure everybody sees what they should be seeing.

So here is our agenda. We're going to have-- we're going to be a little bit experimental today. We're going to be doing what we're calling a reverse panel discussion. So we have three panelists, I'm one of them. Sudie Whalen who you can see on your screen is the second one, and Carol Hirota, who you can also see on your screen, is the third one. So we will be the three panelists.

We will be doing the panel discussion in reverse, meaning we'll be asking you questions instead of you asking us or having some moderator ask other panelists or whatever. You're going to be the askees, and we're going to be the askers, basically. More on that here in a little bit. We're going to-- these are our introductions here. Before we got into the reverse panel though, this was based on a session from the CASAS Institute back in June.

It was a very innocuous session called Mentorship and Collaboration for Data Managers that was at the very end of the institute. It was one of those that I thought I'd get 12 or 15 people at the end of the institute. Everybody pooped out or everybody insta-pooped out, you might say. So we'll just limp along on this one and get her done. But then, miraculously, 300 people showed up and it ended up being an unexpectedly vigorous session for everybody, energizing all those great adjectives.

So that got me thinking on stuff. I got talking to Sudie a couple of times. I got talking to Carol a couple of times, and before you know it, we hatched a new session. So I do want to recap from that just because it was the antecedent to this. Some of the concepts were started from that session. And then, we'll do-- we've done the panel introduction, but I'll let them do a little deeper dive. One big thing here is, why on Earth should you care why these panelists are asking you questions?

So it's in reverse. So the panelists have to explain themselves a little bit. Why are you wasting your time with us? So that's part of the reverse panel as we accept a little bit of onus that way. And then we'll get into some questions. What can we do for you and then what can you do for us? We're going to keep it simple, maybe four questions on each category, going back and forth, trying to do some extra fact finding, you might say.

So again, here are the panelists. I introduced Carol, introduced Sudie, introduced myself, more on them here shortly. OK, so here is a recap from that session is, again, we started by just saying, hey, what issues are keeping you awake at night? Focusing on data managers. We'll be talking about everybody but the focus will be on data managers a little bit because that was obviously the big focus of what we talked about at the CASAS Institute and that's what Sudie and Carol and I have been talking about here over the last couple of months since we did that session as well.

How can we orient some of the things we do to benefit data managers? How can we be thinking about this role in a more meaningful comprehensive way, et cetera, et cetera. So we started as an icebreaker. And this is probably what got it so rollickin' as we just asked, what's keeping you awake at night? We could have gone for hours on end and not even bothered getting into any of the other questions here.

So a little bit of recap on some of the things I like to talk about with this is, first off, you see that little gendarme there. We'd like to talk about the data police, sheriff going to get you. So everybody's a little worried about that. That's how you start, what's keeping you awake at night, dealing with the state, dealing with the feds. Which sheriff is going to get you this time on all of the myriad of things you might do wrong.

Another one of my favorite little topics is alphabet soup. That, of course, starts with, everybody loves alphabet soup, right? How many people love alphabet soup? Raise your hand if you love alphabet soup. Everybody's going to raise their hand, right? Who doesn't like alphabet soup? So we've talked about that in the sense that everybody loves it, but, hey, it can be a pain because, hey, when you have alphabet soup, what always happens no matter what? Anybody want to help me out in the chat. What's always the problem with alphabet soup?

Anybody? No. Not enough-- well, not enough vowels. OK, somebody is a stickler for precision out there. I was just going to say not enough letters in general. But if you're having trouble with vowels, that's an even better answer. But hey, you're trying to spell data, D-A-T-A. Good luck finding a single A in that bowl of alphabet soup, much less two A's to spell D-A-T-A. Good luck with that. Mission impossible, right?

So you're doing long sentences, and then you really can't spell nothing. That's a big problem. So I relate it to data in that you never really have enough vowels, you never really have enough letters to spell everything. No matter what you do you've got 125% chance of being incomplete all the time. There's never enough vowels to spell anything when you've got that darn alphabet soup. And then my final thing just to kick the cobwebs out and bring everybody back into this is that House of Mirrors analogy.

How many-- this is less unanimous but how many people are House of Mirrors fans? Everybody loves alphabet soup, but House of Mirrors, everybody's more like 50-50. Half the audience loves it, half the audience can live without the House of Mirrors. So whichever way it is, I'll just say, if I'm in a house of mirrors, I'm always like this guy in the picture. I'm always looking over my shoulder trying to look over those mirrors, so I can see the back of my head thousands and thousands and thousands and thousands of times, right?

That just trips me out, how many times you can see the back of your head and that's that whenever you do-- for-- I think it's Isaac flippin' Newton we're talking about here. For every action, there's an equal and opposite reaction. Isn't that Isaac Newton? Any physicists here? I think that's an Isaac Newton thing, right? That's my observation. Anyway, so Isaac Newton says, for every reaction there's an equal and opposite reaction. That's the house of mirrors.

You do something to fix your data. You're thinking you're doing something fam-flippin'-tastic, but before you know it, all that fantastic work you do caused an equal and opposite reaction. You've got all these unforeseen problems you unwittingly created. You fix those problems, you unwittingly create more problems. You fix those problems, you unwittingly create more problems, and so on and so on and so on. You can't-- no matter what you do, you keep seeing the back of your head, right?

So those are my analogies. That's what keeps you awake at night, or at least that's my story and I'm sticking to it. We've got those problems that always keep us awake at night. Getting more to brass tacks, we talked about rudimentary stuff, training networks to opportunities that might benefit this role and then we got a little cutesy, talking about stuff like coaching and mentorship and how can we collaborate within the region and across the region.

And then, we also talked about, hey, everybody's job description. Good luck if you can even name your own job description. But job descriptions usually do a laughably bad job at accurately describing what anybody does. I know that's true about my job description. Most people admit, yeah, my job description doesn't really say all that much. So we talked about what you really do at your agency and got some really interesting answers. And then, related to that is how can we leverage this. That's where the reverse panel, hopefully, will come in and say, how can we start leveraging this position?

Some of you I know have done a lot of leveraging, on the down low and to your infinite credit, I would say. But there's gotten to be more of that in recent years, that's something that really has been a benefit. OK, so rudimentary stuff people want to-- this is back in June, everybody wanted more face-to-face training, more face-to-face networking. We made all kinds of high-falutin' promises. I'll just say that was a, "funny thing happened on the way to the forum," Part Deux, though, where everybody thought, we'd be all face to face by now.

But here we are. We're still frittering away, zooming our lives away, watching those sands of the hourglass disappear before our very eyes just like we've been doing for the last couple of years. But we hopefully will get back more into that as we move along. And then more access to networking, maybe not a big California thing, but we added that TE network meeting for all states, not just California. For my two cents, that's been a successful evolution.

So then, moving on, we talked about how are we going to leverage this role. So, hey, if you're thinking, Gee Willikers, nobody's done nothing on that one yet, I'll just say, that's not true. We did do something, not nothing. We made some plans and began discussions to plan this session right now. That was my take-home item. Hopefully, it at least moves the ball a little bit.

And then over here, we were also talking about, Gee Willikers, we'll look at things like mentorship and coaching when that was also addressed by some of these discussions the three of us have to plan this session. So before I move on, I will define it. This was where we all three talked, is just so you know what we're talking about here, we're using the term mentorship, we're using the term coaching, we're using the term collaboration.

Collaboration, we're thinking everybody knows what that is so we're not doing a definition. But coaching, just so you know, for this session, we're saying, that's where an experienced person supports a learner in achieving specific goals by providing training and guidance. Very generic definition. It can be lots of different kinds of training and lots of different kinds of guidance. But just so you know, there's the definition.

And then mentorship, good luck finding a definition that doesn't use the word within the word to define it. I couldn't find one that did it, so we'll just have to go with developmental relationship between a more experienced mentor and a less experienced protege or mentee, that's how we're going to be defining it here, OK? So I think we don't want to spend too much more time getting into line item by line item debriefs.

Let's get into the purpose of this presentation. So here's the list of panelists again if you missed that at the beginning. I don't think many of you did. But again, part of this is to introduce yourself but to introduce yourself with the idea of, hey, why might you want to listen to questions? Why am I answering Jay's question or Sudie's question or Carol's question be worth your while? So to be fair, I'll start before putting Carol or Sudie on the spot.

So my name is Jay Wright from CASAS. I'm putting myself on the panel because I came up with the idea to do the discussion, I guess. But also, I was the one that did that session at Summer Institute. I really think we did have a good discussion, 300 plus showed up. Lots of people aired all kinds of dirty laundry. I like it when people do that, contrary to popular belief. So I wanted to get the clothesline out and see if maybe you might have some handy to air it out more.

Hey, if you've got some really moldy stuff there at the bottom of the pile, that's even better. The moldier the laundry you're airing out, the better for me. So that's why you might want to listen to my questions. So I'll move it along. Sudie, you're next. I'm going-- starting with the bottom, working my way up. So Sudie, your next step on the elevator, why should people be listening to you?

Sudie Whalen: Gee Willikers, Jay.

[laughter]

Jay Wright: That's right, Gee Willikers is the only good answer for that one.

Sudie Whalen: [laughs] So I don't want to murder your dirty laundry analogy. So I'm going to leave that one where it was--

Jay Wright: OK.

Sudie Whalen: --but I'm Sudie Whalen. I'm the CALPRO Deputy Director and I'm also the PLC Institute Coordinator. And one of the conversations that Jay and I were having, that spurred his brainchild of us doing this, was just thinking about how can we be more supportive and how can we provide more guidance and more support and information and research-based best practices on how to approach data from a mentorship and a coaching perspective.

When we initially started the conversation, I was thinking about the PLC Institute and how can we reinforce that within the PLC Institute in the coaching that we provide via the PLC Institute. But we realized there was a much larger conversation that support is needed in a lot of different places. So part of the reason to listen to me and to engage in this conversation with me is because I and the rest of CALPRO genuinely care about your input, and we want to make sure we're being responsive to what your actual needs are.

And so, if that means airing the moldy dirty laundry so we can figure out what that is, then we definitely want to hear from all of you. And we also want to talk about what we do actually provide and how we can make that even better by being responsive to what data managers, those who work with data managers, those who receive information from data managers, and anybody within that sphere needs, whether it's through our institutes, through our training, or even by doing webinars and different events.

So we just want to make sure that we're being responsive to your needs and that we're leading with data and not trying to make data lead us. So that's my spiel for why I'm here, and I'm going to pass the buck over to Carol. Gee Willikers, Carol, what do you think?

Carol Hirota: OK. Thank you, Sudie, and thank you, Jay. So I am currently working with targeted technical assistance with the CAEP TAP Office. I am one of the staff, one of the coaches. We are working with-- there are five coaches and five in consortia that we are working with. And the team that I'm working with-- I actually have the opportunity to work with their person who is responsible for their data and their assessment.

So it's been a real nice opportunity to see how we can use coaching in that process. My past experience, though, has been a principal and director in Stockton at Stockton School for Adults. And we worked on the professional learning communities and data teams. And I have to share with you that the success of our teachers and our administrators and the counselors was really the data accuracy and the collaboration of the student data technicians at the school.

What they did was so valuable because they needed to make sure that everything was accurately placed in or they corrected it depending on if there were any mistakes. But they also worked very closely with the teachers on sharing reports, weekly, monthly, and quarterly. So I think the role of that data person, to me, is like a foundation so that our teachers and counselors and administrators do the good work to show evidence of student learning, and I think that's critical. So thank you.

Jay Wright: All right. Thank you, Carol, and thank you, Sudie. So we'll get into the questions here now. We've got four or five questions trying to keep it as simple as possible, four or five or in this category right here, What can we do for you. And you won't be that surprised to know the other category of questions is called, What can you do for us. So we're trying to keep it real simple that way.

We'll start with some questions. And again, we're going to ask you what sort of things can we do from CASAS point of view, from CALPRO point of view, from the CAEP TAP point of view. Maybe there's some other little threads with what I do, with what Carol does, with what Sudie does that also might be helpful. But with that in mind, what sort of things might you like to see from the various individuals and organizations that might allow us to do a better job leveraging the role of data manager, promoting that role, helping you do your job more easily et cetera. Hand up?

No? OK. I thought I saw a hand.

Sudie Whalen: Brenda, did you have a-- Lydia. Sorry. Did you have a question?

Jay Wright: I saw a hand up but it was taken down, so I guess I'll take that--

Lydia Jones: I was just waiting for you to finish, Jay. You know how I roll.

Jay Wright: OK. OK.

Lydia Jones: You know you can always count on me to put my hand up first.

Jay Wright: Yeah. OK.

Lydia Jones: That--

Jay Wright: Go ahead.

Lydia Jones: That idea of support is so intriguing, especially for those of us data managers who have been around for a while and have had to build in our own support systems for a wide variety of reasons. That is a fantastic idea just across the board. So that comment, I want to get that out of the way first is to have that support system. That would be amazing in whatever context that ends up developing to be because there are data managers who are teachers, there are data managers who are admin, and there are data managers who are classified staff.

So how that role ends up playing out, how that-- because traditionally PLCs are built for teachers. So how that would end up playing out for a data manager role would be very interesting. But the idea of having a support system for data managers is amazing because, like I said, those of us who have been around the block for a while, we've had to build our own support system, and usually, it is not within our agency

Sudie Whalen: Thank you, Lydia, for pointing-- for bringing that up and pointing that out, that PLCs are-- well, we like to say teacher-led and student-focused. But they also have to be driven by what data shares with us, right? And so it's really important for those who are engaging with professional learning communities to have a close partnership with their data managers so they can get data and not necessarily in real time but in a timely manner so that they can utilize it with those PLC teams.

And so having that structure in place that enables the-- and empowers the data managers to be able to do that without additional stress is really important. So I think some of these questions that we've got here today will definitely help us with identifying what some of those needs are and what that picture perfect support system looks like pretty well. And I just want to see as you're jumping in, thank you, Lydia, for being a really great example.

She jumped on camera and she unmuted and she shared with us. If you can't be on camera, that's OK, but please feel free to unmute and tell us what's on your mind and join the conversation because this is definitely a discussion-based session.

Jay Wright: And as we said, we are the question askers and you are the question answerers. So part of the process is, we really are hoping you might answer a few of these questions. OK. So everybody's had a chance to read these questions. I won't read them off. We'll get going here in the interest of time. But here is the first question looking at people new to the job.

The second question will be more on experienced folks. But at that session, there were a lot of people new to the job. It's a very daunting task for people who are new. That dominated a big part of that discussion at the SI session and it definitely is a recurring theme at TE and WIOA II network meetings. So I'll just ask and-- what type of training and resources might allow somebody to get started as somebody new to the job.

Are there specific skills we need to work on building? Is it less about skills and more about just giving opportunities for networking? What sort of things could any of us do to help new people get started with this task? And, hey, Lydia, jump at it. You got it.

Lydia Jones: So for me, I relied heavily years ago on-- there was no one in our area-- well, let me rephrase that, in our agency who knew TOPSpro Visual, who was willing to train, who was willing to do any of that. So it was myself, my boss, and the TE support. So I was all by myself. So the opportunity to have a mentor or to network with people and get some help, I think, is amazing. So having the network where you can call someone or have someone sit with you is fantastic.

I'm not taking anything away from the tech support because they're amazing but having to call Kevin Locke and Patricia McBean every single day--

[laughter]

Like, I'm pulling names from back in the day.

Jay Wright: Right, right, right.

Lydia Jones: I will never forget when Patricia was like, thank god, someone with a brain. But it was just-- it was-- I-- so I got.

Jay Wright: Two and half hours of time with Kevin, nothing beat it, did it?

Lydia Jones: Well, I mean, he had to set my password several times, so I had to learn the hard way. So that networking opportunity and being able to diversify who you're calling and get different points of view is fantastic. And now that we're in a different world of adult education and we have a consortium, encouraging the consortium managers to, hey, if you have another data manager who knows what they're doing in your consortium, go ahead and let your data managers talk to each other.

If you don't have data meetings, maybe you should start having data meetings. It doesn't always have to be about the individual. What do your data managers actually need? Do you know? Have the conversations with both of your data managers or all of your data managers and some consortiums are amazing at this, and some of them are not. And that's from very small consortiums to very large consortiums and everything in between.

But having those conversations with more than just one person there or just one person who is making all the decisions, I think is very, very important. And having multiple voices is very important. That's my two cents.

Jay Wright: All right. Thank you.

Lydia Jones: [laughing] five cents.

Jay Wright: Doreen, you've got your hand up. What do you-- do you want to contribute there, Doreen?

Doreen Odonovan: Yes, I'd like to address the calling technical support every single day for six months. There's got to be a better way to get somebody onboard than relying on tech support. When you go to the checklist, it's how to do a test. It's not how to set up TE. Setting up TE without integration into our SIS system was just insane and took so long to get the hang of it.

And there's got-- there just has to be another way rather than calling them up every single day to ask another question. And I'm like, where would I have found this in the documentation? And they point me to a 72-page document. We need a checklist to understand uploading those templates by hand. There's no-- there's nothing in sight for me to get automated because my IT department is so busy doing other things.

And so I'm going to continue to have to upload every single template multiple times a semester. And I think I might finally have the hang of it. But I'd be totally happy to work with somebody to go through everything that it took to get to where I am now to create some sort of training specifically for a new person.

Sudie Whalen: So what I'm hearing, Doreen, is the need for better onboarding and better onboarding resources so that someone who is brand new has access to-- here's the quick way to get the things that you need to get instead of just a very long document that they scrub through and have to call a lot to get support.

Doreen Odonovan: Yeah, it's-- I mean I refer back to the actual TE upload list all the time. And that's not on site anywhere that I know of. I mean, I have the data dictionary and I live and breathe the data dictionary too. But there are just so many things that we learned along the way that I don't think we had to learn the hard way. And the other-- and the quirk of it is that I'm at a college rather than an adult school and everything is very adult school-centric and not college-centric and we're different.

Jay Wright: You're from Cabrillo, right? If you don't mind my asking.

Doreen Odonovan: Yeah, I'm-- this is moldy, moldy laundry. So I checked--

Jay Wright: OK, there you go. It's all right. That's what we said.

[laughter]

Bottom of the pile.

Doreen Odonovan: It is at the bottom. I checked to see who else is online before I even spoke, and I--

Jay Wright: Oh, OK. There you go.

[laughter]

Carol Hirota: Thank you, Doreen.

Jay Wright: Well, people are liking what you had to say. I'll say, any other hands up? Anybody else want to address anything, I'll just say, hey, Kay, Linda, and Usha, a lot of really good comments here on the chat. Any of you wanted to add to what you chatted?

Carol Hirota: Well, there's a lot of comments about the data team process within the consortium, and I think that there have been some sessions that are scheduled or were scheduled. So I think we can kind of catch up on some of those. I believe South Bay is doing one this afternoon. I know Poway has a data team. So what does that look like when you have your data manager working together with your teachers and your administrators and your counselors and your transition people?

I think that's critical. And I know I believe-- let's see who-- who? Oh, Francisco talks about how he mentored and assisted colleagues in his consortium. And I think that should be an expectation. Someone called out your consortium manager. So how do we work all together, you know? I think that's very important.

Jay Wright: OK. Well, this is good feedback. Thank you. I don't see anybody else's hand up. So, hey, we've got other questions, so we'll go ahead and go to the next one. And hey, I'll let Sudie, maybe, take command and control of the second question.

Sudie Whalen: Thanks, Jay. So our question for you is what additional training will provide the timely information needed to continue to excel for you all as a data managers and those who support data managers, including skill building or networking opportunities? We've already heard networking opportunities. We'd like to see more data meetings within the consortium groups, better onboarding. But what other training needs do you have?

And I see a couple coming up in here. Tutorial on advanced filtering would be really useful. OK. Good to know. Other training needs. And if you want to unmute and come on cam and share, please do let us know what additional training needs do you have aside from what's already been mentioned. Go ahead, Lydia.

Lydia Jones: So coming out of the newer user. And I know Jay knows exactly where I'm going with this. So coming away from the newer user a little bit, but as far as skill building for the advanced user, that would be fantastic. Something that-- and this would have to be really thought out about a little bit more and at a little bit deeper level. For someone who is already familiar with some of the schemas and the topics that we've discussed a lot.

But for those advanced users who want to dig deeper into their data, who want to know the whys, and who want to go-- I don't know. Gary wants to go into statistics, and we talked about that at the Summer Institute session a little bit, but that would be great so that we cannot get-- and this is going to be bad, but get a little bored with the day in and day out of our job.

So to keep it interesting-- and then, of course, always networking. Networking is always great. But as far as taking it up to the next notch so that we don't become complacent with our jobs for those of us who have been around the block.

Sudie Whalen: So do you mean going beyond just cleaning up and sharing what the data is but actually doing some data analysis and trending notifications and things like that--

Lydia Jones: Yes, I do.

Sudie Whalen: --to identify equity gaps and those kinds of things?

Lydia Jones: Mm-hmm. Yes.

Sudie Whalen: Great. Anyone else? Really good suggestion. Maybe host a monthly networking meeting.

Jay Wright: Doreen?

Sudie Whalen: Great. Thank you. Go ahead, Doreen.

Doreen Odonovan: On the positive side, I walked into the position where we were already doing reports at the consortium level of the consortium data. And so there were some existing, basically, PowerPoints that they were used to looking at. And I refined them a lot along the way. And I've never shared those with anybody, but my systems are close to set up, they could be better. So that I copy and paste the blue sheet, the agency report, into Excel and it creates some reports--

Sudie Whalen: Nice.

Doreen Odonovan: --that are-- it doesn't go straight to a chart because you have to pay special to clean things up, but it definitely takes you to an entire PowerPoint around enrollment and TE going-- and literacy gains and everything in charts and graphs because we're not showing directly out of TE to the board. And we haven't-- I've never been to a training where we looked at how to take that data to the board.

And then the other thing that we did is the board said, great, we want it by region, and Jay is familiar with this fun-fun project. They wanted to know North County versus South County, and there was no way to do that in a reasonable manner in TE. And so we asked for a flat file. Now, I don't know if Jay wants everybody to know that that's a thing, but with that flat file, I was able to do all kinds of analysis way quicker and easier than pulling out out of a PDF.

Jay Wright: OK. Chris, you've had your hand up too?

Sudie Whalen: Thank you.

Chris: Yeah. And this is a shoot-the-moon thing that just came up a little recently. Maybe a simple tutorial on statistics because what we did recently is, we had-- we took two courses or two classes, and we looked at the attendance rate for both classes. And they were-- one of them was in the evening, one of them was a day thing. And there wasn't-- there was a little bit of a change, but there wasn't a big difference.

And so, four of us and our leadership team sat around saying, so who remembers their statistics? Who knows this? Is this a big enough difference? It's an actual difference or is this just some little piddly thing that happens because of random chance? And no one really quite knew the answer to that, so if-- that would be a neat thing. I know it's off left field, but I thought I'd bring it up.

Sudie Whalen: It's a really good point. And I think I'm like-- I'm totally hearing everything we're saying. Doreen already has created her own little tool so that she can do that data analysis piece and maybe larger understanding of what CASAS can provide, so we can get more regional information as well as better ways to share these data reports and information with stakeholders.

But then, I'm also hearing that need for a better understanding from a statistical standpoint like, do we all have a shared understanding of what this means? And I really like the point that you just made, Chris, in terms of what really does indicate a trend and what is too narrow of a margin to count as a trend. So I think that's also important. What about for those who are supporting you or for those who have to work with?

Do you-- can you think of any kind of training needs that-- for example, I'm a PLC leader. What do I need to know in order to know what to ask you for or what are the things that you wish people would know when they come to you with these kinds of requests? What kind of training support can we provide to those who are supposed to be there supporting you or that you provide information to? Go ahead, Lydia.

Lydia Jones: So I think that that's a question that really is district by district. In my agency, it very-- it goes through the director of every program. So I don't have the PLC leads coming directly for me for information. In the wayback machine, they would. Everything now goes from as a lead to the director, from the director to me. So I don't know what to say. So it is very interesting. It makes things a little bit more colorful.

So it very-- it turns into a game of telephone, trying to figure out what exactly do you need to effectively look at data? Especially when you are running through the gambit of admin turnover. We've stabilized at my agency as far as that's concerned. But then, it is the retraining of high school admin into the world of adult education which is always fun. And then once they get it, then it starts all over again.

And then a new director of adult ed comes online, and you're like, OK, we're now switching gears and reevaluating so it's-- and I'm sure we're not the only organization who has had that flux going on. But again, we're finally stabilizing, but at least as far as medium-sized agencies that are trying to work within our confines, I don't-- I no longer have the luxury of being able to speak with my PLC leads and saying, all right, so what exactly would you like to look at and what are you trying to accomplish?

It very much is program director letting me know this is what they want to look at--

Sudie Whalen: Right. OK.

Lydia Jones: --which makes things a little bit challenging.

Sudie Whalen: It does. I hear-- I completely hear what you're saying. And I know, for our participants who go through CALPRO, PLC-- not PLC but Leadership Institute, they get to hear from Jay and they get to hear from Carol about how does-- what does this data mean? How do I utilize it? That kind of thing.

But what I'm hearing is a broader need of teachers and teacher teams to understand what data is available and what specifically to ask for when they're requesting data from data managers, just to make that game of telephone a little bit more streamlined and clearer. OK. Thank you. So I think at this point, Jay, we're ready to move on to the next question. I see your comment, Francisco. Admin and clerical turnover is an issue and that's not the first time I've heard that too.

So thank you all so much for sharing with me on that question, and I'll pass it back to Jay.

Jay Wright: One other quick thing is, Lydia and Priscilla, I'll just say, you can scroll up. You've been beckoned. I'll leave it up to you, Lydia, and you, Priscilla, whether you want to respond to the chat or not, but I'll just note you're being called out. OK. So, Carol, I'm going to let you take the ball on this next question about types of opportunities.

Carol Hirota: OK, so the next question we have for all of you on this call today is, what types of opportunities will help you leverage all that you know and do? And who needs to have a better understanding of what you do and why it is so important? And so far, I've heard that there's been some turnover, learning of roles and responsibilities. I'm also curious to know how many of you work in isolation as opposed to working with a team at your site or your consortium.

So, please, comments, questions.

Jay Wright: Somebody's hand-- I don't-- can't tell who. Oh, Lydia. Oh [chuckle]

Carol Hirota: Lydia. Thank you, Lydia.

Jay Wright: Like I needed to ask.

[laughter]

Lydia Jones: So there are times where I feel like I work in isolation. I'm party of one. And yet, when there are projects, obviously, I'm in the director's office. And then I work with her team which are under-- the directors under her. But then, if there are problems at the testing sites, then I go out to the testing sites and troubleshoot all those problems. So it is-- the data manager is not a-- it's collaboration when it needs to be.

And then, it's isolation when you're working. And it's not-- it can be exceedingly lonely, especially if you're someone who enjoys talking to people--

[laughter]

--and you're an extrovert, so it's not always the most fun. But if you enjoy data and digging and trying to find out where the problems are and problem-solving, then it's great. But it is lonely.

Carol Hirota: Thank you, Lydia. So I'm reading the chat also. There's quite a few people who are in the same situation as you. They all work in isolation. They're working in a small consortium. I do know that there are some opportunities if your teams are in like a PLC, a professional learning community, because then you're working with a team and not in isolation.

I don't know if there's anybody out there that has that opportunity to work in a professional learning community or a data team or any kind of a team where you don't feel like you're working in isolation. Can anyone else out there share what their experiences are? So that your why like Lydia is asking about data, you all work on it together. It's not just the data manager all alone.

Lydia Jones: I can tell you that I've asked.

Carol Hirota: OK, thank you.

Lydia Jones: I have asked for data meetings, and I have asked to be teamed up in our consortium with the other data manager since we're a small consortium, and I was told no. So that's what led to my initial comment early on.

Carol Hirota: OK. Lydia, you've got an invitation in the chat, so go check it out. Doreen? You have your hand up.

Doreen Odonovan: I work with five researchers, but I'm only assigned 20% to the consortium. But I still have the access to all of them and a manager that's awesome. And so I have access to the SQL database for the whole college, and they're teaching me how to use SQL, so I can get enrollment data and stuff from there as well. So I'm feeling very lucky, and anybody can reach out to me too off of my email. And I would love to hear from more college people, Lydia.

Carol Hirota: Thank you. Thank you very much. Kay also has a comment in here about the differences between large and small agencies, absolutely, perhaps establishing a network of data managers from a small agency with mentorship support. Thank you, Kay. A great opportunity. So more formalized. Thank you.

Sudie Whalen: Erica has her hand up.

Carol Hirota: Erica. Thank you.

Erica: So our consortium, what we do is that we have monthly meetings with all of the other data managers within the five schools within the consortium, including the college within our consortium. And so, we all work together to bring up issues on the table, what each school is experiencing as an agency as well as our data. And so we all work together to ensure our data is matching to where we all have set standards.

So all of our data consolidates together, so we're not having different issues. We're not looking at different things at the same time. And so we've even discussed together, OK, the definitions of our using the data dictionary. We've discussed certain things of how we can tag things to determine as a consortium, and it has helped along the way. For a while, I've always been alone because we're a very small agency compared to the other four schools that I work with.

And so having that network as well as that reliability of for me to just reach out if I have one data question, they are able to answer any questions and everyone has different perspectives of how they work things. And so it really has helped us on our consortia coordinator getting us together and discuss these issues and getting everything-- everyone to be on the same page.

So it really helps a lot to have that discussion with your consortium coordinator for all data managers to work together to ensure that the data is being inputted correctly as well as bring up issues where maybe some person is more knowledgeable than others. And that's how we're able to learn together and train each other.

Carol Hirota: Thank you, Erica, for sharing that experience that you have with your team out there in your consortium. I'm also seeing in the chat, Maria, if you want to unmute and share about your working group of consortium members at its NAC, NAAEC. If you want to share that experience so people will have a better idea of how you work within your consortium.

Maria Einaudi: Sure. Hi, everybody. I'm Maria Einaudi. I'm a transition liaison at Oakland Adult and Career Education. And there are some other people here in this meeting whom I work with as well. So the consortia is made up of a variety of adult schools and the Peralta Community College District. And we have been looking at data for a few years now. And we've have been bumpy because where we pulled data from, what are we supposed to be adding-- entering data into, I think some people here may be using CommunityPro. We have stopped using CommunityPro.

And the community colleges have a different reporting system in the adult schools. So we were spending a lot of time looking at definitions of things that we should be tracking and how to improve upon that, how to improve and make data systems more usable, user friendly. One of the other things, though, that I mentioned in this is that we all have different access to parts of the data. And so you can't drill down in the same depth if not everybody is sharing the exact same system.

So anyway, that's that. And we meet pretty regularly, at least once a month, sometimes twice a month. Sometimes, if it's demanding a little bit more.

Carol Hirota: Thank you.

Maria Einaudi: But we also do have the manager. I'll stop real quickly in a moment. But the manager of our consortium is doing a really excellent job of tying all the pieces together. OK, thanks.

Carol Hirota: No. Thank you very much. I appreciate your comments about your experiences in the Peralta area, community college area. To meet more than once a month just tells you how much you guys value your data and how much you are making that a priority to get together. I also know, and we'll go on to the next question, but Richard from South Bay consortium made a comment about talking about shop with other people.

I do know that they do have a session this afternoon on their data team process. Richard, do you want to unmute and make any comments about that or then we will move on after you make your comment? Thanks. OK, Jay. I think we can move on to the next question.

Jay Wright: I thought he was here too. OK, so looking at just overall statewide activities or anything regional. We've covered this, I think, within Carol's question. Some of you were looking for networking with small agencies or networking with specific roles and so on. But just keep at any specific activities that we could offer from a statewide perspective or anything that we could facilitate locally that you think might help.

I see a lot of comments on the chat that address this already, but I'll just say, does anybody have anything you wanted to add on this? OK, Doreen.

Doreen Odonovan: I was just thinking about this duality between the adult school progress with CASAS and the college progress with the student success dashboard and LaunchBoard and getting people to understand how you measure progress at the college was really hard. They really wanted to see our CASAS data. And we're like, no, CASAS doesn't have anything to do with adult ed at the college level. You have to look at progress of students progressing through ESL levels.

And they're like, well, is there a test? And they're like, no, it's whether the teacher passes them or not. And they were just horrified because they're doing this super fancy, are we testing everybody and what level are you at? And at the college, we're like, oh, yeah, we think you passed the non-credit class, and that counts as [inaudible].