Dr. Jeremy Roschelle and Dr. Pati Ruiz from Digital Promise join the podcast to discuss their learning sciences research into AI's role in education. They share details about an innovative project using AI to improve student reading literacy and explore frameworks for developing AI literacy and responsible use policies in schools.

• Practitioner Toolkit from Digital Promise, provides resources for collaborative learning that are flexible, adaptable, and rooted in real teaching experience
• Challenge Map, from Digital Promise
• U-GAIN Reading, program from Digital Promise seeking to amplify new knowledge about how to use GenAI to create content that matches each student’s interests and strengths, enables dialogue about the meaning of content, and adapts to a student’s progress and needs
• AI Literacy, framework from Digital Promise to understand, evaluate, and use emerging technology
• SceneCraft, program from EngageAI Institute with AI-powered, narrative-driven learning experiences, engaging students through storytelling, creativity, and critical thinking
• As they face conflicting messages about AI, some advice for educators on how to use it responsibly, opinion blog from Jeremy Roschelle
• Teacher Ready Evaluation Tool, helps standardize the way ed tech decision-makers evaluate edtech products
• Evaluating Tech Solutions, ATLIS is an official partner with ISTE to expand the presence of independent school vendors and technology solutions in the Edtech Index
• If you are interested in engaging in research with Digital Promise, or just have a great research idea, share a message on LinkedIn: Jeremy | Pati

More Digital Promise articles:

• GenAI in Education: When to Use It, When to Skip It, and How to Decide – Digital Promise
• Hearing from Students: How Learners Experience AI in Education – Digital Promise
• Meet the Educators Helping U-GAIN Reading Explore How GenAI Can Improve Literacy – Digital Promise
• Guest Post: 3 Guiding Principles for Responsible AI in EdTech – Digital Promise

NAIS, welcome to Talking technology with ATLIS,

the show that plugs you into the important topics and trends for

technology leaders all through a unique Independent School lens.

We'll hear stories from technology directors and other

special guests from the Independent School community,

and provide you with focused learning and deep dive topics.

And now please welcome your host, Christina Lewellen,

Hello everyone, and welcome back to

talking technology with ATLIS. I'm Christina Lewellen, the

President and CEO of the Association of technology

leaders in independent schools. And

I am Bill Stites, the Director of Technology at

Montclair Kimberly Academy in Montclair, New Jersey.

And I'm Hiram Cuevas, Director of Information

Systems and Academic Technology at St Christopher school in

Richmond, Virginia.

Hello, gentlemen. How you guys doing

this afternoon? So nice to see you again.

I'm hanging in there doing all right. So glad,

enjoying life.

I want to ask you guys, how are things

going with AI before we welcome our guests on today, I was kind

of curious, you guys are in the school year. You've done all the

back to school fun stuff. Where are we at with AI right now

taking a temperature?

So interestingly, a few things. One, we're in a

strategic planning process, and AI is one of our focal points of

that. So it's definitely a hot topic. Late last week, we had a

meeting with our AI Task Force, and as I mentioned, just before

the pod started, I had a meeting with my head of school where we

spent a good majority of the time talking about AI. So it's

definitely front and center. The one thing that I was happy to

have the conversation with my head of school about is that

when we talk about AI, we need to be focused on it, not just

for how we are using it in the classroom, but how we are

thinking about it in the operational areas within the

school as well. So I think that those can often be overlooked. I

think that those are areas that often try to operate in

isolation from the other policies and procedures that

govern the school, and making sure that we are clear on how we

are talking about AI as a whole school endeavor and not just a

an academic endeavor, is A conversation I'm really looking

forward to having this year

here in Richmond. Gratefully, I think we've

surpassed that tipping point where we weren't just talking

about it, and we've actually drawn a line in the sand, and we

developed a an AI vision statement for our school, and

we've also matched it up with an academic integrity policy as

well, much like what Bill said, we're looking at this also from

the academic side and the operational side, and seeing how

we can incorporate it. Given the announcement that Google made

this summer about Gemini and notebook LM being a core

service, we have opened it up to our faculty and students in the

middle and upper schools. Teachers can use it across all

three divisions, but we're very excited that everyone feels

confident enough that we needed to provide the experience that

the boys need to prepare themselves for the college and

jobs of the near future. And in addition to those, we are going

to be deploying Flint AI as an additional alternative AI bot

for us to use.

That's really cool. It walks in

parallel. What you guys are talking about with what I'm

seeing on the road. I've spent some time with trustees and

leadership teams at independent schools. I have some conferences

coming up where I'll be speaking to admission professionals and

heads of school and different audiences at schools. And so I

think that kind of, I don't even know if it's bifurcated approach

of both the AI in the classroom for education, but then AI just

in the operations and in running a school. You know, I'm seeing

that and talking about that a lot too. So I love the

conversations are evolving past chat GPT, and I'm really excited

to welcome our guests today, because I think that we can kind

of drill into a little bit of this in terms of literacy, and

in particular the learning sciences piece of this. So guys,

I'm welcoming to the podcast today, two important guests from

digital promise. We are welcoming Dr Jeremy Rochelle,

who is the Executive Director of Learning Sciences Research at

Digital promise, and we also have Dr Patti Ruiz, she is the

director of Learning Technology Research at the Center for

Learning Sciences Research at Digital promise. Both of you,

welcome to our podcast. We are so, so grateful that you are

willing to spend your time with us. I'm sure there's a lot of

demands on your time, so thank you for being with us.

It's great to be here. Christina, so I would

love to start by

asking you to help our listeners understand

I think a lot of folks understand the brand of digital

promise that's a. Brand that gets used and thrown around a

lot at our independent schools. But can you explain a little bit

what it means to be learning sciences research at Digital

promise? Tell us a little bit about the organization and how

you guys kind of fit into that place.

Let me just start by saying what learning

sciences is, and actually my back story is I was a computer

science student as an undergrad at MIT in the 1980s and I was

totally fascinated by AI, and there was people doing stuff

with AI and education in the 1980s which seems almost

impossible. It wasn't what we're doing today, but people were

doing stuff, but the direction I took it, I was really interested

in people. And how do people learn things. So what the

learning sciences is, it's not necessarily the Educational

Sciences which might be concerned with, like, what's the

best policy for teacher retention or to prevent drop

outs, or, you know, lots of things are important. The

learning science is really concerned with, how do people

learn, and how do we effectively teach? And so it's really inside

the learning process. How do we make that learning process

better? And so that's what we do in our center. And we have about

35 researchers, and we do work at different points, pre K, 12,

up into university, different subject matters. But our

underlying thing is we want to help every learner to learn more

effectively, learn more deeply as they go. And so we try to

apply research methods to do that.

That's really cool. So what are some of

the projects that I mean, I can take a guess what you guys are

working on, but what are some of the projects that these 35

researchers are focusing on of late?

One of the big projects we have is a R D

center, research and development center funded by the US

Department of Education. And the project is called you gain

reading. And our goal is to take an existing product that listens

to kids as they read out loud, and what the product already

does is it'll notice if they can't pronounce a word or they

struggle in a particular place, and offer them science of

reading based guidance to overcome that particular

struggle. But what we and lots of educators out there observe

is these products have been designed for the typical reader,

but lots of our readers are speaking with an accent or a

dialect or they use different vocabulary, and we're not yet

adapting to fully support English language learners,

multilingual learners and other people whose English isn't the

typical English these products were designed for. And so you

gain reading is all about that. It's about studying the problems

and the solutions to make sure that when we listen to kids,

when a computer listens to kids read out loud, it can really

help them. Patty, you want to add

something about that. Yes. As part of that project, we

are working with educator leaders from across 10 districts

in seven different states, and they're supporting us to help

develop listening sessions so that we understand what the

national conversation is and what educators are really

interested in getting out of these technologies. And they're

also sharing their thoughts and helping us develop an educator

toolkit to be able to leverage digital learning platforms to

support student literacy. So we do much of our work in

collaboration, not just with developers of ed tech, but also

with educators who are on the ground and help us bring that

practical perspective and what actually happens in various

learning environments into the work that we do.

So you're probably seeing that like with

nape scores just came out really recently, and reading is a huge

area, and the level of proficiency that students are at

varies a lot by the characteristics of those

learners and a lot of AI that's out there right now is

addressing very generic problems, to my taste, like

better lesson plans, supporting kids while they're doing

homework. But reading is such a huge need, and we need very

focused things from AI in order to improve reading that's just

sort of general, hey, I'm gonna point the kid at a chat bot

isn't going to turn them into a kid who's say, in second grade,

just giving them a chat bot isn't going to make them a

better reader. So we're really focused on the specific

processes of how kids read, how expert science of reading based

teachers would tutor them, and how to get those to happen more.

It's sort of interesting how this is a

blended project. So I'll say this as a non educator, but I

spend a lot of time in this space, right? And to look at

this as looking at something so fundamental as reading and

language skills, and then supplementing that with an AI

solution is a. Very interesting blend of the kind of

conversations we're having right now around AI right like,

where's the line of making sure that the fundamentals are in

place so that we can create these very discerning consumers

of AI as we move forward? And we'll get into that a little

bit, but I'm just curious if my observation as an outsider is

something that lands with you? Yeah,

absolutely. The product we're building our

work on, and our partner in this work is Amira learning. When

we're working with schools, the recommendation is that they get

a half hour per week of practice with Amira, which is this AI

based tutoring program. I hope they're doing a whole lot more

reading instruction in grades one through three, than a half

hour per week. So clearly, this is like a hybrid situation, and

in particular, we're expecting the classroom teacher to provide

that basic instruction, but what's hard for the teacher is

to spend enough time with each kid, closely, listening to them

read and noticing exactly what's hard for them and giving them

specific spot advice about that sound or that combination of

letters or whatever it is that's throwing them off. There's like,

1000s of specific skills that you have to learn between

kindergarten grade three, and it's hard for a teacher to be

providing that much practice. And so it's really a supplement.

It's a teacher's assistant, but it's not taking over.

So is the AI bot, listening to the students read

that are having difficulty that are not native English speakers,

and processing what they're saying and offering suggestions.

So it's picking up the accent, it's picking up all these

different things in order to make these suggestions. Am I

correct? Yeah,

that's right. That's exactly it. So the child

is reading a book that's on the screen, and maybe a short

passage depending on how old they are, just a couple words

depending on how old they are, and they're speaking out loud

into a headset and with a microphone so it hear them well,

and it's noticing like, oh, you said the first word fine, the

next word was fine. Then you got stuck. And it might even

diagnose what you said wrong as you did that. And then it's

offering you an exercise, perhaps that will break that

word down in syllables and say, Hey, you're it's the middle

syllable. It's the vowel combination that you're finding

hard here. You're doing well on the consonants, but let's look

at how to say that. Oh, you sound because you're a little

off on that. So it's that kind of thing that it's doing, and

it'll give them practicing, and it'll repeatedly listen to them,

and they get little feedback on the screen when they get it

right.

So based on the script that knows what to

expect, and then, therefore, when it doesn't hear what it

expects. It's not breaking down what it heard. It's just

breaking down the word that it was expecting, how to pronounce

that word. It's not doing anything with the word that the

kid actually said. I mean, it's not listening to that word per

se. It's just listening to the fact that what that student said

was not what it was expecting in the way in which it was meant to

be said.

That's right, you're really close. Bill, yeah,

that's right, it is listening to the kid what they actually say,

but it's comparing it. It knows the text. And the cool thing is

that this technique goes back to the 1990s a guy named Jack

Mostow, Professor Jack Mostow at Carnegie Mellon University,

realized in the 1990s that even though computer speech

recognition was really primitive, if it knew the text

that the kid was trying to read, it would be good enough. And so

also, we avoid the problem of fake content. The texts come

from science of reading experts. The computer is not generating

fake content for the kid to read. This is authorized

content, so we avoid some ethical problems.

But it's not a free text reading. It's not like the

kids just coming to it and reading. No, that's right. It's

a prepared text. It's not like a reading companion that I'm going

to read this out loud. No, okay, that makes perfect sense. I was

very curious about how this was actually functioning and how the

AI learning model was working to do this. But if it knows what

the text is, knows what to expect, it makes perfect sense.

Thank you for the clarification. So

on the flip side, then, from a comprehension

perspective, the student who's now going to listen to the

computer make the suggestions if they're having difficulty with

the pronunciation and just literacy in general, imagine

there's additional support in addition to the AI bot to help

them with that piece as well with the auditory component of

it,

Hiram, you got to come join our research team.

You're so right on the ball. What we're doing is we're going

out in the field. We're watching Real schools, children in

classrooms that have lots of different accents going on, not

hard to find in America, and we're watching what happens, and

we're looking for opportunities to improve these conversational

interactions and ways that would work with a greater variety of

students. And actually, that's where AI gives us a leg up,

because, I'd say, five years ago. So the style of interaction

in a product like this would be, if a student does something, you

give them a very pre configured bit of feedback, and it was

spoken. Amir would do text to speech and would say the thing,

but it can only say that thing that the programmer had put in

before, and now it can be more conversational, and you can

actually engage the student about what they're reading, and

maybe you need to do that for a little bit to keep them

interested. It's that guided learning that you're

providing, yeah,

it's more like a person, like a parent or an

older brother might do. We're trying to simulate a much more

natural way of interacting around a text

and then provide that differentiated instruction,

as the various levels within a classroom exist. We're so

excited about this. This is exciting. This is very exciting.

It's

really interesting because we jumped

right into the you gain program and the work that's happening on

the R and D side. And my assumption is that there's any

number of problems you could have solved with the use of AI,

and you happen to walk down this path. So how did you get there?

In other words, how did you decide that this was going to be

where you put the effort, energy focus for right now, and you

think that this is going to be kind of like a bigger gain or a

better outcome than if you had started someplace else, because

obviously AI, there's so many tools, so many solutions. You

all could have put your big brains on any number of research

projects. So why this one?

Happy to give you a little of that back story.

We also realize we're a group at 35 but that's not enough to boil

the ocean, so we got to pick our problems carefully, so we look

at things like the National Assessment of Educational

Progress for clues, and so one of the things that was really

clear to us, looking at that data in the newspaper, what gets

reported, is just scores are up, scores are down. And, you know,

we know that story, scores are down, but there's a persistent

gap for students who are English language learners, where they're

gaining proficiency at about half the rate of everybody else

and reading. We also know from lots and lots of research, if

you're not reading well by the end of grade three, that has

major consequences for anything else in the curriculum. So it's

not only a big problem in terms of, hey, we're not getting

enough kids to be proficient, but it's also a big problem. If

we don't fix this, there's downstream problems that are

even harder to fix, so that's like a really central place to

try to make a difference. And then realistically, like you're

out in schools, we're out in schools, kids speak with lots of

different accents in our schools, that's just reality.

Teachers are telling us all the time these kinds of software

aren't hearing kids well. So as researchers, we don't want to

just improve a particular product. We want to do things

that would help the whole field. And we think by doing the kinds

of things we're talking with you about, it'll help us prove it

with a mirror learning but the things we learn about how to

work with kids, accents will be shared as general knowledge that

any product in this space could take advantage

of. Jeremy, how many different languages does

your application detect in terms of the accents? Because I'm

thinking of like Northern Virginia schools often have 35

different languages represented in their schools.

Yeah, again, you'd be a great researcher on

our team. We would just turn around say, how many do we

really need to detect? Like, how many meaningful variations are

there? So interestingly, I'll just give you an interesting

example. Southern is an accent that's important to detect. The

experts we're working with on this project come from the

University of Pennsylvania, and they're really talented at this

process, and we're trying to empirically figure out what are

the number and kinds of ways to group students so that we can

more effectively intervene with them. So there may be a whole

Arabic cluster, for example, may not need to do every single

language in Spanish. There might be a couple of different

variants that are really important to pay attention to

absolutely and so on and so forth. But it's an empirical

problem, and we're chipping away at it. Do you handle Dyslexia as

well? To some extent, but there is a parallel center. There were

2r and D centers like this funded, and there's one out of

the University of Buffalo that is more about that kind of

thing. But these are all related. They're just different

ways of speaking. And so what we're trying to do is to go from

a system that does a really cool thing, listen to kids read out

loud and give them feedback, and then, hey, but kids are not all

the same, so how do we deal with learner variability?

So can you help me understand how the R and

D piece fits into digital promise?

Before I do,

I want to mention something. So we got

really excited about you gain reading and we might move on.

What I want to mention is our ability to do. What we're

talking about depends on work with schools and getting data

sharing agreements so we can get examples of student voices. So

if there are listeners out there who are school superintendents

or heads of literacy, and they get really excited about this,

we're always looking for schools to work with that have

interesting populations with a lot of variants, and that would

be willing to work with us on the data sharing agreements so

we can hear their students

voices? Yeah. I mean, one of the things

I would think is that we have a lot of boarding schools within

our community, and some of those international students come in

to the states, and I would imagine that there's some

opportunity there. So we can definitely leave all of this

call to arms in our show notes and also as part of our

conversation, because it's possible that there are subsets

of independent schools that might be a really great fit for

you and your team.

Yeah, that would be super cool. We'll put

it in the show notes. Okay, so how does research fit into

digital problems? Really well. I'm happy to report it's the

main thing. It's such a pleasure to be at an organization that so

is interested in and respects research, and since digital

promise does a lot of work that is out there, directly

supporting schools like our league of innovative schools is

a great example. Through that work, we get to learn about what

are the problems really facing school leaders, facing teachers,

parents, students. The league, for example, produces their map

of problems from digital promise, we get the sense of

what are the important, pressing problems, and that helps us

figure out what kinds of interesting research questions

we can ask. We also do a lot of translational work. And what I

mean is, you know, researchers speak in jargon, and they don't

present things in ways that educators can pick up and use.

So I'll toot the horn of one of my colleagues, Judy Fusco, who's

just done an amazing thing. There's a huge body of research

on collaborative learning and how to really support kids in

collaborative learning, and that's something on every

schools portrait of her graduate, you're going to find

collaborative learning, but they can't read the research handbook

to figure out what they should know from research 2000 pages

and in horrible jargon. And so Judy worked with a team of

educators to figure out, what are some high value concepts

from that research. How could we express them in ways that

educators can grab hold of them, and also even produce some

videos showing what it looks like in practice to do the

research based thing. And so we do a lot of that kind of work

too, where, where we're doing original research to study

problems that schools care about, and we're doing some

research translation, I guess I would say if we do a third thing

too, because it ties into this topic of AI, and this is where

potty can come in. For sure, is that we had the opportunity to

be a little bit ahead on the topic of AI, because we were

already studying it before it went big. And so we also offer

our expertise and advice and help policymakers. So maybe

that'd be a great place for you to say some more potty bits in

the work we're doing. That's more policy.

Yeah, I'd love to hear your perspective,

especially because I think that from the perspective of

independent schools, we tend to lean in to AI and

experimentation, as you heard at the top of the show. I'm asking

the guys like, how's it going at your school this year? And

they're walking a path. But I would love to just kind of hear

your perspective and the work that you're doing with schools,

and kind of where you think the industry, the educational space,

is with AI.

Yeah, happy to talk about how we've worked with

district leaders, especially when generative AI came out, we

did a lot of work with district leaders to help them be

responsive and proactive about how they were allowing for use

in their schools and districts. And it was at a time when there

was still a lot of uncertainty about how generative AI was

really going to be implemented in classrooms or not, and so we

worked with a group of League of innovative school district

leaders to help develop and identify the key topics that

they were interested in addressing in their responsible

use policies. I came into it as a researcher, and I'll just give

you a little bit of my background, because I did work

in independent schools, and shout out to joy Lopez at Sacred

Heart schools in Atherton, who is one of your members, because

she taught me a lot of what I know about putting technology

and pedagogy together to Ensure that the technology is

supporting learners and focusing on their needs and the needs of

teachers. So we identified five key topic areas within that

group about priorities that district leaders needed to

include in their guidance to their teachers, so that they.

Could support not only the students, but also we hear a lot

of parents coming directly to the schools and to the teachers

for guidance. So the whole community really needed more

support. So we have those topics which are safety and

prioritizing student, teacher and community data, security and

safety, the ethics side of it, transparency about the process

from school leaders and acknowledging that this

technology is changing rapidly, and there might need to be edits

to these policies, and that we're all learning together, and

then a key focus on professional learning and guidance for

implementation, and not just at the various grade levels, but

also in different subject areas, as Jeremy was speaking earlier,

there are specific things that are needed in an English

language arts classroom, and there are different needs in

math classroom computer science classrooms, so being responsive

to those needs, and then regularly evaluating these AI

systems and tools to better understand whether they're

benefiting learners causing harm, and what can be done to

make modifications and ensure that they are working for the

learners. One of the big pieces that came out of that work is

the need to focus on professional learning, and

specifically AI literacy for both teachers and learners. And

so that's a big part of the work that I've done at Digital

promise. And as Jeremy said, we've been working in this space

for a very long time, and we've always taken a human first

approach and an approach that puts people first. So we think a

lot about envisioning safe, equitable and meaningful AI

enabled learning environments through the development of AI

literacy, which for us, means developing the knowledge and

skills that enable humans to critically understand, use and

evaluate AI systems and tools to safely and ethically participate

in our increasingly digital world, and we have a whole

framework that I can point you to and Put in the show notes.

Do you think that schools are landing with

that framework? In other words, is it resonating with them? Is

it fill in the need at the moment? Because obviously, I

can't speak for public schools and districts, but for the

Independent School world, we are all over the map in terms of

adoption comfort level, whether we're using it in the classroom

at all or just using it on the productivity efficiency side.

And so I'm just curious, do you think that as this all unfolds,

so too will the framework I would imagine there might be an

evolution there?

Yeah, just like you heard me say earlier, we know

that these things need to be co designed with the communities

and specifically the end users of these so one of the things

that Jeremy and I have been exploring is partnering with

districts and school systems, larger school systems, in order

to develop a version of this framework that works within

their context and works within their needs, so that the AI

literacy practices that they identify are the ones that go

along with the portrait of a graduate that we mentioned

earlier as well, because we know that that's where the school or

district is focused, and We think that these things need to

be complementary. And of course, while centering the core values

of this framework, which to us are human judgment and centering

justice in the use of AI systems and tools, but absolutely, we

encourage folks to take our framework and adapt it to meet

their needs.

I would think of the framework sort of as a

way to think carefully about the problem, but not prescriptive.

Terribly. You might come in and your first thing is, I want to

understand AI, and that's what literacy means to me. And

looking at the framework might remind you how important the

evaluate side is, and there's no way we're going to get to safe

AI in schools without really experienced adults all

throughout the school steps and parents who know enough about

how to evaluate these tools. And so we need the evaluation side.

And so it's just a way to make sure you're thinking carefully

as you design your own approach,

so as people who spend a lot of time thinking

about this, can I ask you each to tell me what concerns you

about AI in education and also what excites you?

What excites me is seeing what students come up

with when they begin. Experimenting with the use of

tools. For example, a high school student used AI to design

a uniform for their sports program, and I think that that's

a great example of using AI to develop something that then gets

made. So this uniform ended up getting made because the team

and the student just developed it because they were interested

in designing a uniform that they would want to wear, and their

teammates agreed, and they ended up making this uniform. And so

how learners are partnering with this technology to go beyond

their current abilities, to be able to extend their capacity to

be creative and to leverage it as a tool to support their

goals, right while they maintain that intrinsic motivation right

to create something new. So that's always exciting to me to

see how students end up using these tools. And there are a lot

of cautions that I have for the use of AI, and specifically

generative AI, primarily the evaluate portion of our AI

literacy framework, which includes thinking critically

about the information and the synthetic outputs that are being

produced, especially by generative AI, and thinking

critically about the ethics and the impact of those outputs, but

also of the use of the tool itself. So helping learners and

teachers understand when they should be using these tools and

when they should not be using these tools, or identifying

between use and being okay not using these tools, I think, is a

critical piece of what we need to help develop in both learners

and teachers,

absolutely. And I think that thinking

critically is so important. I mean, one of my worries in this

space is, you know, we go to a lot of conferences, but CNI and

digital promise, and you see the kind of gold rush of companies

rushing to put out products too quickly to get into the market.

Some of them are pretty half baked. And you know, you wonder

how much good they're really going to do. They look cool, but

are they really going to do any good? And they're going to take

time away from other important educational things I worry about

moving too fast and educators not taking it slow enough to get

it right. And on the positive side, the thing is, I've studied

Technology and Learning Sciences my whole professional life, and

we've always had to figure out how to make the technology do

something useful for education, but it was really limited,

especially in terms of conversation, story, discussing

things in the kind of conceptual terms that people talk about

things and AI is really different in opening up new ways

to bring the interaction we can design closer to the research on

the learning and what the learning process should be. You

know, my ideal learning process is one of you guys in a

classroom having a great conversation with a student, but

we can't do that for every student all day long. So if we

could use technology to have some of those great

conversations, that's exciting to me,

Jeremy, in terms of the support that this tool is

going to have with readers, in terms of, like, a wish list that

I could potentially have as a researcher. There are different

types of reading. Yeah, there's reading in the humanities,

there's reading for science, there's reading in mathematics.

Has your organization even gone the adjacent route yet to these

other disciplines?

No, but I've thought about it, and it's so

exciting to me, because reading happens across the curriculum.

And it's not true that one's reading challenges are confined

to ELA instruction. And so why shouldn't there be better tools

available when you're a science teacher? I've studied science

education too, and there's a lot of reading difficulties there

because the vocabulary is so tough, and so why don't we have

reading across the curriculum supports, and I think teachers

would welcome those that those would not be interfering with

their role as a science teacher or math teacher. Math, tons of

reading problems come up and prevent kids doing the math

because they can't read the word problem or struggle with

particular words in it. So I think reading across the

curriculum is huge. Likewise, you could do math across the

curriculum and say math shouldn't only be taught in math

class. You're going to come across it in science, in

history.

Oh, you're speaking my language, right? But

ed

tech products of the past are very curricular

silos, and. This is a more general purpose capability.

Could we use it to do interdisciplinary learning?

As a former science teacher, I've often

found that the students that struggled most with science

often had a language arts deficiency of some sort, and

they were really challenged by what I call the vernacular of

science. Yeah, you just didn't know the information in terms of

communicating as a science student. And likewise, you

wouldn't have the same capacity in, say, Spanish or French or

Latin, which would also prove to be difficult as well.

You probably experienced this too, and you're

probably, like, one of the top 1% teachers, so you probably

have a great way to handle it, but you'll have science teachers

in a situation, say you're graphing something, and, you

know, students learn something about the equation for that

graph and math class, but you're not the math teacher, so you

don't know exactly how it was taught in math. And wouldn't it

be a great thing to be able to say, hey, you know, I know you

learned about this. Let's make those connections. I'm going to

give a few instructions to your AI assistant, and I want you to

go study those connections between the math you've been

learning in the science I'm talking about here. And like

that kind of connection making is really hard for the average

classroom teacher,

and it's so fundamental, I think, to the

student understanding well beyond just comprehension, and

it's an opportunity for you to actually develop an effective

response to the content so that they actually enjoy it.

Absolutely. Yeah, we're all about

stimulating student curiosity about the content they're

learning. That's meaning and understanding. And, you know,

finding ways that AI can give them agency as a learner, to

connect their worlds to what they're learning. Make it

meaningful, make it important. Those are the things we have to

work on. How do we realize those visions?

So our tech leaders often are in a position

to support encourage their faculty down this path. How do

you think tech leaders, you know coming into our core audience of

CIOs and tech directors? How can they best support teachers right

now? Part of the context of the question from me is that

listeners of our pod know that I have a daughter who's a senior

in college, she's coming through her education program, and she's

student teaching. She wants to be a teacher, and they're not

teaching her about AI. Weirdly, program is not really spending a

lot of time talking about Ed Tech at all, let alone this

massive tsunami of AI tools that are coming at educators. So what

that means, I would think, is that the tech leaders in our

schools that are local, they're not at the district level, so

they're local, trying to help educators unlock the potential

while being concerned about the things you're concerned about.

You know, what can our tech leaders do? Where can they stay

informed about some of these frameworks, but also just learn

enough to be able to be great coaches and supporters of the

faculty who are swamped and busy and all those things, right?

Well, stay

tuned. We have an AI literacy in education, PK 12

brief that we'll be publishing next month, so I will be sure to

share that with all of you. But as part of that brief, we did

identify some of these gaps that you're discussing, and the

recommendations that we give to educators and educational

leaders are to ensure that there's funding for professional

learning. We need to be able to give teachers and people

developing into teachers the time and the resources that they

need to be able to develop this. This is an ongoing issue with

professional learning, as we know, but it's also important to

co create and contextualize the AI literacy policies and these

frameworks like we discussed with these teachers, so that

they are able to identify what's important to them and why and be

better able to integrate these skills, practices and core

values into their own teaching. It's also important to establish

educator support systems and help connect educators to one

another so that they are experiencing more targeted

professional learning opportunities, right? Depending

on their grade level subject area. And this can be an ATLIS

community. I'm sure you have one that you can share in the show

notes. But also, one final recommendation is we have

identified a lack of high quality and evidence based

professional learning and curricular resources when it

comes to integrating AI, because, as Jeremy said, there's

a lot that's not fully developed that's out there, and so helping

educators use. Use evidence based curricula, instructional

materials, tools and helping to provide guidance on what tools

they should and should not be experimenting with, I think is

always a great place to start.

One of the things I'm curious about is the idea of

targeted professional learning on the website, you've got

things listed on there for micro credentialing in terms of, what

are some of the things that you offer, what are those micro

credentials that you do offer, and how do those, or do those

fit into any of the pieces that we're talking about at this

time,

the micro credentials, the way that works

is, we're a host for micro credentials, and lots of

different places can develop and post and deliver their micro

credentials through our open source platform. Then within the

platform, we may have specific things. The set of offerings is

changing a lot. So I'm not up to date at this very minute with

exactly what the AI ones are, but I think if educators went

there, they're going to find tons of relevant micro

credential content. And the flip side of micro credentials is

digital promise also does product certifications, and

there are some AI specific product certifications. This is

where companies apply, and they provide a package of materials

saying how we're honoring a principle, like safe AI, and

then we either approve them or go and approve them as actually

honoring that principle. And so that's a good way to you know,

when you're evaluating products, do they have any certifications

from us or somebody else that would give you some confidence

that somebody's done some really deep due diligence on that

product.

Yeah, and that's a really good point. Jeremy, our

partners, ISTE, also have the ed tech product evaluation guide

that can help educators identify well built digital products. And

then there's also a platform that they host that identifies

various ed tech products, and connects those to product

certifications like the ones that Jeremy just mentioned, so

that teachers or leaders are able to find technology

solutions that are meeting specific product certifications,

and that's the Ed Tech index, which I can also share.

Yeah, ATLIS has also partnered with ISTE on

that, because we have been aiming to get more independent

school specific products and solutions on the index. So

certainly, you know, ed tech tools are fairly agnostic in

terms of the type of school, but there are some independent

school specific sis, LMSs and things like that. And we've been

working as partners with ISTE to try to make sure that, you know,

we get the representation of independent school solutions as

well. So we're big fans of that, and we can definitely share that

information in the notes.

There's two things I would emphasize to

folks who are in the position of guiding adoption or procurement

of AI in schools. Number one is what we all saw during the

personalized learning era, past decade, was schools and

districts take an attitude of, we'll let 1000 flowers bloom,

see what works out there, and then we'll spread the good

stuff. And the problem was the good stuff never got spread, but

all the bad stuff stuck around. And so we are really encouraging

people to be more choosy this round and be more intentional

about what products you're adopting for what reason. In

part, because this is a somewhat riskier technology, so don't let

1000 flowers bloom. Do the hard work to be selective, and the

other thing is to really think not about a one time buy, but

who's your responsible AI partner, who's going to be with

you on this journey? There are companies that I have a lot of

faith in that what could be your responsible AI partner, and

there's others that I just think want to make a sale in this

field, it's going to be so important to only work with

companies that are going to be your partner on this journey.

That's really great advice. So I'm

curious, as I play facilitator with our tech directors here on

the pod, my co hosts and our researchers here from digital

promise, I have kind of an interesting scenario that I'd

like to put in front of you guys. So Bill and Hiram, let's

say that Patty and Jeremy finish up their research that they're

doing and they're ready to tackle a new grant, a new

project. What research would you want them to do? You deal with a

lot of your faculty. You guys are wrestling these issues day

to day, probably even today, you've been wrestling these

issues, what do you wish you had more research on at a high

level, the one

area where I would go, and I'm not sure exactly

what the research question would be, but I think research at the

early learning levels, like when you look at AI, when you look at

this type of work, because I think that there is question.

About how it is applied, what is appropriate. I taught third

grade, and I would always say, if a pen and paper, pencil and

paper is better, use that, you know you don't need to use those

tools so understanding how, when and why to use AI at those

levels. Because, again, I mentioned at the start of this,

I came from a meeting with our Head of School, and it was

really trying to talk through, how do we articulate that vision

statement? How do we articulate the learning goals that we have

outlined for AI in the educational sense I mentioned

kind of the operational pieces earlier, but from an educational

sense, and I think you can talk about some of those things with

your middle school and your upper school, your high school

age students, but I think it's those early learners where I

would really want to see what, how and why we could use it

there.

Love it. Bill, we're on it. My co director of

our group, our learning science research group, is heina

Dominguez. She's an expert, and her team is in exactly this

whole early learning area. I think the basic guidance I would

give anyone in this space is people and human relationships.

Caring relationships are so fundamental to young kids. When

we look at the technology, what the research says we often land

on, if you choose a good half hour a week to use technology,

you can see some pretty good gains. So don't go nuts. Find

your best half hour to play with technology, but really double

down on that human dimension of being a great teacher to those

young children.

Jeremy, I think what you'd probably hear from

the Independent School community is that we are in the business

of relationships. Yeah, we've got that pretty much nailed

down. My research topic would build off of what Bill just

mentioned with the early learners, given that it is so

important to build that foundation very early on, is to

look at the impact of AI in terms of using manipulatives in

science and math education, and how that can be augmented to

improve overall literacy with the students in perhaps what I

would call the initial Laboratory Sciences.

Yeah, we resonate with that one too. It

relates to work we're doing, absolutely. That's a very

appropriate research topic. A lot is known. I guess my overall

thing about research, since you guys have real research

questions, would be to encourage everyone in the audience to

think about knowledge as really a limiting factor. Right now,

this AI disruption is grabbing us all, making us rethink

things, and it's making us realize what we don't know

research is not just about numbers and finding out how to

count this or measure, that it's about producing useful

knowledge. And so find some friendly researchers who want to

produce knowledge with you and get in the game, because we just

all need to be active growing knowledge in order to use this

technology.

Well, I love it. That's really cool. Thank

you for that. Thought. That's a wonderful thing to round out

this conversation before we let you go. I'm just curious what

kind of AI tools are open on your desktop right now? What do

you guys like? What are you using

open on my desktop now I can say none.

We're actually a little cautious. I'll tell

you. One thing I've been playing with is note takers when they

are going to keep my information safe. But I go to a lot of

meetings, a lot of different people, and some of these note

takers can produce beautiful summaries of the meeting that

are very helpful to me, because I am intrinsically a very poor

note taker, so I'm interested in that. And sometimes I find some

of the research capabilities of AI helpful. I always find it's

nowhere near a real researcher in that area. But if I want to

come up to speed really quickly on the basics of a topic that's

on my periphery, it can be quite helpful to ask for a summary of

recent findings and knowledge in that space I get used to stuff.

Those are my two favorite

researchers of tomorrow are never going to

understand the old Dewey Decimal or even Lexus Nexus, right?

Poor John Dewey,

well, I'd like to thank you both for

taking the time and spending it with us, because these are big

picture things that sometimes our tech leaders get into the

day to day, and they don't take a pause and think about these

things. We love to see this research that you're doing. I

can't wait to follow along with your project, and we welcome you

to come back and talk to us anytime about these types of

topics, because we'd love to stay tapped into what you guys

are thinking about.

Thank you for having us. Yeah. Bill Hiram

Christina, it's been a real pleasure.

This has been talking technology with ATLIS, produced

by the Association of technology leaders in independent schools.

For more information about ATLIS and ATLIS membership, please

visit the atlas.org if you enjoyed this. Discussion, please

subscribe, leave a review and share this podcast with your

colleagues in the independent school community. Thank you for

listening. You.