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Technology in education shouldn’t feel overwhelming, confusing, or disconnected from what actually works in classrooms. This show keeps it real. Each week, educator and K–12 EdTech Advisor Lindy Hockenbary shares practical strategies, stories from real teachers, and no-nonsense conversations about how to use tech in ways that feel human, joyful, and grounded in learning.
Whether you’re a teacher, a school leader, or an EdTech product builder, this show helps you Make EdTech 100 — real, relevant, and rooted in what matters most: kids.
Speaker: Welcome to make EdTech 100.
I am LindyHoc Educator, K 12
Ed Tech Advisor, and your host.
This is a podcast where we keep it real
about what actually works in classrooms.
No hype, no overwhelm, just practical
strategies, honest stories and
tools that make a real difference
for teachers and students.
So come along with me on a
journey to make EdTech 100.
Speaker 2: Today's episode is
a part two, a Companion two.
Episode nine is AI Safe for Students.
So if you haven't heard that
one, go back and listen first.
If you don't, it's not
the end of the world.
You'll still get a lot
out of this episode.
But there's some important context that I
laid there in that first part one episode.
Today is AI Safe for Students.
Part two is our subject matter.
After that first episode dropped,
some research also dropped.
So I wanna continue this discussion
of is AI safe for students and
discuss that research summary.
Also, I know I have some parent listeners,
part one focus fully on the teacher
perspective, and I gave my three things
that I look for in an AI tool to use
in learning or classroom environments,
guardrails, teacher dashboards for
visibility, and using it at key
instructional moments for normally very
short, five to 10 minute periods of time.
Just as a summary there.
Since I have some parent listeners, I
wanted to kind of add onto that, and
I created some dos and some don'ts
when it comes to using AI tools
with both students in a classroom
environment as a teacher or instructor
or educator, but also kids if you're
parent, trying to help your kids with
their schoolwork at home, for example.
Let's get into it.
Stanford has an AI hub for education
that has over 800 research studies
on all things AI and education,
and just a couple, two, three
weeks ago, they released a summary.
This research repository, and they
called it understanding the evidence
base on AI and K 12 education.
It has some important takeaways around
the topic of is AI safe for students?
First of all, the majority of the
studies that were indicated as
being high quality causal studies,
which were not very many by the way.
I'll talk about that more in
a bit, focused on students as
the users of ai, not teachers.
That's really interesting.
Moral of the story is that the number of
studies deemed to be high quality causal
were low, and of those that were deemed
to be high quality causal, the majority
of them were about students using ai.
As a tool rather than teacher use.
One important takeaway from this
research summary was, I quote, the
research base is growing quickly,
but rigorous evidence is still thin.
A k, a, we have some research,
but a lot more is needed.
That doesn't mean that we shouldn't take.
What the research is saying and look
at it and use it to guide what we're
doing, especially when it comes
to emerging technologies where of
course it's a brand new technology.
The research is going to be a constantly
increasing and changing field.
Of the high causal studies, one major
takeaway from that research summary from
Stanford was that learning improvements
were noted when it comes to using AI
as a learning tool, essentially with
student and learners, but with one
really big, but is the caveat there.
So learning improvements were
noted, but tool design matters.
Here's some quotes from that study.
Or I should say, research summary
across the causal studies.
Reviewed evidence suggests that AI tools
designed with pedagogical guardrails,
such as tutoring systems that give
hints or guide reasoning, show more
promising outcomes than general purpose
chatbots that provide answers directly.
Here are some other quotes
from the studies directly, so
that one was from the summary.
These are from the studies
that were deemed as high
causal as part of that summary.
Not all AI tools function the
same way in learning environments.
Tools that support reasoning
may help support learning.
While tools that simply generate answers
may reduce the cognitive effort that
supports durable skill development.
In other words, using AI with
students is not black or white.
It depends entirely on the
tool that you're using.
Tools that guide and not give
the answer are those that are
linked to learning improvements.
The research cites this
as a Socratic style tool
a Socratic style tool guides not give.
So for example, if you were to give
a Socratic style AI tool, a math
problem, it would say something like,
let's work the through this together.
Let's break down the steps.
Let's take it one by one, rather than
just giving the answer outright, which is
what you're gonna get if you're gonna go
into say, like a chat GBT esque type tool.
The research summary also says that
learning science provides one way
to interpret these findings, and it
discusses various different educational
theories on how an AI tool design would
provide opportunity and also risk.
If you dig down deep teachers that
are listening, if you dig down deep
to your teacher prep program, you
likely remember your educational
theory or educational psychology class.
Every person that has a teaching
degree has to take this class.
And you learned about all the
different theories out there.
You may remember, Vygotsky
Vygotsky talks about the zone of
proximal development or the ZPD.
This is the idea that you have to
meet students within their zone
of proximal development or their
ZPD if you are outside their ZPD.
The learner's not prepared essentially for
the information that you're giving them.
This is a great way to think
about using a guard, railed large
language model with students.
They are not ready for the, give me
the answer that these tools do us,
that are adults with fully developed
brains can also struggle with this.
This can be we're overseeing that.
This can be challenging for adults
with fully developed brains as well.
So it makes sense that it
would be challenging for.
Kids that do not have
fully developed brain.
Why don't I say that one more time?
You get the point.
You get the point.
So if you remember from the Part
one episode I gave you those three
requirements when it comes to
using AI as a learning tool, the
guardrails, the teacher dashboard,
and the key instruction moments.
So I told you that the first
requirement for the guardrails, the
guardrails have different functions.
One is to make sure that there's
no inappropriate or developmentally
inappropriate outputs by the ai.
But another purpose of these guardrails
is to set up the large language model
that's running them in the background
to be in that Socratic style, to
guide, not give the answer essentially.
That is kind of just a little bit
of a look at that Stanford research
summary, which I think gives us a lot to
think about and really matches what my
experience has been and kind of what I
shared in that last episode all about.
It's all about the tool.
It's not black or white.
It's not give or don't give.
It's give, but with a giant,
but, and the tools are.
Very, very important, but
also how you use them.
So the tools, having the guardrails, the
teacher dashboard, but also kind of how
you use them in an instructional setting
is what I shared in that last episode.
Based on this idea that tool
design matters, I created some
dos and don'ts when using AI for
both teachers and or parents.
And I know many of you are teachers
and parents, so here we go.
I don't like to start with a
don't, but it just really made
sense to start with a don't here.
This one's for teachers and parents.
I do not want you to drop your
students into an AI model, AI tool
without any foundational AI literacy
lessons and or conversations.
Lessons can really just be conversations,
and in this case, when it comes to
AI literacy, they really should.
Be a lot of conversations around it.
So before the tool, the AI model, the
AI tool ever goes in students' hands.
They need to know that this is an ai, this
is not a person, it is not your friend.
I'm gonna talk a little bit
more about that in a minute.
That's an important one for
all ages of kids and adults.
Pause, I'll come back to that.
, They need to know, here's what it can do.
Here's what it can't do.
Here's how it can help you.
Here's how it can't help you.
Here's why you should
question it and push back.
I've been teaching and talking
about that a lot lately.
We need to learn to push back on ai.
It's not magical.
It's not always right far from it.
We know it hallucinates, right?
So knowing when to push back
on it and in appropriate ways
is a really important part.
Of that conversation.
Now, you might be thinking, I
don't feel that I am equipped or
ready, or, I'm not a tech expert.
I'm not an AI expert, so I
can't have these conversations.
But that is not the case at all.
So much of AI literacy is having
the conversations and just
talking about all those things.
I just gave you what it can do, what it
can't do, what it is, what it is not.
You just need to model
the right questions.
Sometimes it's presenting and taking
advantage of like a teachable moment
to have the conversations too.
So if you have.
Surrey on your phone if you have
a, I can't say it, A-L-E-A-L-E-X-A
or Google in your house.
Hey Google machine in
your house, AI device.
Use those as a way to kind
of spark these conversations.
Hey, you know, I see
you're talking to Surrey.
Did you have, you thought about
what Surrey really is, right?
You understand, right that Sury is just an
ai, not your friend, not a human, right?
Like just an example there.
I was working with a teacher with
elementary age students and we were
using a guard railed AI tool and we
had had all these conversations with
kids, with the kids in the classroom.
Mostly the teacher.
I was just kind of
there supporting and uh.
They started using the ai and
of course one student in the
room said, it's my friend.
And then you know how something like that
spreads like wildfire in a classroom.
Then all of a sudden,
oh, that's my friend.
So we were able to use that as a
teachable moment and we paused the tool.
'cause that's another thing
that these guardrail tools
allow you to do is hit pause,
and brought everybody together and we
created a kind of t chart of what our
characteristics of a friend and what
are not characteristics of a friend.
Okay?
And we let the kids build the
list and by the end they were
going, oh, you are right.
I don't, I don't think
this AI is my friend.
That was an example of a
perfect, teachable moment
of instead of that teacher.
Just saying, Hey, nope,
AI is not your friend.
That that was the natural
inclination, that anthropomorphism.
So stopping, having that teachable
moment and letting students think
through it and come to that healthy,
responsible, ethical conclusion.
Their self, moral of the story,
curiosity, healthy skepticism,
conversations, discussions, those
are the foundation of AI literacy.
Not being an AI expert,
not being a tech expert.
You already have the skillset you
need to know to question it and just
start having those conversations.
Okay.
I said I would come back to
this idea of companionship.
This is becoming companionship with AI,
in particular from humans to ai and humans
developing really unhealthy relationships
with AI and thinking that they are a
friend, sometimes more than a friend.
We're seeing this in all
ages, kids to adults.
You've likely seen something
about this in the media.
It is a major concern,
but here's the problem.
The knee jerk reaction is to
say, as a parent especially,
and a teacher, is to say, oh.
Nope, we are not touching that.
We're not touching that technology.
Nope, nope, nope, nope, nope.
We're just not even gonna let it in
our lives, and that's gonna shut down
the option of that happening or the
chance of that happening, I should say.
That's not how I want you as a teacher
and or a parent to react to this.
. I know that seems crazy.
You're like, Lindy, you just told us this
is a major concern and it's a problem.
Why wouldn't we just block it no more?
The problem is artificial intelligence
is embedded in everything in our
lives already, and it's not just
technology, so not allowing the.
A-L-E-X-A devices in your house or not
allowing students into a large language
model on a device, a laptop, a phone,
doesn't mean that they're not going to
be interacting with this technology.
I always use the example I of walking
down the street, you're likely having
your face scanned by a video camera.
And that video has AI built into it.
That , has facial detection, that's ai
and that is just walking down the street.
So this is no longer like, oh,
we can just limit a device.
We can limit screen time and we can
keep our kids safe from this technology.
And this is just the beginning of it.
So instead, you need to take
the approach of setting up.
Responsible, healthy interactions
with specialized tools.
And I'm gonna talk more
about that here in a second.
And having the conversations, and
honestly, even if you don't wanna touch
the technology, okay, that's okay, but
you still have to have the conversation.
You can't act like it doesn't exist
because your kid, at some point in their
life is going to come across an ai and
you want them to understand that that
AI is not human and you don't want to
develop companionship with that ai.
Okay.
Enough babbling about that.
But hopefully that babbling
led to you understanding that
companionship is 100% a major concern.
Another reason for guardrails is
to help with that, by the way.
I'm not sure I said that clearly.
And the kneejerk reaction is just
to not let your kids touch it.
But that's actually the better
way to go about it, is to teach
them responsible healthy use.
Whether that is just through
having conversations or ideally a
combination of having conversations,
interacting with some very
specialized tools and technologies.
And the great thing about that
is it sparks the conversations,
just like that example I gave you.
Alright, so that is a don't,
don't put your students kids
into AI models, AI tools without
first having some conversations.
Those AI literacy conversations
are so important and I should say.
If you are getting them into these
tools, don't just let it in there.
Use them to spark those conversations.
Okay, now let's go to a do.
This one is for teachers.
I want you to use tools that
have guardrails and teacher
dashboards to give you full
visibility into students' progress.
These tools use the same underlying AI
models like the GPT models from chat, GPT,
the Claude models, the Gemini models, but
they have this educational scaffolding
kind of layered on top of them.
I gave you six of these tools in the
last episode and talked much more
in depth about the guardrails and
the dashboard and the instructional
moments and when and all of that.
There are a few caveats
here with older kids.
There might be specific use cases,
likely will be specific use cases,
I should say, where you could use a
Gemini gym if you have access to Gemini.
And if you aren't familiar with a gym,
it's really similar, pretty much the same
as a custom GPT if you're a chat GPT user.
And what gyms and custom GPTs do is
they allow you to basically in the
background prompt the AI to have
a specific goal or have specific
knowledge base that it's pulling from.
So you can add files to a gym and a custom
GPT so that it's pulling from those files.
So imagine like a chapter from
a textbook or something like
that, that students are learning.
That's something that you can
load in the backend and it's
going to use that information.
To give its outputs essentially,
so gyms, I would be hesitant to
use custom GPTs with students.
Maybe if you have GPT for education,
you would wanna make sure all the data
privacy and check for check is all good.
But if you're a Google workspace
for education school, Gemini
is part of your core service.
It is under the umbrella of your , data
privacy agreement with Google, et cetera.
So it's much cleaner in terms
of compliance, if you may.
That would be the way that I would go a
hundred times over, over a custom GPT.
But even if you're using a gym,
you've got all that compliance
checked, they're still not gonna give
you that visibility that you need.
You're not gonna get summary of insights
and where to take the instruction next.
So again, this is only gonna
be used with older students and
really sparingly and only in really
specific instructional use cases.
Now parents, let's talk about you.
There are some freemium guardrail
tools that you can use with your kids.
I would start with either school AI
spaces or Brisk Boost, and that will
allow you to do, and you'll just have one.
Kid, maybe two, three, how
many kids you have in there?
Likely one or two in that space or that
brisk boost session interacting with it.
So that's a really great option,
but since you are working at more of
a one-to-one or a few to one ratio
compared to teachers that have more
of like a 30 to one ratio, you have a
couple of other options that are a lot
more challenging to do in classroom
environments that you can do with
only one or two or three kids at home.
Gyms and custom gpt, I
already mentioned those.
That's gonna be a great
strategy for you to set up.
Let's say your kid is trying to
work through their science homework.
You could set up a gym or a
custom GPT saying this is their
age, this is what they do.
You can even load specific
information in it, like I said,
and it's gonna pull from that.
And you're kind of like prompting the
AI to guide that learning experience.
Claude and I think chat GBT too.
Yeah.
Both have what are called projects
and what they allow you to do is
give instructions and or files, and
then you can have multiple chats
within that project that have the
context of the instructions and
the files that it's pulling from.
Perplexity has something called
spaces that functions very similarly.
It's basically the same thing as
projects in Claude and Chat GPT.
The other thing you can do, which is
similar but not as repeatable as a gym or
a custom GPT or a project or a space, is
you can set up a general purpose chat bot.
So chat, GPT, Jim and I clawed, likely
perplexity, maybe especially if you're
doing more research stuff, you can set
one of those up to guide, not give.
By priming the chat with information.
So for example, I would open up a new
chat in one of those tools, large language
model tools, and give it a prompt.
Something like this, you
are helping a 14-year-old
complete school learning tasks.
I want you to guide and
not give the answers.
You can break down the steps
for completion, help brainstorm
ideas, give steps to help
complete the problem, et cetera.
Ensure outputs are developmentally
appropriate to age 14.
Okay?
So now one thing to understand here is
when you go into a chat in any of these
large language model tools, chat, GBT,
Claude Gemini, are the three biggest ones.
Every time you hit enter on a new
prompt, it rereads the entire chat.
To a point.
It does.
There does come a point where you hit
what's called a context window limitation,
where it can only go back so far.
But if you haven't overloaded the chat
with a lot of stuff, basically it's
gonna reread that chat every time.
So every time your kid is in there
asking it things, Hey, help me with this.
Help me with this problem.
I'm working through this.
It's gonna reread this prompt that I
just gave you, and it's gonna know.
I gotta make sure that I'm giving outputs
that are appropriate to a 14-year-old.
I've gotta make sure that I guide,
not give, . This is essentially what
a custom GBT and a gym and a project.
Are doing, but just within one chat.
And if the idea of creating a
gym or a custom GPT or a project,
you're like, oh, I'm not there yet.
If you're newer to these tools,
this is a really great way to start.
Just open up a chat, give
it a prompt like this.
But this is similar to kind of what the
prompt could be on the back end of a
custom GPT or a gym, if that makes sense.
Lemme give you one other example,
and I wanna do this one for a writing
task, since that is the biggest
pain point when it comes to the copy
paste idea of large language models.
So here's another one.
You are a homework helper
for a fifth grader.
Do not give answers directly.
Instead, ask questions that help them
think through their own response.
If they ask you to write something
for them, redirect them to try
a first draft themselves first.
The assignment is a blah,
blah, blah, blah, blah.
A book report on this title, a essay on
this topic, . There's another example of
what you could do within a chat or within
like a custom GPT or a gym or a project.
Now the AI has the context.
I would test this in different tools.
I constantly go between those four.
Chat should be Gemini, Claude
Perplexity, well, chate, Gemini, Claude.
I constantly go between the three
of them and almost always have
all three open in my windows.
Sometimes multiple different tabs open
with multiple different versions of those.
Perplexity.
I use it very specific times, usually
related to research type stuff.
I'll talk a little bit
more about that in a bit.
So test it in the different ones, the
different AI tools, general purpose,
large language models, essentially, and
see if one does better than another.
And try to act like your kid and see
what happens and see if you kind of
gravitate towards one or another.
Also, test different models in
these different general purpose,
large language models, tools.
So this is something that a lot of
people don't understand, especially
if you're only using the free versions
of these tools, especially chatt PT,
the free version of Chatt PT, at least
the last time I was in there, I don't
think this has changed, only gives
you its default model, so you don't
even have the option to switch models.
I am pretty sure the free version of
Claude lets you change between the
three different models that they have.
I'm fairly certain, okay, so if
you're on the free version of trash,
GBT and you're not willing to pay,
by the way, I don't wanna go there,
but you're gonna get so much out
of these tools if you pay for them.
Maybe I'll do a whole episode on that.
So go into Claude if you're on the
free version of chat, TBT, and in
the chat window on the bottom right,
you see a little dropdown, it'll
always default to the Sonet model.
If you click that, it also
gives you two other models.
Sonet is their default.
That's kind of like the go-to
for anything and everything.
Um, I always call it kind of
like my, my go-to default.
If I'm not doing anything like
particularly specific in my prompt.
Haiku is a faster model.
I never use it.
Opus is their reasoning
model and reasoning models.
Essentially, they use what are
called chain of thought prompting
in the background to work through
their outputs in more detail.
It takes longer to get a response
out of a reasoning model like Opus.
Then it does a default model like sonnet.
But you usually get much more
detailed responses and it lowers
the chance of hallucinations
because it's using that chain of
prompting to kind of check itself.
I'm gonna make sure I'm giving
you the right information here.
So, Claude, yes, you
have sonnets are default.
It says for most efficient,
for everyday tasks.
It actually tells you that.
When you click the dropdown, then you have
Haiku says, fastest for quick answers me.
And then Opus is most
capable for ambitious work.
So it doesn't state that it's
a reasoning model, but from my
understanding, it is a reasoning model.
Okay.
Then Jim and I has their, they call
their models and it's in the same spot as
Claude in the chat window where you put
your prompt in the bottom right corner.
If you click that, it'll
likely default to fast.
So it says fast answers, quickly
thinking, solves complex problems.
They also have a pro model, which
is really good with advanced math.
So if you have a high school math student,
or you're a high school math teacher,
definitely check that pro model out.
And it's also their coding model.
And then chat GPT at the moment.
They quit.
, Notice that Gemini quit numbering
and really naming their models.
Claude is still naming
them and numbering them.
Sonnet, Opus Haiku and they each,
I think we're at 4.6 right now, 4.6
for Opus and Sonnet, 4.5 for Haiku.
Gemini is just calling it Fast
Thinking Pro and then chat, CBT.
We have instant that's for
everyday chats and thinking.
That's for complex questions.
So that was a little bit of a tangent
sidebar there, but I think an important
one to understand what I mean by go
test different models and different
tools to see which one is going to
be the best for whatever task you're
trying to help your kid with at home.
If you're trying to help them with
advanced math, absolutely do not use the
default models in any of these tools.
It's not gonna likely be a whole
lot of help, and it's probably
gonna be full of hallucinations.
Likely you never know, but I feel like
the likelihood is pretty, pretty high.
So I kind of summarize that the
default models in any of those tools
are going to give really quick,
not super thorough answers, but
that's sometimes what you want.
The reasoning models often called
the thinking models are gonna take
longer to answer, but typically
have more thorough answers with
, less chance of hallucinations.
Just in general, the Claude
models tend to be more creative
and better helping with writing.
So anytime I am ideating and wanting
AI to help me think through an
idea or build on that idea or help
me brainstorm, I'm almost always
gonna go use one of the CLA models.
Depending upon exactly what type of
ideating I'm doing, I'd probably start
with the sonnet models, and then maybe
once I narrowed it down to one or two
ideas, I might then go into the Opus
model and dig a little bit deeper with it.
Anytime I want AI to help me finesse my
writing, maybe reword this a little bit.
I always go into the Claude models 100%
over chat, GBT, I would say Gemini's
kind of in the middle there and depends
a little bit on what type of writing.
Gemini's pretty good at more
of the technical writing.
Now if you're at a school that has
Google Workspace for education,
you're gonna have Gemini.
It's part of your core service.
That means it's compliant,
all that good stuff.
It has some amazing multimodal
opportunities that the other.
Large language model tools, chat,
pd, Claude Perplexity don't have.
So for example, you can click a button,
you can add the nano banana model, which
is Gemini's image Generation model is
really good at creating infographic type
visuals so you can turn something they're
trying to learn into an infographic.
Notebook, lm, I'm gonna talk a little
bit more about this in a bit, but
Notebook LM is amazing and has all
sorts of multimodal stuff in it.
So more of the story if you're at a Google
school, if your kid's at a Google school.
Jim and I has a ton of power and
integrates really well into like Google
Docs and the whole Google ecosystem.
Alright, so to wrap that up.
Remember, don't do any of that
without first having those
AI literacy conversations.
Now for a don't.
This one's for teachers and parents.
I don't want you to drop students
into one of those general purpose
chatbots with no structure.
Don't put your students and or kids
into a large language model with no
prompting or priming or those guardrails
set up without any of that set up.
The AI is going to default to answer mode
and answer mode is what makes it super
easy for them to outsource their thinking,
especially for young people.
Alright, now a do, this is
for teachers and parents.
I mentioned it.
Notebook, LM Notebook.
LM is a big do.
It is so, so, so good.
So if you're not familiar,
, it's made by Google.
So it's part of the Google
ecosystem and it's built around
Gemini, the Gemini models.
And essentially it allows you to
give it sources of information.
So the, that can be a website, it can be a
document, it could be a research study, it
could be a Google doc that you've created.
And then it pulls information.
And in the chat, when you're chatting
with the ai, it pulls its responses from
those sources and even cites those sources
of where it came up with the response.
This is called a RAG Model
Retrieval Augmented Generation.
There you go.
There's a mouthful for you.
This idea that you give the AI a
knowledge base, and it's using all
of its large language model knowledge
and training data, essentially,
but it's specifically pulling its
answers from that knowledge base.
Okay?
So that's what Notebook LM does.
So it's a really great way to teach
students how to research and check and
verify information from large language
models, but making sure the responses
are specifically coming from the
sources of information that you give it.
It also makes this
multimodal learning a breeze.
So if you're in regular Gemini,
you can use nano banana.
You can tell it to create an
infographic from the information.
You can do that in Notebook L limb as
well, and it's gonna take all of that
source documentation, that knowledge
base, and create an infographic.
And there's actually a button that
specifically says infographic.
You can also create an audio summary
that creates kind of a podcast
style explanation of the sources.
This is fantastic because I always
say kids always have earbuds in
their ears, so take advantage of it.
Right?
It'll create like two people talking
through whatever content it is.
It'll create a video of whatever
the source knowledge is or
whatever prompt you get it.
It creates flashcards
and so many other things.
It is so, so good for both
teachers and students.
Teachers of course.
You need to be at a Google school.
If you're going to use this with your
students, it could still be something
that you can use as a teacher tool
and maybe you use it to create an
infographic and then share it in
your learning management system.
But you don't wanna put your students
in notebook LM unless you are at a
Google school that has approved it.
All of the good stuff.
Alright, another do, gonna
do two dos back to back.
And for this one I want to talk
about research with one big caveat.
I have an entire session that I
do on basically the new research
skillset with AI and large language
models in particular, research is
changing a lot and there's a lot that.
Humans need to know how to do research
using these large language models.
I'm gonna pack the
essentials of that session.
I do.
That's easily 1, 2, 3 hours into just
a few minutes here, so I'll do my best
if you teach high school and maybe,
maybe, maybe, maybe, maybe middle school.
It really depends.
With middle schoolers on their AI literacy
level, there are really specific use
cases where teaching them how to research.
Using these AI tools and large language
models is really, really important and
also can be really appropriate, especially
for those high school aged students.
This is an example of when you might
want to put them into a general
purpose, large language model, not
necessarily a guard railed model with
the teacher dashboard, all of that stuff.
But I wouldn't just do this willy-nilly.
This would be after tons of
AI literacy conversations.
It would be after I've used those
guardrail tools with them, I would
start with notebook L and teach
them how to follow citations.
So kind of like scaffolding in, and then
before I put them into it, I would've
put these large language models up on the
big screen and walk through the process
and talked and showed them how you verify
information, how you follow cited sources,
which tools have cited, sources, which
tools don't have sided sources, et cetera.
That's my big caveat there.
I recommend either Perplexity or Gemini
right now for research after notebook
L. So Notebook L is number one, but
the problem with notebook L is you have
to have the right source information
loaded into it, so it takes potentially
a little bit of adult help to do that.
If you wanna teach kids how to research
and find appropriate source information
and how to verify that's correct,
then load into notebook themselves,
that's where this comes into play.
So Perplexity and Gemini as of today
are the two of those four big tools.
Parity, Gemini Chat, GBT, Claude.
That automatically default to provide
cited links that can be followed to verify
and evaluate sources, in other words.
So hopefully everyone has at least
gone into chat t and done one prompt.
If you haven't, please go do it right
now and you're gonna see that it's gonna
give you a response with the default.
And don't change any default models,
don't change any default settings.
But what it doesn't do, it gives you
the response, but it doesn't tell
you where that response came from.
It doesn't give you cited websites
that you can use to verify that
that information is correct
and it's not hallucinating.
That's what Perplexity and
Gemini do as of default.
And Gemini, this is a newer ish thing.
It hasn't always done this.
So if you haven't been in Gemini for a
while, it does do this by default now.
So when you put a prompt into Gemini,.
When you get that prompt back,
you're gonna see, and sometimes
it'll look like a little link.
Sometimes it'll look like a little number,
like a citation and a research paper.
When you click on that, it'll give
you a website that you can click
and open to say, Hey, look, this
is the website that is showing the
information that I'm also giving you.
Part of that is going and looking and
saying, okay, this is a credible website,
or This is not a credible website.
Also, both perplexity and Gemini.
At the end usually, or off to the
side, there'll be a sources button
and you can click that and it'll
show all of the sources that it
cited throughout the entire response
that it gave you, essentially.
So what I do is I put it up
on the big screen, I model it.
We have lots of discussions
and conversations.
Around.
I talk about the technology, all
of the things we compare outputs
across the different models.
I show them and I put up chat, GPT and
Claude, and I show them, at least as
of right now, that those tools do not
automatically provide sided information.
There is a web setting that you can turn
on in both of those tools that if you turn
it on, then sometimes, not always, always,
most of the time it'll give you setted
links, but you have to know to turn that
on and you have to know where to find it,
so we talk through all of that
and yeah, and then just show them,
Hey, look, see how perplexity and
Gemini give you these citations.
I give them, I kind of have four different
strategies that we talk through of how
to validate information, et cetera.
One of them is ask different models.
Go give the same prompt
to different models.
These are essentially AI literacy
lessons that students must know and they
must know prior to getting into an AI
model that does not have guardrails.
So Notebook LM is a great scaffold to
learning how to research responsibly
using large language models.
Start there.
Then we get into Gemini and perplexity.
Lots and lots and lots of scaffolding.
AKA.
We're not just throwing them in
there, even high school kids.
Alright, next.
This is a don't for both
teachers and parents.
I don't want you using a general
purpose, large language model
for research tasks without that
source verification built into it.
So if you're able to know how
to go into Chatt PT, and this is
specifically for research tasks.
Specifically, you're trying to
find information, verify that
information, compile that information.
That's very different than just
going and asking it, what should
I have for dinner tonight?
That's not the greatest example, but we'll
go with it, so specifically for research
tasks, you need that source verification.
Ideally, all large language models in
the future are going to have this kind of
like source verification built into it.
I hope we're not there yet.
There's gonna be times
where you're gonna use it.
There's gonna be times when you don't, but
research is when you do want to use it.
Now, a do for both teachers and parents
do teach your kids to prompt AI in
ways that actually help them learn.
These are five different strategies,
and I've got these in a blog post,
which I'll put in the show notes
that I teach to personalize a task.
So one, if you need something simplified,
something like explain this like a third
grader, explain this like a kindergartner.
I've even gotten down to explain
it like a preschooler before.
And it'll take really complex tasks and
try to explain them as simply as possible.
And then you can build back up from there.
But if you're not understanding
the complex tasks to start with,
it's really hard to do anything
from there until you understand it.
And then you can go back up.
You can have it
personalized reading level.
So change it to a 700 Lexile score,
change it to a 500 Lexile score.
You can use it to translate if
you're a multilingual learner or your
kids are multilingual learners, you
can have it translate to Spanish,
you can have it give outputs in.
Two languages.
So English and Spanish.
If your kid or student is not interested
at all in whatever it is that they're
learning, and maybe you're a parent
and it's 7:00 PM and you're trying to
get through this so everybody can go to
bed at night and there's no motivation
there, you can have the AI related to
something that they aren't interested in.
So how does whatever concept
you're learning relate to soccer
or Fortnite or cats or curling?
I've been doing that a lot lately.
I'm like, tell me how
this relates to curling.
Got into it at the Olympics, whatever
it is that your kid is interested into.
Or you, maybe this, this
applies to you as well.
Now this is one that I hadn't
been doing, but I am now doing
more and more for task initiation.
So have the AI take.
Whatever the learning task they're doing
or whatever the homework is for that
night and say, break this task into steps
to help me complete it step by step.
You can even then have it break it into
more steps, or maybe it breaks it too far.
You can say, oh, maybe not that far.
Bring it back.
Wherever your kid is at in terms of
their executive functioning skills,
have the AI help you break it
down step by step by step by step.
I'm digging into this more and more of
how AI can support executive functioning.
I hear from almost every educator I
talk to in every school that I'm in,
that one of their biggest challenges
with students is executive function or
the lack of executive function usually.
So when AI tools break tasks into steps,
guide students through the process,
they're building those executive
functioning skills, they're helping kids
build those skills, task initiation,
cognitive flexibility, metacognition.
These are skills that many
students, especially neurodiverse
learners, generally struggle
with, and a well designed.
Remember, tool Design Matters.
A well-designed AI tool can help kids
learn how to approach problems and
accomplish big tasks with lots of steps.
This is really hugely helpful for a
teacher that has 30 kids in a classroom.
You can't sit down with every
kid and walk them through each
step every second of every day.
And some need more steps broken
down than others, but this is also
a huge help for parents trying
to get homework done at night.
Maybe you have multiple kids.
You're trying to get all their
homework done at night, and you
can't sit one-on-one with each kid.
So executive functioning,
helping with task initiation.
Huge.
But notice, so I gave you those.
What were those five examples?
Simplification, changing the
reading level, translation, personal
connection and task initiation.
Every one of those prompts puts
the student in the driver's seat,
the learner in the driver's seat.
They're not asking for the answer
they're asking to be met where
they are in their zone of proximal
development, their ZPD, ? That is using
this technology in a powerful way.
That is AI literacy and action.
And it's a skill that they're gonna
take through the rest of their life,
far beyond the homework assignment
that they're doing at that moment.
On that note, please don't
assume that students know how
to prompt effectively most.
Absolutely do not.
In my experience, this goes back to
this idea of digital natives, which
I really wish we would get rid of.
I always say that yes, we may have
quote digital natives in terms of
they're not scared of the technology.
They pick it up, they start
pressing buttons versus adults,
typically older adults are quite
a bit more hesitant, right?
And they're not just button clickers.
Kids typically are button clickers
'cause they're used to it.
It's what they grew up with.
But that does not mean that they
know how to use these digital
tools and devices for learning and
ethical, responsible, productive use.
They know how to use it to play
Fortnite or Angry Birds or Candy Crush.
I don't know.
I don't play digital games.
I don't even know what's in right now.
I don't think Candy Crush and
Angry Birds are in anymore,
regardless, whatever it is.
Roblox there.
That was a much better example.
They know how to use this technology
to play Roblox in Fortnite.
That is very, very different
than leveraging technology as a
learning tool to help you organize,
to help you accomplish tasks.
Very different.
And the latter has to be taught,
has to be modeled specifically.
They pick up on the former pretty quickly
'cause they are quote, digital natives,
but they don't pick up on the ladder.
The same is now going for using AI tools.
They don't know how to
use them effectively.
The number of kits that I've sat and
watched just take the very first.
Response that comes from a large
language model and copy and paste it,
we all know they're doing it, but
because they don't know any other,
they've been taught to do it differently.
They also don't know the right tools to
use or how to prompt correctly to use
it in ways that support your learning
and your thinking and don't outsource
your learning and your thinking.
So proper prompting of AI takes
teachers, building that into a lesson.
Parents, you have to model it at
home and both teachers and parents
having the conversations no matter
who or how it has to be taught.
Alright, that is the end.
Our dos and don'ts.
Let me give you a quick little recap here
because I blabbered, I know I
gave you a lot of information
and I blabbed a lot for that.
There is, did you notice there's
a lot to talk about and cover here
and the answer of is AI safe for
students is not black and white?
I hope with all of my babbling that
that is the conclusion that you have
hopefully come to after the last
episode, part one and this episode.
Okay, so here we go.
Here is an overview of my dos and don'ts.
Don't for teachers and parents.
I do not want you to put your students
into AI tools without any AI literacy
lessons and conversations First.
Next do for teachers.
I want you to use tools that have
guardrails and teacher dashboards to give
you full visibility into student progress.
There are a few caveats and special
use cases and circumstances with
older kids where you may put
them into like a Gemini gym,
but that is not the norm and not
where I want you to start either
parents, you can use these
guardrail tools with your students.
Actually, I did a webinar on this for
varsity tutors and I showed them how to
use school AI spaces, notebook, limb.
And one or two others.
But those were the two big
ones that I showed them.
So you can use these tools too
as long as they're free meal.
So I mentioned school AI spaces and brisk
boosts were two good ones to start with.
You also have a little bit more
flexibility than teachers 'cause
you're working with much smaller number
of kids, so you can use some gyms,
some custom GPTs projects, spaces,
you can quote unquote prime those gyms and
custom GPTs and projects and spaces with
instructions that say, guide not give.
This is the age of the student.
This is what they're learning.
You can also, if you need a baby, step
into creating a gym or a custom GPT.
You can also just do this within a chat
in a large language model and give it a
prompt and say, this is what we're doing.
This is the age of the student.
'cause you wanna make sure the outputs
, are age and developmentally appropriate.
This is what I want you to do.
This is what I don't want you to do.
If you're gonna do that, test different
tools, test different AI models
and find the one that works best.
Also, I'm not sure I specifically
said this, but the one that works best
isn't always going to be the same.
It depends on the task that you're doing.
I gave the example of math.
If I'm helping with math, especially
more advanced math, I'm gonna
use a very different model than
if I'm helping with writing.
So a don't for teachers and parents.
Don't just drop students into a
general purpose, large language
model or chat bot with no structure.
Maybe, maybe, maybe like
upper high school kids.
That would depend on a lot of stuff,
a lot of different caveats there.
But ideally, at minimum, go into the chat
and give it some background and kind of
prime that chat with information about
what you're wanting the student to do.
Also, teacher, I don't know if
I specifically said this, but
teach your kids how to do this,
especially the older kids, how to
prime their own chats to tell it.
Do this, don't do this.
Guide me.
Don't give the answer a big do notebook,
lm. For both teachers and parents,
depending upon for both, really, both
what age student you're working with.
This might be more of a U tool where you
go into it and maybe generate an audio
summary or an infographic, or it might
be a tool that you can put students in
and have them create infographics and
videos and flashcards and audio summaries.
Also, notebook element is really
great as a first scaffold into
teaching students how to research
correctly using large language models.
That leads to my next do, which is for
parents and teachers about research.
It takes a lot of scaffolding, a lot of
AI literacy lessons and conversations.
Putting them in notebook, lm, putting
it up on your projector or your screen
in the front of the room, showing them
perplexity, showing them Gemini, showing
them notebook L, and teaching them
how to verify information and evaluate
information for research purposes.
Especially.
I don't, for teachers and parents, don't
just put them in any general purpose,
large language model for research tasks
without source verification built into it.
A do for teachers and parents.
Do teach your kids how to prompt AI
period, but also specifically how to
prompt AI in ways that actually help
them learn to simplify, to translate,
to help them with task initiation,
that's it.
That's it.
That was a lot.
We covered a lot of ground today and
I could talk about so much more, but
here's what I want to leave you with.
You don't have to be an
AI expert to do this.
You don't have to be a tech expert.
You don't have to have the perfect lesson.
You don't have to feel fully comfortable.
You're likely never gonna feel
fully comfortable because this
technology is moving so fast.
What matters most, more than the tool
or anything else is the conversation.
Have the discussions.
Talk to your students.
Talk to your kids.
Ask them what they're using, ask
them if they think it's always right,
those conversations are AI literacy,
and that is more important than
anything right now to help avoid the
bad things about this technology.
Like companionship, conversations
are available to every
teacher, to every parent.
No login required, no tools required.
Even as the tools keep changing, those
conversations are the foundation to making
sure that we're using this technology
in healthy, responsible, ethical ways.
The research will keep coming,
but building curious, skeptical,
thoughtful humans, that is what we
need to be focused on right now.
Speaker 3: Thanks for
joining Make EdTech 100.
I know educator time is valuable and I'm
honored you choose to spend yours with me.
For more EdTech strategies you can use
tomorrow and ways to bring me to your
school or event, head to LindyHoc.com.
If this episode resonated, hit subscribe
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I'm LindyHoc.
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