Well, you know, who could stop at the refs if they made a call every once in a while, that's all I'm all I'm saying.
I'm really sick of the Taylor Swift drama. It's like, let's just focus on football, please? Oh, I'm glad they stopped showing her every other time. Oh my gosh, the media just won't leave it alone.
So, you know what somebody did, calling her, did an interesting analysis of that, and he was like, everybody has been complaining, you know, about Taylor Swift being shown on TV. But then he did an analysis. He was like, Do you know that they only showed her for like, 15 seconds total out of the whole game, you know? And everybody's like, why are they showing her so much? It's like, it's 15 seconds. Get over it. It's like, yeah, okay, when you put it like that,
you know, it's not the showing her that bothers me. I mean, it is what it is, but if she gets up and blinks her eyes, we get some kind of a news. Oh, that's
Oh, right. Oh, I know, not her fault, though
it's that's not her. That's why I said the media just needs to take a break.
But no kidding, right? Oh, my goodness, so much to talk about, and really the whole reason why we're here today is to talk about research. I love this group so much. You guys make me happy. All right, now, let's get this officially started. Welcome. Let me get some more people in here. Welcome everyone to the learning rebels, Coffee Chat. I am Shannon Tipton, the owner of learning rebels, and thank you everyone for joining me today. It's great to catch up with everybody and have our our little bit of football talk before we kick off. Everything officially today, we are talking about how we can be better at research and how we can use the tools in front of us for research purposes, specifically, a couple of AI tools, perhaps. But I really want to get your thoughts around research in general before we get all techy. Techy right now, for those of you who are new, this is your first coffee chat, or maybe you haven't been here in a while, go ahead and let us know in the chat itself, so that way we can give you the warm welcome you deserve. So let's see who's new, and you guys have to forgive because Amanda went on vacation this week. How dare she? So we'll we'll see how all the resources end up this week. Amanda being gone. Alright, look at all the first time people. Okay, let's see here. Thank you, everyone. Christy, Laura, Rashida, let's see here. Teresa, lots of new people. I love it. Um, yes, it has been a while. Tom but good to see you here. John dorette, it's a pretty name. Dennis Peggy, Loretta, or is, I hope it's Loretta, or I'm gonna, I'm gonna stick with Loretta. If it's, if I pronounce that incorrectly, you will let me know That's fabulous. Yes. And when we come together here, here's the thing. When we come together, for those of you who are new or who haven't been here in a while, here are the rules. There are no rules. That's the rule that we have, that there really aren't any rules. And the reason I say that is because this is an open forum discussion. I want to hear everyone's thoughts or questions, and everybody else wants to hear your thoughts and questions and to share your stories. This is a no judgment zone. We don't care how much experience you have or do not have, you know, so that's what makes this group so powerful and so interesting. Now, as far as your video is concerned, if you want to have it on, like those of you there, that's awesome. We again, we don't care. I don't care if you're in your pajamas. I don't care if you're in a closet somewhere because of sound. I don't care if you're on a bus someplace. It doesn't matter to me and it doesn't matter to the group. It just matters to you. So if you are not comfortable, then don't have your video on. But just know that we really do not care what's happening in your background. If you have a cat rolling around or a dog rolling around, doesn't matter. It was all right. Well, then let's get this party started. Let's talk about some research now, when it comes to research, and as I said in my email, typically, what we say as an L D group is we encourage people to do their. Own research, right? So when it comes to learning myths, for example, you know, around personality assessments or learning styles or any of those sorts of things, we encourage people to do their own research. And I say that term a lot myself, do your own research. But what does that mean? You know. So I think that I have forgotten in my years of doing this that when I say things like, Do your own research, the person on the other side may not understand what that means, you know. So we might be letting down our audience. And so I want to start there, when we tell people or we encourage people to do their own research. What does that mean? So who would like to kick off this conversation?
Mark, go ahead.
I think, sorry about that. I think we may want to separate the concepts of, we'll say big R research, which is all the, you know, following the scientific method and those kinds of things, from small r research, which is, you know, looking up different sources for information. But at the same time, still something that will challenge your biases. A lot of people who are doing research tend to fall into that actually, both big R and small r research tend to fall into the the confirmation bias trap, whereas, if you're in a position to be looking up information that challenges your opinion. If somebody says, Hey, do your research. You need to know that. That means don't find stuff that supports your opinion. Find the stuff that challenges your opinion, and look at the balance or the gaps between
the two. And I thank you. I think that's an important point to make. Right? When we say, do your own research, we are really trying to encourage people to gather from different spots, right, not to necessarily support your Echo Chamber, you know? So you've got the things that you believe in, and it's like, well, I believe in I think learning styles are a thing, so now I'm going to go on the Google machine, and I'm going to find all the research that supports that, right? Versus, let's talk about learning styles, and let's grab from here. Let's grab from here. Let's grab from here. Let's grab from here and see what the collation of data tells us, right? And I think that that's something that we often forget to mention to people when we say, do your own research. We want it to be well rounded. What? What else are we missing from that? You know, nebulous piece of advice. I Tricia, hi,
hey. Sorry. Hi, everyone. You don't see your sources. You got to, you know, make sure the sources that you're you're going for, are correct, and not just somebody's uncle's cousin, who might you know one time read something 45 years ago.
Yes, and that, actually, I don't know if you spoke with Dennis just a moment ago, because Dennis also put that into the chat just as you were talking. It's find the original source studies, right? It's not just Bob's opinion, or, for that matter, it's not just Shannon's opinion, you know, it's what is the actual resource, resource or research behind that? Right? The original source material. What? What other things would we advise people to look for? Is this all fit? So when we're talking about late in a few we're going to bring up these AI tools. But AI is only as good as we use it. So if we are only using it to support Bob's research, then that's what we're going to get back out of it. So it's important to nail down some of these foundational aspects before we go moving into how do we use AI to help us out arc?
One of the things that they practically beat into us in grad school was to look for bias, either in secondary source research, or primary source research, the term, the phrase follow the money, is often a good guide point. So Pharma is a great example. There are a lot of biased pharma, medical, bioscience. Science type studies that have been founded by the R D firms, as opposed to independent research. So you have to know how to how to take some of that research part, how to interpret it, look for the bias. And that's why spending time looking up authors and all that kind of stuff, and citations, organizational affiliations that can, you know, that can potentially skew what you're looking at
right exactly? And we used to call that circular research, I don't know, but I'm older than a lot of you, so it's like, that's what we used to call it, where that meant that, you know, you're looking at who said what to whom, and who got paid by whom to say that, right? So it's like, like you said Mark is like, follow that money trail. You know, a good example of that is the is the goldfish analogy, you know the 10% attention span, you know that one that that research came out of Microsoft, which was came from somebody else, and it stopped there. It was like it came from nowhere else. But really, Microsoft used that as an advertising tool. They weren't really using it as a research based tool. So the more that you dug into it, the more you found that out. So this was that was actually a marketing ploy. It wasn't, it wasn't research that was supported by anything in particular. And we, and we know that that's not true. You know, the whole, you know, goldfish only remember for 10 seconds, or what have you we know that's not true. You know so and that's where that came from. It's like we grabbed on to, we grabbed on to a commercial, and we claimed it as truth, and because we we didn't follow, we didn't follow the path, right? Yes, and the 10 hour, 10,000 hours of proficiency and Dennis, yeah, the 70% of all change implementations fail that one as well. So there's a lot of stuff out there to sort through. Now, here's my question to you, there's a lot of stuff out there to sort through. So how do you go about doing that? How do you organize this? How do you know what I should be reach researching and what I shouldn't be researching? Do we don't have enough time in the day to research every sentence that comes across. So what's your path? Do?
Right now, there's no right or wrong answer to this question. I'm just curious as to what you do, John,
there we go. So the for me, what I'm thinking is I usually have a purpose when I'm looking sometimes I'm just looking for fun, but and new ideas. But usually I have a purpose. I'm looking to improve performance. Yes, I'm a trainer, but I don't do training because somebody asks me to do training. All right, good. I want to know that I can do something with it, that I am contributing to performance. And so I usually have a purpose when I go looking and when I find a study, there are some things I want to look at to find out, you know, how useful is that really going to be? How accurate is that really going to be? Were the results valid? Those kinds of things? Thanks.
Oh, thank you. And I agree with that. I think that's an important thing, right? Because we all have fallen down that research rabbit hole, you know. Or we're going to look at this, and then, oh, that leads us to that, and, oh, my God, look at that, you know. And so the next thing you know, two hours later, you're like me. I've started with, I'm going to research XYZ. Two hours later, I'm looking at baby goats on YouTube, you know. So it's like, how did that happen? You know? So I agree. So if you can go in with a goal, you know, because there are just some hills I'm not willing to debate on at this moment, I have other things to look at, and having a goal, you know, is important, so I appreciate that. And Tricia, you put this acronym into the chat about research. I love that. I had never seen that before. You know, that's new to me, so thank you.
Full disclosure, I just read that two days ago. On noon, they were talking about, you know, research for Food Studies and whatnot, and how to determine if they're but it applies. It's universal. It's great. It's amazing.
That's interesting. Okay, I love that. All right. And. Yes, as I'm my pause is me looking through the chat to make sure that I'm capturing people here. And it is hard to ignore some research claims that are bananas. I agree with you, Dennis. And then that's when you go, Wait a second, what is that all about? And then I got to fall down that research hole, and that's when I find myself finding sources, you know, and in my blog, generally, my blog is generally opinion based, unless it kind of goes back and forth. Sometimes it's research based, sometimes it's opinion based, but generally, I'll have sources within the writing that you can check out. And that's that's the thing. So if you're reading information and it cites nothing, then, then you have to question what's happening there. You know, Dwayne, most people, however, don't know many of the misinformation around stats since we've been told since so many have been told as truth for years. That's very true. So, Dwayne, do you want to expand on that thought? I'd love to hear your thoughts around that. Well,
I mean, I can expand on it in a sense that, you know, I grew up learning a lot of different things that over the course of my time and living, I had to like question, right? So imagine all the things that we've been taught from educational position, from family stories, from legends that were given to us by different people groups, and all the stuff that drive our acting, actions, drive out engagement with our own community and things of this nature. So, you know, when we start thinking about, even when we google something, where did it come from? Well, Google was based on search engine optimization, so half of the stuff that we did get was somebody actually putting it together and then using a sales funnel to get it to us, as opposed to, was it the real information? So we have to really understand where we are, this landscape of AI and landscape of information, because we have so much access to information now that sources are definitely the thing, right? So perplexity and Claude being one of the things that actually bring along some of those cited citations is so important. But look at how many people did all this research with things they never had a clue where it came from,
right? Oh, I love that so much. That is such a great point. Dwayne, thank you. And we can have a whole other hours worth of discussion about the you know how Google has degraded over time. We can certainly have that conversation, because now, when you Google something, Reddit, pops up, it's like, I don't want people's Reddit in my Google search. You know, I don't know what, what who those people are, or what they're doing. And the way that Google pulls that is, somebody asked a question on Reddit, and if it gets like, 100 thumbs up, it gets it gets carried over, it gets indexed. But those people could be approving a snarky message or a joke or something like that that has no truth in it. And so I think that, Dwayne, you're making such a good point there that it's not just about because before we did, used to say, Oh, we googled it, and that was cool. And now you just can't, you can't lean on that anymore. So Mark,
sorry, it works better if I unmute. There was a post I think it was on LinkedIn a little while ago. I'll have to see if I can find it. And I can't speak to the scientific validity of this claim, but an observation was made now that Google, as you've pointed out, has become a lot less reliable and and useful as a search engine because you're populated with sponsored results that come up first. And one of the things that Harold jarky, who's very big on personal knowledge management frameworks and things like that, has said he asked a question in his workshops, where's the best place to hide a body? And the answer is on page two of Google search results, right, right, right. So you you do have to dig and get past the ads and the sponsorship, and it's it's not. I think the take on the article too, was that it's not to Google's advantage to actually provide decent search results as long as they're getting sponsorship, so
we're more money
Exactly, exactly. And no, no wonder the US DOJ is taking a very close look at potentially breaking them up, right?
And yes, and I've heard another version of that joke, and I use that a lot in my presentations, which is, where do businesses go to die the second page of Google. Because nobody ever goes to the second page of Google. So the goal is to get indexed on the first. Page. So, yeah, I've heard that. Leslie, hi, Leslie, good to
see you morning. So you were asking us about the pathway, and then I got to thinking about, you know, Google, like we're talking about. And so, yes, when I'm working with subject matter experts and they're just gone, right, you can't get a hold of them forever. So I start doing the Google thing, which is a bad thing in my life, because I'm in government. And so I write some stuff down, right? And then I go, okay, my subject matter experts love to correct mistakes. I'm just gonna send what I wrote over to them and let them hack the crap out of it, you know? So sorry, my French.
Well, that's okay.
Like, just mark this sucker up. Really, this isn't true. Are you sure Google said it was true? You know? So it's a fun conversation with this me, yeah.
And then it forces them to think critically too. It's like, okay, here's what I my initial research says this, and that's usually what I say. It's my initial meaning. I didn't go deep. But here's what I found on the first page of Google. And you tell me whether or not that works for you or where I need to go from here, right? Tricia,
hey, yeah. So I just Googled learning styles. And one thing that we aren't talking about, that Google's just started to do is the AI overview that pops up at the top that's supposed to be helpful. Yeah, learning styles are important in education when the professors. So you know, not only do you have to do the sponsored and the ads, but now the helpful AI is also for those of you who don't believe in learning styles, like I don't, I don't agree with the AI overview. So you have to everything that pops up. You have to grain of salt, right?
It's a matter of really questioning, and it's also important to understand. And here I'll take a quick, quick poll there in the chat, you guys let me know how many of you attended the AI as your instructional design sidekick, or the AI as your image generation sidekick webinar. So just let me know that in the chat, because in those webinars, I covered what exactly is an LLM, and where it gets its information right. And the llms large language models get their information from the Internet, and, you know. And so if there is a prevalent opinion floating around the internet, that's what's going to be that's how the LLM is going to be trained, and so it's up to us to retrain it, if you will, you know, so that's part of understanding what large language models are all about, and it's also important to understand that when you are doing your research. So now let's shift. Let's talk about this from a technology perspective, right? So now we've talked about using Google. Now, how many of you are using an AI tool to help you with some of your research, or you've dabbled with it to see, oh, if I put in this question, what will happen? You know, so how many of you are in that space right now? Yeah, yeah. Leslie,
okay, safe space. I'm not allowed to use it, but I do. So we've been blocked state government, right? So we've been blocked from a few Gemini is one of them, but they haven't figured out all of them, so I still just go use it perfect. Perplexity is one of my go tos. Okay,
yeah. Perplexity, Claude, chatgpt, Gemini, there's a whole host of of AI tools out there for people to bounce around. Um, and, yeah, AI in your organization heavily restricted, but you know, we all have, where is my phone that's
is Google Scholar still any good you guys, I see you put it in the chat, yeah, is it? I was thinking it was outdated, but, oh, I can go back and use it, because you guys use it,
yeah, Google Scholar. I still, yeah, I use Google Scholar. I still double check it just to be sure, you know, but for the most part, I use Google Scholar a lot. Okay, yeah, and, and, yeah, on your fast I was reaching for my phone. It must be downstairs by the coffee maker, which is, I guess, a good thing. Um, so chat GPT, it has its app. A lot of these AI tools have their apps that you can use on your phone, and that's how a lot of organizations get around it, right? You know, where a lot of knee jerk decisions were made when chatgpt first came out, which has, you know, the granddaddy of most of the AI programs now a lot. Of other organizations have made their own gpts, you know, to support it, you know. So you might have an AI tool within your organization that's not nearly as robust, but seemingly more secure, but really it's only as secure as the information that you put into it, you know. So that's when you have to really be sure that you've got a robust or you don't have to be sure. But hopefully your IT department is pretty robust. All right, so let's see Google Scholar copilot, yep. So there's, there's, is a lot out there. And now here's my questions for you. So when one of the tools that let me get here for you, now, if you use chat, GPT, one of as you may or may not. Know, chatgpt has custom gpts or apps, if you want to consider it that way, that's you know, they have customized apps that you can use to help you with whatever task you want, so you can click on a recipe app or any other sorts of any other sorts of apps that you may think of now, it also has scholar. So if you went into and let me bring this up, let me share my screen for you guys here. Okay. All right. So everybody seeing my screen, give me a thumbs up. Let me know. All right, let me bring the chat back up in front of me. Here we go. Okay, well, so as you see here, scholar GPT. Now there's all. There are so many others. Let me go back here. So right here where it says, explore gpts. This is where you're going to find this information. And you're going to find all of these custom versions of things that you can do with chat GPT, build your resume or write code image generators. Connects with Canva Dolly, create your own coloring book, if you will. You know so lots of things out there that you can source now you can also source research. So if we just plug in you, uh, research, here are all the different and there's more. See more, but wait, there's more out there. So here's all of these different things that can help you. So if you're writing a research paper, here's a GPT to help you with that. Medical research, academic research, case law research, qualitative research, data analysis, so all the different sorts of research that you can possibly hope to gather. Now the one that I like to use is this scholar, this scholar, GPT, and what it does is it, it provides you with different ways to analyze data and also different ways for you to get data back. Now, let me get out of this. Let me get back here. Bring it up as full screen. We'll get rid of this. Here we go. Alright, so now here it gives you some starter gives you some starter questions. And what you can do is, if I drag in, and I'm going to I'm going to drag in, let's drag in something here, let's go active learning set. So here's a research paper on active learning sets, and I'm just going to throw that up there. Then what it's going to do is it's going to give you, first off, it's going to give you a summary of what this PDF stands for. And then it's going to ask you, if you what else do you want? And because I didn't tell it anything is this is where it automatically goes. All right. So now, what other aspects of this do I want? I want? What? What else would I want? I would like identify any biases. My spelling, of course, is always as always is off. There we go. Okay, so now we see where it's a. Applying as with the different sorts of biases that it sees in this paper. Now, why is this important?
Look at all the different biases and some some of these biases, they're okay, and others, it's like, oh, I need to look at that. So we've got a confirmation bias here. Although the guide promotes open questioning, participants might unintentionally ask questions that confirm their own viewpoints or assumptions about the presenters situation. This can lead to questions that steer the presenter towards a pre assumed direction rather than genuinely exploring new possibilities. So it's identified this particular type of bias within this document. So now what I'm going to do is, let's let's go back. Let's start a new chat. Shall we actually let's go here.
So earlier, I plugged in a research paper and some of the things that you can have it do for you, summarizing question, critical inquiries, contrast, analysis, key concept, clarity. These are all of the things that you can have this particular GPT do for you. So what I plugged in was the 2023 learning at work survey that came from LinkedIn. So I asked it to analyze this report for me, and I asked it to identify, let's see. So I went about again. I asked it to identify any biases that might be included in this paper. So here we go. So according to this paper, or according to this particular GPT, there's a bias towards digital learning solutions. The the paper was written with an eye towards larger organizations. Also an interesting one popped up here, bias from survey methodology and respondent demographic. So this was the survey primarily conducted among UK recipients, so therefore there is a geographic bias.
So what are you what do you guys? What do you want to see? So now that we've got this up here, and we know of the different items that we can ask it, what questions do you have right now. Let me stop.
Have you used the fact fact check part of that?
Let's do it. I
I still say, please, I don't know why. Maybe it's the Midwest in me. So let's, it's, it's searching its own database. It's searching, it's going to search the document and then compare. I'm
so these are the statements coming through that it believes have been verified. And then if there were some here that were not verified, I don't know what this means, but I'll get rid of that in a second. So second, statements requiring further context or clarification. So that's fair. So it's not saying that the information is false. It's saying you may want to look for further clarification from this. Now it might be interesting to go in here and say, Can you cite additional sources that support this paper? Let's see what it comes up with. And of course, any time that we're going to ask a large language model to cite its sources. We're going to be good researchers, and we're going to go back and we're going to double check it sources, because we don't depend on one source of information. So.
Okay, and so right away, it's being honest with you. There's an issue with retrieving additional resources directly. However, there are some widely recognized sources that align with the themes and findings. So here's where it's going to encourage you. You know you can go out on your own and look at these variety of different sources that may or may not support. It's this research in of itself,
and then it gives you the links for you to be able to go and find it. Although these links don't work, that's fine. I always find that that's an issue with any any AI, sometimes the links work, sometimes they don't Okay. Now, now we have this. What else can we do with it? What are some of the things that we may want to ask it? So based on what you guys have already talked about, okay, so one of the things we talked about was understanding who, who paid for it, right? Who, who supported the research? What's the question I'm looking for here? Help me out? Funded? Quite, unfunded. Oh, thank you.
Who funded this research? There we go. Let's see. Let's see if it can tell us that.
Oh, with CPI t see CIPD, I'm sorry, not LinkedIn. Okay, so there you go. So now what? What do you do with this information? You guys tell me. So it says here, it was funded by CIPD, Chartered Institute of personal Personnel and Development. Okay, in addition, the report acknowledges the support of YouGov, particularly Ian Neal and Sophie Webb, who contributed this collaboration with YouGov, suggests some external involvement in survey design or data collection, but the primary funding and initiative came from the CIPD itself. All right, so now what's our next step?
I would go research those two people's names in YouGov, or There you go.
And while we're here, we could probably do that, right? So we could take the first steps here by saying, let's, let's just ask it. Would you do? You consider C, i, p, d, a rep to full source. Of course, that's always nebulous, right? It's like that's an opinion. But still, let's see what it let's see what it says. It's not again, opinion, not fact. Let's see I.
Yes, you're right, Leslie, that's what that's that's the the thing. That's the name of the game when it comes to research, there is no one. Here's your magic wand, here's your one statement of truth, or your one source of truth, right? Okay, so here we go. So it gives you all of the background, not all of it, but a lot of the background for CIPD itself, and we could probably do the same thing for these two. Let's, let's see what it says.
Who are?
There we go. So now what we're doing is we're using this tool. And the reason I'm using this scholar GPT rather than chat GPT itself is because the same reason why you might use Google Scholar versus regular Google. Oh, there's a good question, Douglas.
There we go. I
So you see where I'm going from this what's what are your thoughts? Is this helpful? Pat, scholar, GPT, I have the paid version of chat. GPT is. So I cannot tell you, I think these custom, these explore gpts. I think you get those with the free version. You
so anyone who has the free version out there, if you want to verify this, there we go. Thank you.
I can verify that. Okay, there we go. Thank
you so much for that. All right,
I had a question in the chat Shannon with these custom gbts. Does anyone know how to assess if the GBT itself was written soundly like I've built my own gpts, and I can do a terrible job and still post it out there for public consumption. So when we're using the General chatgpt, we're relying on the fact that, you know, OpenAI did a good job building it, but this was just built by someone. Yeah, is there? Does anyone know of a way that we can actually take a look under the hood see how these gpts were built? I saw when you first searched for it, it did have the name of a group that created it, and it did indicate that it was the number one used scholar GPT or research GBT. But I'm still curious about like, who built it? How did they build it? How do we know that this is a reliable GBT to be using, or any of the other ones that are in that custom list?
That's a great question, and thank you for that. Amy, what I did is I went back and I looked at the different people who created these gpts. So I researched the I researched the researchers to see whether or not they were viable and whether or not they were, on the surface, at least trustworthy. And then what I did is, after using this for a while, I went back and I did some research on it that I knew, that I already felt confident in. So I kind of put it through my own testing parameters to see whether or not it at least came back with information that wasn't disinformation, you know. And so through this you're you're building trust with it, and each GPT has its own sort of personality, if you will. And so people are going to gravitate to one or another versus on the the tone and how they like, the answers coming back at them. And one of the reasons why I chose this one was because of these different options here, you know. So it gave me all of these different options, which I didn't feel a lot of the other ones did a lot of the other ones just gave me executive summary type of things. They really didn't do a good analysis of it. And so I felt this one gave me better analysis than the others did, and that's that was my path, and everybody may have a different path. Trisha,
okay, so this summer, I took a six week seminar at Stanford University about AI. Number one, thing, nobody can define AI number two, my big thing about the AI was the data that they used to create and train and create and train and populate these models. Oftentimes they buy pre made libraries of data. And my question is, where did the libraries come from? Any regulation over the libraries? How you know what's in the library, so things like that? And the answer is, they just are there,
right? And again, it's, you almost have to research your research, you know. So anything coming out of here, it's not that I take it with a grain of salt. It's that this gives me a really good foundation for moving forward. Now let's take a look at another tool. So now what we're going to do is we're going to take a look at notebook and notebook LM is not new. It's been around for at least a year or so, but it's only really become it was in beta for a very long time, and then it over the last few months, it became more and more available. Now here is where you can take the information that you currently have, and plug it into here to get information and and synthesize notes, for example. Alright, so the action learning set paper that I just plugged into scholar GPT, I plug that into here for you for an example. So what I did here is I plugged in all of these different sources and created these different notes. Now let me tell you what this means, because it looks like a very busy screen, and so you might be confused right off the bat. So let me tell you here. How this breaks down. So what notebook LM asks you to do is it asks you to input different sources. So when you go back, let's click on a new notebook. You can upload different sources that you may have that you wanted to collate for you. Now let's play around a little bit. Let's, let's, let's pick a topic that's an pretty easy topic. Let's go with, let's go with learning. Let's go with learning style. Shall we? No, let's go with learning myths. Let's do that one so somebody find me a link about learning myths.
Any only that can't be hard to do, it
could shouldn't be hard to do. Somebody, somebody, plop one in there. There we go. Thank you. Okay, so I'm going to throw this in here. Thank you, Susan, okay, and so now it's a website, so I'm going to click on this website link. I'm going to plop that in there answer, okay, so you see that it comes up here common myths. And here we've got a summary of the article. And here are some questions that you can ask. You can ask these questions. Let's go with this one. What are the most common myths about student learning and how are they debunked by current research? So now what it's doing is it's going back through this article, and it's giving you the answers. So it is not going to the internet, per se, it's going to what you told it to look at. And so here you can see, right? So here's the citation, right here, when you click other citation, more citation, right? So it's going back to the information you fed it. Somebody give me a different somebody find me a research or a PDF file or something here that I can add to this, a video. Find me a YouTube video, somebody.
And that is what is. That is what makes notebook LM unique to the other AI tools that are out there, because it's reading the information that you tell it to read that you are giving it to access. All right, thank you. Tom, here we go. YouTube video.
I should warn you, I picked one that I thought I would have been offended by. So, okay, but I haven't watched it.
Okay, that's all right. So now you see that it is, now what it may come up with. Let's see. Ah, it liked it now, notebook, LM sometimes will tell you that it doesn't like a YouTube video because it doesn't have a transcript attached to it. It needs a transcript. And so what you what you do? And yes, Dwayne, you can use a PDF. So Dwayne, if you have a PDF somewhere, or if you can locate one about learning myths, please plop it into the chat, and I'll insert it into here. See Dwayne, you spoke up, and now you've got homework, all right. And so what you do, in the case, if you've uploaded a YouTube video that doesn't have a transcript, open up a different tool, pull the transcript out of it, and then copy and paste it. You Um, yes, it's, well, it's as private as any AI is going to be. And you can, I haven't found a limit yet to how many sources I can put into it. I'm going to show you what it can do here, but I'm looking for, you know, a certain number of resources before we move forward. Okay, now you can also take from your own notes. So let's see if I've got something here in my own documents. Go I got something here about move a couple things out of my way. I'm going to see what I've got here.
Give me one second whoop. That's not what I meant to do. I do not Oh, here we go. Maybe. So let's plug this. Let's see here now what I can do just based off of what we put in here. But I do want to put in one more source, so you notice here that you can this is a Google tool. So this tool comes with Google so if you've got a Google login, you can access this. You can copy and paste text, you can put in a Google Doc. You can put in a Google slide. Oh, here's the source. Limit. It's 50. And so what I'm going to do is I'm going to put in this PDF and see what it says, which is about adult learning and literacy. And right here you can see I clicked on the source, so now you can see what the key topics are about this source, the summary of it, and a recap, a full recap of it. And also, well, this is full This is like the transcript of it. This is the summary. Now, here's something that's actually kind of cool. Let's go back here, where it says notebook guide. And now I've got all of these sources selected, and you can do them individually. So let's say, let's unselect this. Let's just go with common, miss. Let's create an FAQ.
Give it a second while it's thinking about it.
All right. So now here is an FAQ
about let me go back here and FAQ. What are the main learning styles and how can they be used to improve learning. So this is where you've got to use your own common sense here. And so it says here, these are the main learning styles and how can they be improved. But we know that people have a mix, or that it's not true. It says here that there's been a shift, current challenges for using it, etc. So it's just a it will give you a summary of what or you're building your FAQ based on what you see here, and you can edit this. So if there's something in here that you don't like, you can edit that as well. Now the other thing that you can do is you can create, let's get out of this one. Let's go to this one. Let's create a study guide out of the let's see, I saw a hand somewhere.
Oh, I'm sorry. That was me. I don't know if it's just me. I was going to type it into chat. Is adult basic education and acronym everybody uses, because I have not heard that before. And what does it mean to
to you? I i Don't distract, yeah, it's actually pulling from this. It's not pulling Yeah, okay. And so we can save this. This came from adult learning, so I can change that, so I can find it later. And so now here we've got the study guide. So this is the study guide that we've created based on that paper. And I'm not saying whether or not this paper is accurate, not accurate, or or what have you. What I'm showing you is how this particular tool works. And then from here we can, we can take this if we wanted to, and we can say we want to ask different questions. I'm sorry. I want to go to this one critique suggested related ideas, create an outline, help me understand so now I can ask questions specific to this particular study guide, if I wanted to. And then from here, we can take all of these sources and have them review all of these sources. For example, what we could do here is, and this is one of the cooler features of notebook LM, is its ability to generate a conversation. So it will take all of this information and create what seems to be like a pod. Cast, if you will, based off of just the information that you put in. And again, this is what makes notebook LM unique and special to the other ones, because it's only looking at the information you tell it to look at, which is why this research conversation that we had was really important, because you have to know that the information that you're giving it is relevant. How much does it cost? It's free. It's free for now, yeah, I love that Jeanette Build A Bear, but for information, yes, exactly, exactly. How Thank you, Chris, You're so thoughtful, and it takes a while to generate a conversation. So let me go back here and let me find I was playing with this for the coffee chat that we just had about the book club. And so it it created the conversation. I'm going to have it loaded and I'm going to download it, and now I'm going to take it and I'm going to put it here into the chat for you, and so you can listen to it yourself, if you want to, while I'm talking. And what's really great about this is it really is I would not use this to create podcasts because, as I have played around with different identities using notebook LM, it's the same voices, using the same tone, the same sort of structure. So if you're thinking about, Oh, I can use this to create a podcast, no, don't do that. But maybe it would. It would. Here's where I would use it. Is if you have information that you want to share with your organization, and they don't have time to read it, this might be helpful for them. They could listen to it. So you can give them these audio clips that give them a deeper dive. For any piece of information that you want to have a deeper dive given to them. Okay, well, you know, Dwayne, I haven't used 11 labs, so that's why I hesitate to give that particular piece of advice, because I haven't used it. I don't have experience with changing the voices out. So I'm trying to keep this simple. But I appreciate that you mentioned that. So if you guys want to experiment with 11 labs and see what you come up with, I would love, I would love to learn more about that. Dwayne,
if I could add to that, what you get is a transcript as well, right? So you can actually take this transcript of this new conversation that is based on that information that you just generated from Google, and take that over now to 11 Labs, which is a voice synthesizer as well as Synthesia, and either one of those can be correlated into real conversations with voices that you really like, and then you kind of put those all together. So there are some pieces that you know, when you think about these tools, you gotta be looking at collaboration with these tools, because you won't use one without the other just like you wouldn't do that research without Plex, you know, perplexity, and some other different sources, then you bring it together into chat, GPT or this particular thing. So just want to kind of bring that to everyone's attention, because there are some ways to do that, where you use Google first, and then you take the transcript and actually create it the way you want it so it could and people are doing podcasts right now. I was just on one yesterday, so, and I'm not to shine down on what you said, Shannon, I just wanted to add that to the conversation that is now available absolutely,
you know, and I do encourage that as we're just talking about this one tool, I don't want to muddy the waters by bringing in a bunch of other tools in with it, and we can do a workshop on that later on, where we can talk about how all of these different tools do work together. And I think that's a great tip Dwayne, is that you can take the transcripts off of these and move it into, you know, whatever different tool that you want, so that it does become useful and relevant for your organization. If you're just thinking about suing, I just want to do something quick. This is, this is what you can do, and you can upload here. Here's another way to do it, if you've got, if you're starting a book club and everybody's got the PDF version of the book, you can upload it here, create a deep dive, kind of a cliff notes version, and then send that audio out for a chapter or a section or what have you. So these are some really quick wins that you can use. This tool for now, we are at the top of the hour. Actually, we're past the top of the hour. And so I thank you all for hanging out with me and having this really robust discussion. I'd like to remind you that our Learn Something New Wednesday, October 23 is all about accessibility, and so we have Sarah Mercier with us, and she's going to be showing us how we can bring accessibility into our learning designs, and how we can do it in a reasonable way, in a fast way. We can use different tools to make this work for us, and it doesn't have to disrupt your workflow. So hopefully you take you have some time to join us for that. That's on october 23 and don't forget that our next Coffee Chat for those of you who are new, these happen every other Friday, so not next Friday, the Friday after our topic is all about change management. So how can we help our organizations navigate change, especially right now, there's a lot of stuff happening right now with organizations everywhere. Everyone is busy, so what is our role in helping them our teams navigate change? So that is what is coming up in the next few weeks. So I hope to see you guys there. And thank you once again for joining me for this conversation, and thank you everyone for contributing. This was this was awesome. And again, this is why I love this group. You guys are fabulous. Thank you so much for making my Fridays. Now, anyone doing anything special this week? This weekend,
I'm working, you're working all weekend, all weekend,
although it should be mentioned. So this is interesting. It should be mentioned that Tom you, you are the king of the windmills here. So when generation, that's where Tom works. And I think that's an interesting topic, not necessarily for LED, but it might be a good sidebar topic.
That's why I was wondering what a B, E is, and whether other people use that adult basic education. I mean, I feel that's what I do for the energy sector, for people who come in. So I was just curious if that's a common term that's all. Ah,
good. Thank you for clarifying that. I
mean, because we because we can't possibly know the person's background as they walk in the door.
Yeah, and I'm sorry not to brush that off. Tom real quick, Dwayne, I see your question there, and just connect with me. So my email shannon@learningrebels.com Yeah. So we've got fall coming up, and apples and apple cider, and football games, all of the fun things with fall, really, you know, football I tell you, football season, that's my jam, other than NASCAR, as you guys know. So we've got NASCAR and football. And for me, baseball season just gets in the way of football season. That's it. That's how I feel about that. But hopefully you guys all have a great weekend, and I look forward to seeing you next time. So Bye, for now. Bye.