Hi everybody. Dr. O here. Welcome to chapter one in our nutrition course. This is just a basic overview. Like most science courses, the first chapter is really just an overview of things to come. We'll talk about, we'll introduce topics here in the first chapter that are really going to be covered in much greater detail. A lot of them have their own chapter coming up later. Let's go ahead and dive in. The first, we have just an icebreaker here. We all know we should eat healthy when we can, but often we make less healthy choices. What contributes to our choice of food? We'll talk about why we eat and why we choose what we eat in this chapter and really throughout the course. We all understand that food should be nourishment and food should be fuel, but food is clearly so much more than that. We make a lot of food choices based on habits, based on how we're feeling. We use food to maybe feed our emotional states as much as we do, feed our biological systems. That's something we'll talk about. That's why psychology is so important when it comes to nutrition. Most people do understand the basics of what they should eat, but most people don't eat those things either. That's something that I like to focus on a lot of this idea of how our ancestors treated food compared to us. Our ancestors, they had a sacred connection with their food and it was nourishment and it was super, super important to them in many cultures anyhow. But now it's just, we just eat based on taste and convenience and price these types of things. All right, so I'm sure you can kind of answer this question for yourself as well. So learning objectives, you can go through these, but we'll try to hit all these things here in this chapter as we go through, but we talked about food choices. We will cover, we'll introduce the major classes of nutrients. We'll talk about the scientific method and how nutrition is a type of science and what makes it a good type of science, what makes it a kind of a poor type of science. So we'll cover those types of things. The categories of the DRIs, which are your dietary reference intakes, you've probably heard of the RDA, the recommended allowance of different things with your foods. That's one of the DRIs and we'll cover all of them. Explain how the four assessment methods are used to detect energy and nutrient deficiencies. So we'll talk about the, if you were evaluating a patient or a client and evaluating their nutritional status, what types of tools might you use. And then we'll look at the relationship between food and nutrition and chronic diseases. All right, so let's jump in talking about food choices here. So why do we choose to eat? And why do we choose what we eat? What time we eat? All these types of things, right? There's tons of answers here, but you see the first choice is just preference. When you survey people about what they eat, you know, generally speaking, taste, convenience and cost are going to be the top choices, not nourishment, right? So we eat what we want to eat, basically. And unless we're purposefully trying to maintain a diet where we are eating a specific way, maybe, you know what, you're on a low carb diet, a low fat diet, a gluten-free diet. Unless you're specifically trying to eat a certain way, we basically eat what tastes good, right? So what, and that might be, it might be, you know, the chemical taste of the food. It could be a mouthfeel thing. I know there are foods that I don't eat just because I don't like the mouthfeel. Peas are a great example for me. So we eat the foods that we want to eat, right? And I think everyone should to some extent, right? We'll talk in these early chapters about the idea of sustainable diets and treat meals or cheat days, whatever terminology you want to use, right? The term diet actually just means a way of living. So we always think of it as this structured thing where we power through and white-knuckle our way through it as long as we can, but your diet is just the way that you eat, right? So one thing I want you to think about, though, is when it comes to your diet is ask yourself, if you consider yourself more of a moderator or an abstainer. So we'll talk about moderation later, but a moderator is someone that can follow that 80-20 rule, right? They can have a snack every day, or they can have a treat meal once or twice a week, and they don't really fall off the rails, right? They can have a couple of cookies, they can have a piece of pie. An abstainer is someone that does better if they completely avoid things rather than eating them in moderation. Like personally, I'm an abstainer. It is so much easier for me to just say that, no, I'm not going to have ice cream, than to decide how much ice cream I can eat, how often I can eat it. It's actually really freeing. People look at my diet sometimes and think that it's super, super strict, but I find it very freeing. If you ask me if I want an ice cream, the answer is no. I don't have to think about it, right? Because I don't have to hem and I don't have to think about, oh, maybe I can have a little bit of it. It's just easier for me to say no. It doesn't mean that I never have ice cream, but I rarely do, whereas a moderator might be able to follow more of that 80-20 rule. So habit, right? We eat when we're bored.  We eat the foods that we've always eaten. These are habits, right? And I think that these things can be changed, right? It takes some willpower and some effort to change your habits, but habits can be changed over time. So now, you know, maybe you reset this, and now your habit is to reach for healthier foods instead of foods that maybe aren't as good for you. Ethnic heritage and regional cuisines. So this, you know, I've taught students from all over the country and all over the world, and people eat the foods that they were raised eating. And I think that's really cool, right? That's one of the cool things about having a diverse student population is I get to learn so much about the cuisine and different parts of the world. And there's a lot of similarities, but obviously every area has its own flavor, even just in the United States, different parts of the country eat things differently. My wife used to live in Tennessee, and they eat foods that are much different than we do here in South Dakota and Iowa. Social interactions. This is something that, you know, over time, right? The default used to be that you ate your three meals, right? If you asked your parents if you could have a snack, they would say, no, it'll spoil your appetite for your meals.  But now, food is related to everything we do, right? You go to an office and there's donuts or cupcakes sitting out. We eat when we go to the movies and the baseball games and the birthday parties and all, you know, wine and cheese mixers or whatever you want to call them. So food has become a really big part of our social interactions, for better or for worse. Marketing, right? You think about it. You know, companies are spending millions and billions of dollars to try to convince you to eat in a certain way, right?  Availability, convenience, and economy. This is, you know, I said cost and convenience matter a lot. I know how busy my students are. I know how busy we are, right? It's just sometimes you have to just choose the healthiest food that you can make quickly, right? So convenience and then of course cost, right? We live at a time when food prices are skyrocketing and you have to make decisions based on cost. So there's, you know, we'll talk throughout the semester about ways to eat healthy on a budget and these types of things. This is where you see the benefits of home cooked meals. Obviously, you know, when you eat at home, food can still be kind of expensive, but it's generally much cheaper than when you eat out and meal maybe spending Sunday meal prepping and having food that you can take with you when you go to work or school will save you a lot of money because you're not you're not stopping at Starbucks and spending $7 or you're not stopping at McDonald's and spending $7 there as well. All right, positive and negative associations. This is like I love eggs but my stepdaughter can't stand them. She threw them up one time when she was a kid and she just doesn't like them. So I know that I have a family member that won't eat things that are white, right? Just because because of a bad experience. So positive and negative associations.  I don't really crave hot dogs any other time, but it's just part of my childhood. Then there are some foods and different things that I don't like to eat because of negative associations as well. So emotions. This is what I meant earlier when I said we don't just feed, we're not just using our body to fuel ourselves, right? We use it to alter our emotional state, right? If we're happy we eat, if we're sad we eat, if we're bored we eat. All these types of things can impact our food choices. And the problem is if you're sitting around bored or stressed, you're not like, you know, I really want some kale now. It's usually I want cookies, I want soda, I want ice cream. It's these types of foods. So generally, certain emotional states make us more likely to eat at the same time. They make us less likely to make good food choices and that's a big deal. It's something that we have to confront. Our values. This might be, you know, maybe because of your concerns about animal welfare that you practice a vegetarian or vegan diet. That would be a good example there. Or maybe focusing on food quality. You know, personally we really believe in eating animal products in my household, but we also believe in animal welfare. So we get our eggs from someone that we know takes good care of their chickens. We get our milk from a Mennonite family in the area. We consume raw dairy here. We get our meat from farms that we trust, right? Where they say that, you know, the animals have really good lives and I've been out there and I've seen these places. So values certainly play a role when it comes to food choices. Body weight and health. Are you eating to maintain weight, eating to gain weight or eating to lose weight, right? And there are people that are doing all these types of things. So you look at like, you know, studies show that people that consume diet soda are more likely to be overweight. Well, that's the problem with nutritional research. Doesn't mean that consuming diet soda makes you gain weight. It means that people that are overweight and are trying to lose weight are going to consume more diet sodas. So these types of things. So nutrition, just do you eat whole foods versus processed foods versus ultra-processed foods? We'll cover that throughout the next couple chapters as well. But really all food has been processed. If you think about it, you know, your milk has been pasteurized and your meat has been cut up for you and these types of things. But even cooking food is processing it. But this is a big deal because studies show that people that consume a lot of highly refined and processed foods, they eat a lot more calories, right? You might consume, if you eat a lot of packaged ultra-processed foods, you might consume 500 calories a day more than someone that eats more whole foods and less processed foods. All right, so distinguish between processed foods and ultra-processed foods. Why is some degree of processing acceptable? At what point does processing become unhealthy? Right? This is, again, we can't do all the discussions on this video like this. This is what we talk about in class. But I think that if the processing has made the food less nutrient dense, that's when it starts to become a problem.  This is an example of a minimally processed foods that's actually kept as nutritional value or in some situations made it more nutritional for you. But when you turn corn into corn syrup, right, or you turn, you see here candy, canned cheeses, pop tarts, right? These things are examples of ultra-processed foods. Let me read that last line.  That's a really bad situation, right, when you look at, and that's where we see this paradox, right, where we have, you know, people that have less money to spend on food are more likely to be obese and you would think, wait a minute, if you're eating, if you have less money to spend on food, wouldn't you be underweight? But the cheapest foods are generally the foods that are highest, they're dense in calories and fat and sugar. What they don't have a lot of is nutritional value. So people are being starved of nutrients while getting too many calories at the same time. So that's a bad thing, right? So you decide where you fall on this continuum, but generally speaking, that's what I look at when I think of an ultra-processed food. When you've removed the vitamins and minerals, when you remove the fiber, that's when these things become a problem. All right, so the nutrients, the six different classes of nutrients we're going to cover throughout this semester. Each of these, except for water, is going to have its own chapter, but then there will be, we'll talk about water a lot as well. So we have carbohydrates, proteins, vitamins, minerals, lipids or fats, and water. So here you see the human body on the right-hand side. You see that we know we're made of basically 50 to 70% water, mainly depending on how much fat and lean tissue we have. We have a lot of fat reserves.  Then at the top of the pictures there, you see carbs, vitamins, minerals, proteins, etc.  All right. So let's go ahead and we'll look at these here. So some of these nutrients are going to actually provide to provide energy.  They have caloric value, whereas water, vitamins and minerals do not. So there's no calories in a vitamin or in a mineral. Doesn't mean they're not super, super important, but they don't directly provide energy. All right. And then the term essential. You're going to see this. There's a couple of terms in nutrition that you have to kind of define and one of them is essential. When you say that something is essential, what it means is you have to eat it because your body can't make it or can't make enough of it. So just because, excuse me, so we'll have like essential amino acids and non-essential amino acids. Well, you need all of them, but the non-essential amino acids aren't any less important, but your body can make them. So you can make them if you need them. So for example, there are essential fatty acids. There are fats we have to eat because our body can't make them. There are essential amino acids, like I mentioned, but there technically aren't essential carbohydrates, and that's because your body can produce them. It doesn't mean that you shouldn't eat carbohydrates. They're a phenomenal fuel source, but your body can technically make them. So they're not considered essential. So that's the word essential, what that means. All right. So let's start with, excuse me, itch, my nose is itching. Let me get a drink here. I'm not used to these longer videos. Most of my videos are four or five minutes long. All right. So let's start with the energy yielding nutrients.  So macronutrients just means you need a lot of them, right? We need grams and grams of them, whereas we need milligrams and micrograms of our vitamins and minerals. So first of all, when I say the word calorie, I'm talking about a calorie which technically should have a capital C, which you don't see here, but a Kcal is the same thing as a calorie with a capital C. So when I say a calorie or when you look at how many calories are in the muffin you're eating this morning, that actually is a thousand true calories, but don't worry about that. I don't want to confuse you. So when we're talking about calories, we actually mean Kcals or Kila calories. All right. So it's just a measure of energy, right? Carbs, fat, and protein have different amounts of energy in them, but that's what we're talking about. If you eat 400 calories for breakfast or 600 calories for breakfast, it's just a measure of how much energy was made available from the food that you did consume. Okay. So energy density is a measure of energy a food provides per gram. So this would be if you're trying to consume less calories to lose weight, then you'd want to eat foods that have less energy density. You're getting a lot more volume of food for less calories. If you're trying to gain weight, you'd want to eat foods that give you a lot of calories per gram. All right. So you see here, fat provides more energy per gram than carbs or protein. A really important point here is that so carbohydrates there are four calories per gram. Protein, also four calories per gram. And fat is nine calories per gram. So make sure you know that and then also note that alcohol is seven calories per gram. So why does fat have so much more energy than carbs and protein? It's because it has less oxygen. If you look at a periodic table, oxygen is pretty big. So fat has less oxygen so you can cram more hydrogens and carbons into a gram of fat than you can carbs or protein. So carbs, four calories per gram, protein, four calories per gram, fat, nine calories per gram, and then alcohol, seven calories per gram. All right. So why do we need energy? Well, we have to, we need energy for our metabolism. Your metabolism is a sum of all the chemical and physical processes occurring in your body. So we have to, we need, we need energy to build things and break things down and all of that. All right. So then we have the rest of the nutrients. So we just, we just covered the three macro nutrients really quickly. They have their own chapters coming up later. Now we have vitamins and minerals. So one of the first things you're going to notice here is vitamins are organic and minerals are inorganic. Here's another, another bit of terminology that you have to understand. Organic just means carbon-based. Doesn't mean that you buy it from a, from a farmer's market, right? So that, that, that means that too, but not in this sense. Organic, so vitamins are built around carbon and minerals are not. So like it says here, minerals are the simplest nutrients. They're just found on the periodic table. So calcium, magnesium, those types of things. So the, the minerals are on the periodic table. They're in the simplest form. They are not carbon-based. Whereas vitamins, so we'll look at your water-soluble and fat-soluble vitamins, they are built around carbon, which is why they're organic. Now notice that neither of these provide energy. I mentioned that before. There's no calories in vitamins or minerals, but we need them to release energy and that's especially the vitamins. So when, when, when I talk about energy vitamins, you probably think of B vitamins, right? Look at all these energy drinks that are loaded with B vitamins. There's no calories in B vitamins, but what they're needed for is the B vitamins are going to be, are going to be the, the coenzymes that are, they're going to power the enzymes that allow you to get energy from your carbs, your fats, and your proteins. So they don't directly provide energy, but you can't make energy without them. And that, that's going to be your vitamins. So minerals, we think about, you know, the minerals in our bones and our teeth and these types of things. Then water, you know, we'll talk about water a lot. I've done several videos already on, on water that I'll certainly share with you in the course shell, but water is critically important because it, like you see here at the bottom, it provides the environment in which nearly all the body's activities take place. So water is needed. We remove water from things. When we build structures, we use water to break structures apart. Water, like think about the plasma in your blood. Water carries nutrients all around your body. So water is critically important. Right.  You can survive without vitamins and minerals for short periods of time. But water, we need a constant supply of water to keep us alive and healthy. And it's one of the simplest things we can do. You know, make sure you're getting enough water from a nutritional standpoint. Before you worry about anything else, make sure you're getting enough water. Right. Students will often reach out to me and say, is this good for me? Or should I try this or should I try that? Like you've got to make sure you're hitting the basics first. Okay. So what's the following facilitates the release of energy from carbs, fats and protein without actually providing energy? So we just talked about that. That would be the vitamins. So you're, I always think of your B vitamins. Right. They, and we'll cover this in the chapter on metabolism. But for example, riboflavin and niacin, two year B vitamins, they're need, they are actually what our electron carriers are built on that power the entire process of generating ATP. So if it weren't, if it weren't for vitamins, we could not generate the energy that our, that our cells need. All right. Case study. So calculate the energy available from a bean burrito with cheese. So I'll have, you know, pause this and do this yourself, but I'll, but I'll walk you through how you would do this. So you take 55 grams of carbohydrates, take that times the four calories that you'd find in every gram of carbs, 15 grams of protein, also take that times four. So because there's four calories per gram of protein, and then the 12 grams of fat, you would take that times nine. So 55 times four, 15 times four, and then 12 times nine. So let me, I'm actually going to quickly get the number because I'll need that for the next part. So 55 times four is 220 plus 60. So that's going to be 280 so far. And then 12, 12, oops. 12 times nine is 108 plus 280. So I think I got that right number, 388 calories there. But we need that for the next part. Determine the percentage of calories from each of the energy nutrients. And notice, notice how when I see K-cals, I just say calories. That's, that's calories of the capital C. So if you want to figure out the percent of calories you would take. So let's, so we got 388 calories as our total. Well, let's take that. I'll just do one of them. 108. So there's 108 calories from fat. And we divide that by the 388 calories that was total. And that would mean, so the number I get on my calculator is 0.278. So that would be 27.8% of the calories in this burrito come from fat. So make sure you can figure out that total and then make sure you can figure out the percent of calories from all three of these macronutrients. Okay. So you can, you can go through all that there, but make sure, you know, pause the video and make sure you can do that. The science of nutrition. So we won't spend a ton of time on here, but just understand that there's, there is a lot of science being done when it comes to nutrition. Nutrition is a science, but it's a very muddy science. And the problem is, you know, we're trying to figure out how we should eat to be healthy. Well, there are lots of issues with that. Number one, we have an amazing adaptive metabolism. Look at, there are people that are extremely healthy that eat high fiber diets. And then there are some people that eat carnivore diets and don't have any fiber and they seem to be okay. And I wouldn't recommend that, but there are people that eat really high carb diets and really high low carb diets and seem to be super healthy. So the problem is, the key is, you need to find out the best way you should eat, right, based on your genetics and your lifestyle. And so there is no perfect human diet. And so we're studying diets, trying to find a perfect human diet that I don't think really exists. The other big issue is, we're looking at how changes in our diet make us more or less healthy. The problem is, there are, we make millions of decisions in our lifetime that impact our health. And yes, diet is a big part of it.  You're not going to be healthy. And then someone else can have a diet that's not as good, but checks all those other boxes and they're doing great. So it's really, really difficult to determine if your diet is what's making you healthy or unhealthy. Let me give you another example. So years ago, studies used to show that people that ate vegan diets lived quite a bit longer than people that didn't. And I'm not saying anything against a vegan diet. We'll cover them more later. But what they basically found is it's called the healthy user bias. People that were vegetarian or vegans and took their diets really seriously, also made tons of other positive, healthy decisions. They're less likely to smoke, more likely to exercise, more likely to do things like meditation or other self-care practices, more likely to drink enough water, less likely to drink soda, right, these types of things. So they made hundreds of positive, healthy choices every day and yes, they were healthier. But studies have now compared healthy vegan diets to healthy diets that have animal products. Instead of comparing a healthy vegan diet to the standard American diet full of pizza and french fries, if you compare, let's say, the healthy vegan diet to a healthy paleo diet, which is based on food quality as well, the health disparities disappear. So it's very, very difficult to treat nutrition like other scientific fields. So, all right. So what we're learning a lot, we're learning a lot. I'm really fascinated by the research being done now using continuous glucose monitors. So they're studying people like constantly monitoring their blood sugar. But the main things that I've learned from those studies is how different we are. Right, you take two people that seem exactly the same. Give them both a cookie. One of them gets a huge blood sugar swing. Other one doesn't. But then you give them both ice cream and the opposite happens. Right, the person that whose body didn't seem to tolerate that cookie very well, when they consume the ice cream, they didn't see a big swing in their blood sugar. But the person that, you know, the other person had a major, major change. And then the other things we're learning is how much other factors play. Right, both of them, if they both have a cookie and one of them slept well and was managing their stress, the cookie's going to be less of an issue than the person that's sleep-deprived and stressed out and all these types of things. So it really is, the hard part about teaching a class like this is I can kind of give you these general ideas, these general rules to follow. You know, I think that making sure your diet is more nutrient dense is never going to hurt you. But I cannot tell you how to eat because we are all so different. Okay, so the scientific, using the scientific method for research, here's another big weakness in nutrition research. It's real easy to do a drug trial. Right, you do a randomized double-blind controlled trial where two groups of people, one's given a fake pill, one's given a real pill. Everything else about them is the same.  But nutrition just doesn't like that, right, because we eat so many times, we make lots of decisions. So a gold standard nutrition research study would be what's called a metabolic ward study where they would basically lock you in a metabolic ward and they would control everything you eat.  They would weigh your urine and fecal material. They would analyze every single thing. Studies like this are really expensive. So when they are done, they have to be pretty short and they have to only have a few people. Right, so it's easy to test a vaccine on tens of thousands of people. A metabolic ward study, you're only going to have a handful of people for a short period of time. So there are a lot of inherent weaknesses in nutrition research. But and that's why we need to kind of weigh the evidence, right? We have to understand that we don't have as good of this gold standard research for nutrition. So it's a part of the decision-making process when it comes to what we should eat and what we shouldn't eat. But it's not that gold standard like it is in some of their fields. Okay, so a control. What is a control? Looking at research studies, a control is a standard of comparison. If you want to see if adding dairy products makes someone more or less healthy, then you have a control where you don't change their diet and then you have the test group that you add dairy products to. I'm just thinking of an example. Placebo, so the reason you want controls is because you do want to see if there's a placebo effect. So a placebo effect would be if someone thinks they're getting treated or someone thinks something's going to make them healthier, to some extent it will. The opposite of that's called the no-cebo effect where if someone thinks something's going to cause a problem, it is more likely to. So if you and they do this, they do these kind of studies in nutrition research like they I saw a study recently where they had people ingest like oatmeal-like substance prior to working out that had carbs and had calories in it and they had a second group that had a control. It was like a sludgy mush that was similar to this oatmeal and similar in flavor and texture and everything else, but it didn't have calories. It used artificial sweeteners in it. So both groups thought they were getting breakfast. One was getting calories and one wasn't. And then they actually looked at the difference. And the placebo, the group that thought they were getting breakfast, did better than a group that didn't get breakfast. So the placebo effect does matter. All right, I mentioned the double blinds already. Actually, I didn't. A double blind would be so a blind that experiment means I don't know if I'm getting a real pill or a fake pill. A double blind means the person giving me the pill doesn't even know if it's a real pill or a fake pill. Someone else in the background knows. So everyone's blinded to minimize placebo effect, to minimize bias. So the scientific method, we make observations about the world. Basically, you identify a problem and you start asking questions. So then you formulate a hypothesis, which is an educated guess to what you think the answer to that question is going to be. Then we make predictions. I like to call these if then predictions. So if my hypothesis is true, then this is what we'd expect. And then we test it. And then you design the best study you can to test it. And when you analyze the results, you determine if your hypothesis was true. And if it was, like I said here, if your hypothesis supported, then you test it over and over and over again. You have other groups test it. And if they all come back to the same result, then the hypothesis can become a theory, which has a high probability of not being wrong. If you go and your results of your tests show that your hypothesis was incorrect, then you make new predictions, ask new questions, and you continue the scientific process. That's the process, right? So when you look at, when you ask someone a question about science, especially when it comes to nutrition, and if they say the answer is it depends or they say they're not sure, then they're being truthful. If they're certain about the answer, you need to be really careful because that's just not how science works. People should always be changing their minds as data changes and more information comes out. Different types of research, let's go through this pretty quickly, but epidemiological studies, so we're just observing people.  A cross-sectional study, you basically look backwards and say, okay, what these people have a disease, these people don't, what they do differently. That would be one example. Case control, you've got a group that did something and a group that didn't, and we look for differences. Cohort studies, you follow, so this would be prospective, you follow a group of people over time, and you see how the choices they make impact their health. So those would be some ways to observe people. The big problem with these types of studies is they are observational, and like I mentioned before, whether or not you eat carrots is a pretty small part of the picture of how healthy you're going to be. We've got genetics and environment and other factors. So it's really hard to determine how big of a deal eating carrots is, you know, just as an example. So observational studies can't answer questions, right? They basically tell us which questions to ask when we do real experimental studies. So that's really the best you can get with observational studies. Now, I still believe in them, and they are part of the evidence that we weigh, but we just have to be careful not to put too much stock in observational studies. All right, experimental studies. So lab-based studies that use animals. Lab-based studies in vitro, I believe it means in glass. So you think about like in Petri dishes, in test tubes, in cell cultures. So those would be some different lab-based studies we can do. And then human intervention trials. So I try not to put too much stock in anything until we get to human trials. I feel like the epidemiological studies and the animal and cell culture studies, they can really help us decide what type of studies to do in humans. But I want to know how diets impact humans. Not how diets impact rodents, right there. Rodents are similar to us and we can answer some questions there. But the human trial data is what we really, really need to get to before we can really truly answer a question. All right, analyzing research findings. Correlations only show association. So what they say there is correlation is not causation. I think there's an example here later on the PowerPoint but about how as ice cream consumption goes up, so do shark attacks. So there's a link between ice cream consumption and shark attacks. That's a correlation. There's no causation there. What do they both have in common? They happen during the summer when it's warm out, right? So that's a good example of correlation not equaling causation. All right, so that's why we have to be careful when we interpret nutritional research and we have to let it accumulate, right? If you show me 10 studies that say the same thing, I will put more stock in that than a single study that says something else. So we weigh the evidence basically. All right, publishing research, I'm just, you can read through this. It's not a huge deal at least for the level of class that I'm teaching. So you can just read through these here. But I would say this, you know, when you're looking at nutrition research, you always want to check the references, right? Make sure that the person that wrote the abstract, the person that did the study that they actually, the references they used actually make sense in the light of what they're saying. But all right, actually I mentioned this earlier. This would be the correlation. This is a correlation between shark attacks and ice cream consumption because when it's hot, you get in the ocean. When it's hot, you eat ice cream. That's basically what we're talking about there. All right, dietary reference intakes. So now we're getting to something else that's really important again. So the dietary reference intakes are the nutrient intake values for healthy people in the US and Canada. So you see here, we have several here. The EAR is the estimated average requirement. The RDA is the recommended dietary allowance. The adequate intake is the AI, or AI is the adequate intake. And the UL is the tolerable upper intake level. Then there are some calorie ones as well. All right, so let's look at these four individual examples coming up here.  The estimated average requirement is how much of a nutrient we need for 50% of the population to be healthy, which is way too low of a number. So the EAR's job is we use it to set the RDA. So if you look at your food packaging, you will see the RDA, the recommended dietary allowance. So the EAR is what we use to get to the RDA. So the RDA or the recommended dietary allowance is how much of a nutrient do we need to meet the needs of about 98% of the population, of healthy people. So the RDA is the floor. I look at the RDA as the floor. It's the bare minimum we need for most people to be healthy. So it's the minimum. It's not your goal. So make sure when you're looking at your food labels that you understand that. It is not your goal to reach the RDA. That is the bare minimum you need. You want to be somewhere between the RDA and the UL. So the EAR is just used to set the RDA. The RDA is our floor. So what's the ceiling? The UL, or tolerable upper intake level, is if you consume more than that, now you're risking toxicity. So if you consume less than the RDA, you're risking deficiency. Like if you're not consuming the RDA of vitamin C, you'll get scurvy. The UL, if you consume, like let's say calcium, if you're consuming way too much calcium, above the UL, or tolerable upper intake level, you can start to see calcification of your soft tissues. So if the RDA is the floor, the UL is the ceiling, we want to eat somewhere in the middle. So somewhere in the middle is optimal. The problem is we don't know exactly where it is. We just know it's between the RDA and the UL. But that's how we use those. So what is the AI, or adequate intake? This is going to be, it's like the RDA, but for things that we can't have an RDA. So let me explain. So like with vitamin C, we've studied it for decades and we know exactly how much vitamin C you need to reach the RDA and not be at risk of getting scurvy for a typical healthy person. But with some nutrients, we can't do that. One good example would be vitamin D. Vitamin D has an AI or an adequate intake. So if we can't prove what the RDA would be, then we have to make our best guesses. And that's what the adequate intake would be. It's like an RDA for something that you can't actually create the RDA.  Well, we all metabolize it differently, but the big thing is we get it from sunlight too. So where do you live? How much are you outside? Right? How many clothes do you wear when you're outside? All the, do you wear sunscreen? All these types of factors would impact how much vitamin D you make.  If you're a lifeguard and you're outside shirtless all day long, you probably don't need any of it. But if you're indoors and you don't see much artificial or sunlight and it's the middle of winter, you're going to need more of it. So that's why I can't tell you how much to consume. That's why it doesn't have an RDA. Vitamin K is another example because about half the vitamin K you get comes from the bacteria in your gut. So I don't know how much vitamin K your gut produces. So it's really hard for me to tell you exactly how much you should eat. All right, so we'll go through these. The estimated average requirement meets the needs of half the population. So again, not a valuable number. It's just useful to create the RDA. The tolerable upper intake level protects against toxicity, getting too much of something. The recommended dietary allowance or RDA meets the needs of 98% of the healthy population. So that healthy is a key word there. If you have some sort of GI problems, if you have some sort of gastrointestinal disease, you're going to need more. Or if you have any sort of condition that impacts your ability to digest and absorb nutrients, then you're going to need more than the RDA. The adequate intake is when there isn't enough evidence to establish the EAR and it's used instead of the RDA. We mentioned that. And the RDA will always be set above the EAR, which makes sense, because the EAR only meets the needs of half the population. And then another one of the DRIs is our EER, Estimated Energy Requirement. The average dietary energy intake to maintain energy balance is basically, so how many calories do you need to eat a day? Which you need to eat as many as you burn if you're trying to maintain your weight. So there's tons of ways to look online and try to figure out your energy requirement. But the only real way to do it for you, if you've seen these calculators online, they're all over the place, you need to eat a certain number of calories and basically know how many you're eating. If you're gaining weight, you're eating too many. If you're losing weight, you're eating too few unless you want to, of course. If you're maintaining weight, you're eating the right amount. So really, that's how you determine your energy requirement. I go to a lab and I get my rested energy expenditure tested. You can do that. But that still only tells me how many calories I burn at rest. It doesn't tell me how many calories I burn. My total daily energy expenditure would be a different number. So you use the online calculators to get in the right ballpark, but then you have to change it up and down. If you're gaining weight, you're eating too much. If you're losing weight, you're eating too little. If your goal is to maintain weight, that's your estimated energy requirement. All right. So now we have the last DRI is the Acceptable Macronutrient Distribution Range, or AMDR. This is what the government recommends as far as the macronutrient breakdown of your diet. So you'll see here, looking if you match these, that the AMDR for carbohydrates is 45 to 65% of your energy expenditure. The AMDR for protein then would be 10 to 35% of your calories, and the AMDR for fat would be 25 to 35% of your calories. So a lot of people think that's a high number for fat, but that is the AMDR. Obviously, there's going to be a lot of variation here.  There are people that, and I'm not saying everyone needs to eat this way. I certainly don't. I eat a lower carb diet. I don't eat, I'm not on a ketogenic diet or anything, but I'm on the lower end when it comes to carbohydrates for sure. So I eat a diet that's lower carb, moderate protein, and then moderate to fat. And I actually like a lot of protein as well. But so everyone's different, but this would be the government recommendations that you start here. So just like with the calories, I think this is a great place to start, and then you play with it and see what diet works best for you. Okay. How do we use these recommendations? I mean, like I said, they're just, they're a great jumping off point, but you've got to figure out what works for you. So here you see three different examples. You see someone that, on the far left, they're eating a lot. This would be like maybe an endurance athlete. So they're getting a lot more carbohydrate calories because they need to fuel their training. Whereas someone in the middle, you see they're on a more of a high protein diet. And then on the right, you got more of a, kind of a moderate diet throughout, but all three of these people would satisfy those AMDRs. So assessment. A couple of terms here that are important. And I'm not, you know, this is an introductory course, so I'm not going to spend a ton of time here, but there are some terms you need to understand. Malnutrition, I think it's really important we talk about this because when I say malnutrition, you probably think of someone that's starving or has some sort of deficiency disease. And that can be true, but let me read the definition. Caused by excess or deficient food energy or nutrient intake or by an imbalance of nutrients. So if you're eating too many calories or too much sugar or too much of a nutrient, you're malnourished, right? Or malnutrition, sorry. So malnutrition is either an excess or a deficiency. So under nutrition is deficient energy or nutrients and over nutrition is excess energy or nutrients. This would be most people on the standard American diet are both. So we eat a diet where we were getting too few vitamins, too few minerals, maybe too little fiber, but then we're getting, that's under nutrition. And then over nutrition, too many calories, too much sugar, too much saturated fat, etc. So most people are experiencing both at the same time, which is clearly not a good thing. All right, so what are some symptoms of severe malnutrition? You see here, GI problems, these types of things. That would be the situation where someone would have to evaluate that and figure out what's going on. But so what kind of nutrition assessments will we see here? So first, if you see historical information, so this, you know, health histories, socioeconomic status, drug use, kind of like an intake you'd see at the doctor's office, certainly can help. If you find out that someone is an alcoholic, for example, you would look for certain things when it comes to malnutrition. Diet history, I think diet record or diet diaries a great tool. So you see here, measures of the intake over several days. Sometimes you have people use like things like my fitness pal or chronometer. Sometimes you have them take pictures of everything they eat. Then you can, or you can just do a diet record where someone writes down everything they eat. A gold standard diet record would be seven days, basically three to seven days, but seven days would be ideal. If you're going to do a three day diet diary, I recommend at least one of those days be a weekend day. So you can get like, cause a lot of people eat a lot differently during the week than they do on the weekends. But really the longer a diet diary, the better. Those certainly work better than just asking someone generally what they eat, right?  Anthropymetric measurements, things like height, and weight. That'll be how you determine a BMI, for example, which we'll cover later. Waste circumference is going to be really, a really big deal. So those are the some measurements you can use. Physical exam, looking for signs of problems, like signs of deficiencies, nutrient deficiencies, or signs of toxicities, and lab tests, right? If you want to know how, what someone, if someone needs to consume more vitamin D, the simplest thing to do is to test their blood levels of vitamin D and see if they're normal or not. All right. So you can read through this. Again, this is a pretty small part of what we're going to be covering here. But, if you do a diet history and a health history, you run some lab tests and you examine a patient, then you can learn an awful lot about the nutritional status. Okay. What type of deficiency is caused by something other than an inadequate intake? So it's a primary deficiency is when you're not consuming enough of something. A secondary deficiency is when you're consuming enough of it, but it's not being properly digested, absorbed, or stored, etc. So that would be so a secondary deficiency. Okay. Nutrition assessment of populations, we have our national nutritional surveys that, you know, the like NHANES would be an example here.  No offense.  So when we take, when we survey people and ask them how much block of the eat, they're generally going to say they eat more block than they actually do. When you survey people and ask them, so does they drink, they're generally going to say they drink less than they do. Things like that. Like just as an example of how kind of inaccurate these surveys can be, if you believe this information, we can only account for half of the alcohol that's purchased in the United States. So, so either half of it's being poured down the drain or people are, I'm not saying people are lying, but they're not really good at remembering or tracking. One study even showed registered dietitians were 10% off when they, when they, when they, when they were surveyed as far as what they actually consumed versus what they thought they consumed. So if a professional has problems, then of course the rest of us will as well. People that are overweight generally are going to underestimate their food intake more than people that are not. And same thing with physical activity. People underestimate how much they eat. They overestimate how physically active they are. So there's, so this, this stuff is important. I'll take any evidence I can get, any data I can get, but we have to remember that. All right. The Healthy People Program is just its initiatives to try to get people to consume more fruits and vegetables and these types of things. It's all, all good. All right. So how important is your diet to staying healthy? Right. It's obviously, if you look at the big ones, sleep, water, stress reduction, physical activity and exercise and diet though, if you do those things that's like, besides genetics, right? That's like 95, 99% of what's going to impact how healthy you are. So here you see the leading causes of death in the United States. We have the first two, heart disease and cancer.  So if you, I always say your goal should be to die of nothing, right?  And some of these, you know, diet has a huge impact on heart disease risk and cancer risk and blood pressure and diabetes, all these types of things. So diet plays a huge, huge role. Okay. So risk factors for chronic disease is, you know, obviously we just mentioned them. Do you smoke or not? Are you overweight or obese or not? Your diet and physical activity, those are the big ones. Despite evidence linking certain behaviors with chronic diseases, many Americans continue to engage in unhealthy behaviors. What can you do as a student to improve health behaviors? This is what, you know, we mentioned, we just said these things. We know this, right? We, now knowing something and doing something are two different things, right? We absolutely know we shouldn't smoke. We know we should be more physically active. We know we should exercise. We know we should try to control our body weight. And, you know, we should sleep, all these kinds of things. So I don't know. You just got to want it, right? And, you know, I said I've actually lost 150 pounds. And I know that, you know, that I had to make changes. I didn't smoke, but I had to make changes in every other facet of my life in order to do that. And I'm so happy that I did. And now it's just part of my new life. There's no going back. But it wasn't easy in the beginning, right? So you have to be motivated. You have to want it. And then over time, your motivation is going to wane and you have to be disciplined. And you got to stick with it until your new life becomes the habit that you fall back to. So feel free to ask questions about that. I love talking about it. But it just shows you that the psychology and behavior change are critically important when it comes to diet and lifestyle. Okay. So we're done with our first chapter here together. So you can, you know, hopefully you've learned a little bit about all these types of things. And this is awesome. So I will, I will do one of these videos for every chapter. And then I plan on doing a whole bunch of shorter little topical videos as well like I normally do. But I'm really excited about this to help you learn. All right. So you reach out if you need anything. Have a wonderful day. Be blessed.


Hi guys, welcome to this channel. This makes for the next creation. If it's your first time come across this channel, please consider supporting this channel by subscribing to this channel and also don't forget to hit that notification bell. You remember we are looking at the road to 3000 subscribers. In today's video, we are going to talk about security guards and the social media. It is something that is coming a little bit very serious. This is the gap. For example, people who are in Qatar here. Remember, everyone is eye or everyone, all eyes on the FIFA World Cup. There are very many people around to watch over whatever you are doing. You may be a security guard. I think most of this goes to what you call the security guards.  You might have a platform for yourself. You might have a Facebook account. You might have what you call a TikTok account. You might have a Instagram account. Or you might have that platform that definitely is on the other side of you, not on the side of the work. But what is being done wrongly with most of the security guards or some of the security guards here in Qatar is taking TikTok or social media. You post videos. You're doing lives on social media and you are in what you call a company uniform. Remember, there is a clause in the company whereby the company has a right to do whatever it says. Once you get to bleach what you call, you bleach the contract. You bleach the rules of the contract. Most of people are falling in what you call trouble. I think it is a scope of what it is. It is something that is being taken off right now for people in uniform and their own social media. To some companies, it's domination. That's what I have to let you know. To some companies, most of our friends are being terminated. People have gone back home. People have been fined.  Yes, much of the time. Why? Sometime it's very important to use that opportunity that is given to you right. How to use it? How do you use that opportunity by doing the right thing at the right place at the right time? Yes, no one is refusing you to use your social media account or do your social media work. But how do you do it? What time do you do that social media work? It's very important. And where are you doing that social media work?  Very many people are watching over you. Very many people are watching right now. And what is going to portray or what are people going to say when you are putting on uniform. So, I call about security guards or people, if you work in the security department, it may not be security government. Even some of these companies, even some of these companies, if you're in uniform, you should infringe yourself, posting, getting live on this social media, posting your photos, updating yourself all the time on social media. What does it mean to that employer? Or what does it mean to that person who gave you the job? It means you are not doing the work. You are not interested in whatever. You are not interested in the job. That is why you are on social media during the working hours. What is the humble hard advice? My humble advice is that do the separate work away from what you call the uniform work. Attend your social media work out when you are off your duty. Don't do that work during the course of the work because you never know who is at the back of you. You never know who is at the side of you. Who is watching whatever you do. Remember, something that I need to let you or something that you need to understand for example in Kata. Security words is not only the security guards or the security departments that are there. We have CCTV cameras. We have CCTV cameras all over some of these places they have cameras. You definitely know you are aware of these cameras. But again, know the code of conduct when you are putting on this company uniform. It is not your uniform. You are representing that company. It represents the company. What about the person that is watching? What about the person that is seeing you? Duty time and uniform. You are making videos. You are making TikTok videos.   What does he mean to that person? Let's say for example this is a client that you don't know because you also like other people. They do their personal work away from the uniform. But what is this person going to get out of you? What is this person going to say about you? He will definitely commit about you and say the security guard does not do his job or he is not doing his work because he wants to retire. He is on social media. He is on live social media. He is posting videos on social media. He is posting himself or he is doing live videos on social media in uniform. So there is no words that you are going to explain. There is no other words that you are going to explain. And some of these companies are not going to tolerate this in one or the other. Remember most of these companies have recruited extra people, extra manpower. So losing one person out of the manpower they have is not going to be a problem because they also need to protect their name. They need to protect their good name in one or the other. So this is my humble advice. Yes, most of us or all of you do work but do your work away from uniform. You can do during your free time. You can do during your time but not in uniform. Hope I have tried to share something for you. Thank you so much for coming back to Sian and thank you so much for supporting this Sian. This makes from the next question. See you again in another video.


So much so my channel's filled with tips, tricks, hacks and anything you could ever need to know about volleyball. So today I'm doing something really cool that I've always wanted to do. I am going to write out my vision board and with the new year every single year we set goals and intentions and one of my goals and intentions this year is to be a little bit more intentional about my goals. So let's get right into it. So here I have all of my different Sharpies and Markers and I have my vision board so you're going to see me doing a different point of view and you're going to see me writing out my goals on this vision board so let's go. So with my vision board, I'm sorry my tripod legs are in the frame but in my vision board I really want to be more intentional about my goals. So one of the ways that I can be more intentional about my goals is I'm going to first write, I'm going to first put out Cocos and then I'm going to do 20, 21 and then goals. So I'm going to lose my little metallic pen because it's golden. I'm just going to decorate a bit. Alright so now that I've decorated the front of my page I have Cocos 2021 goals and these are my goals. So right now I decorated it because I wanted to be reflective of the excitement that I have going on for this year and I chose this yellow paper when a lot of other people choose a white paper. I chose this yellow paper because I'm really looking up this year and I want this year to be sunshiny and happy and so that's why I chose this yellow paper and this paper was really cheap. It was only about 50 cents so I got right now what I'm going to do is instead of just writing a whole bunch of different things and there's so many ways you can do a vision board. You can do it by cutting out things in a magazine and posting it by writing out your goals. You can journal. There's a lot of different ways but what I'm going to do is I'm going to divide my into different sections like different areas of my life and my goal for that area. So of course you guys all come from the area that is volleyball so I'm going to do volleyball first. So we all know that this year has been quite different. It's been a lot different for all of us. However I wanted to set some volleyball goals for this upcoming year because I'm really excited about what's the potential for this year. So my number one goal for volleyball this year is to train for grass volleyball. In the adult community grass volleyball is so very popular and it's something that I didn't really do until quarantine. I did one tournament last year that you guys saw but during quarantine I had a lot of different times where I was playing grass volleyball with my small, small quarantine group where I had the chance to get better at grass volleyball and really learn more about the rules and the regulations because I really didn't know much about it but it also really helped my ball control because as you guys know I'm working on my passing. I've been working on my passing for the last two years and I think that playing grass volleyball really did help a lot. So that is one of my largest goals for this year is to get better at grass volleyball and that goes into my next goal. One of my next goals is to go to the Pottstown Rumble. Now a lot of you guys, you guys are in high school, you're in middle school and you don't really know about the Pottstown Rumble. I don't plan to go into 2021 but maybe 2022. The Pottstown Rumble is a huge, huge adult volleyball. Well they have youth volleyball too but adult volleyball tournament in which people all over the US and sometimes the world come together to compete in this three day tournament. They have some of the greatest grass volleyball players ever coming to this tournament. They have some professional players that come to this tournament. This tournament is really, really, really a way to show your volleyball skills, show what you know and it's a great way for you to be able to meet other volleyball players and it's sponsored by a ton of people. I used to live in Pennsylvania if you guys have been around that long and when I was in Pennsylvania that is when I really learned about this tournament. It's a great way for us to learn more about it and it's such great gameplay. So I'm really hoping that 2021 I can go to this tournament, find a grass partner. If you're a player and you want to be my partner, let me know because I'm looking for a grass partner. So that way I then too can play at this tournament. As you can see these swings are killer. That is one of my goals for this upcoming year is to look into it and train for it possibly. Another one of my volleyball goals for this year is I really want to be able to work on being brave and what I mean being brave.  So being brave and playing sand. I also want to work on making sure my serve receive is better. I've been trying to work on passing for a long time but serve receive sometimes can be intimidating. So I want to work on serve receive so that way I can become better player and that way I can also work on my jump serve too. So there's some things that I really want to work on this year volleyball wise but there's some other things that I want to work on life wise too. So let's review my volleyball goals for this year. So at the top is to train for grass volleyball and the ways that I can do that is conditioning, making sure that I play grass volleyball and get out there and you know, take the chance. Half of the battle is just going out there and doing it.  Number two is look into the Pottetown Rumble. We just talked about the Pottetown Rumble, how big of a deal it is and by training for grass volleyball in 2022, I can be ready for the Pottetown Rumble. I got to find a partner first. Be brave and play sand. I've played sand a couple of times in my life but I want to be able to play sand with confidence. I want to be able to go out there and enjoy myself and part of that comes into these other goals but playing sand is something I've always wanted to be able to do and in order for me to do that, I have to be confident. Work on serve receive. As you guys know, I'm not a passer by trade. That is not my position. I'm an outside hitter, middle hitter which means that I traditionally played in the front row. Passing is not my strength. However, in the last couple of years, I've worked really hard for it to be my strength but I still want to continue to work on serve receive especially when I'm playing on open level tournaments and there's a lot of jump serves that are coming into play. Finally, dominate jump serves. I've finally got the jump float. I got the float serve, a lot of different types of serves but I always wanted to know how to jump. In order for me to know how to jump, I have to practice. So making sure that I take all of these this year into this intention and I don't have to just do them all in January and just binge them quickly but I want to make sure to take the time to actually acknowledge all of these goals and then be goals that I really am passionate about and then I care about, okay? My next set of goals that I'm gonna talk to you guys about is my YouTube goals. So YouTube is another part of my life that's really, really important so I'm gonna shift this over a little bit to YouTube goals and I don't have a red marker but I can use this pink marker to kind of draw the YouTube symbol. If I'm that talented, if I'm ever so talented, let's see, it's working out. YouTube, so my YouTube goals. So for YouTube, oh, I forgot my little squiggly line. Let's draw the squiggly line. All right, for my YouTube goals. Now last year, I really hit a lot of my goals. Let me move you guys over. Last year, I hit a ton of my goals when I hit 100,000 subscribers. I am so ever grateful that I was able to do that. I am so happy that I was able to do that and impact so many of you guys through YouTube but for my YouTube goals this year, I would like, let's see, Rufus, it's okay. I would like to meet more of you guys. I wanna meet more of you guys. That means that whether that's me doing meet and greets, whether that's me doing more live streams, interacting with you all, that's what I would like to do is to meet more of you guys.  Secondly, what I would like to do is I would really like to, a lot of things going on with COVID and all of that stuff, it's been tough to do that but tutorials are what really brought a lot of you guys to my channel in the first place so I want to upload more tutorials so that way I can help you guys on your volleyball journey and more stuff like that. My third goal is to make more merch. Make more merch. I want to make more merchandise that you guys can actually use on your volleyball journey and something that is gonna be good for you that you can use and you can target, it can help you. That's what I would like to do for this is make more merch and then of course, I gotta talk about it. I want this year to get 175K subs this year. I want to impact more of you guys and get more subscribers to impact more of you guys and grow on our volleyball journeys and by getting 175K, oh my God, that would be so totally awesome and it would be a great way for me to meet you guys, to interact, get more volleyball players and all of that so that is my YouTube goal for this year but with everything, you do have to have some goals that are life goals. So I'm gonna put my life goals in the top corner up here by my name so let's move us over. So let's move us over a little bit. So, as you guys recently just knew, I did get engaged so as you can see by this ring, I did get engaged so I'm going to put my life goals, right? Let's see, okay, for my life goals, for number one, definitely, definitely number one, travel. 100% number one. Year number one, I'm gonna help SpongeBob. Travel is my number one. I love traveling, I wanna travel more this year. That is a big goal of my travel. Number two, I wanna listen more. That means I wanna take more time to listen to others, be intentional about listening to others because you know how sometimes people listen to others but then they're thinking about what they're gonna say first. Now, I wanna listen more. I also want to budget better. I know this is kind of an adult topic but some of you guys, money is important so you guys have to learn how to budget. And then lastly, I want to be mindful that means being in the present, accepting being in the present and also I wanna read more books, a big book reader. Read more. Whether that's book, audio, book, newspaper, clickings, peer review, articles, journals, textbooks, all the, oh my gosh, I forgot, Lord have mercy, the biggest goal of the act, graduate, graduate. Yeah, let me see if I can draw a cap and gown. I'm probably gonna butcher this. Not an artist, but anybody can be an artist so I'm trying. Let's get this yellow tassel for my graduate, graduate, that's what I want, graduate. I'm getting my masses right now so I would like to graduate. So I probably will add more things to this later but let's take a look at all of the goals that we have on my vision board so far. So we have so many different sections. We have life, we have YouTube, we have volleyball. I probably will add more sections here later on but I really wanted to make this video so you guys can see how to set your vision board. There's so many ways to do it, there's no perfect way but I wanted you to see me how I did my vision board this year and Coco's 2021 goals. And yeah, so I'm gonna keep this and I'm gonna look at it back when I need to remind myself that what I set for myself this year so I can make sure I'm on track. It's a great way to do that. If you guys watch other vision board videos make sure you look at some of the ideas for some of the things that people are out to use. I hope you like this video but let's go back and I hope you like this video. I hope that these goals kind of inspired you to see something that you may like and please like, comment, subscribe and I will see you guys next time.


So I'm really excited to be with you all. This is my, not only the first data science day, it's my first data science day. So I'm really pleased to be invited and included in this lineup of my colleagues sharing today. So my focus is gonna be on learning analytics and I'm a former librarian, although you never really turn in your library card, so to speak. So I consider myself a librarian, although I've been at the iSchool for about 15 years and that's where my practice and research and teaching is all embedded. So I'm gonna be talking about learning analytics, but from the perspective of libraries. So I hope that those of you who aren't library folks will also find something useful in this talk as well. And just in case, I'm gonna share the slides, if you wanna follow along on a separate screen or if you need a screen reader or something like that, that's the link to the slides. So here we go, let's get to it. We only have a half hour to talk about this great topic. So as you're going through the talk, I would invite you to add questions. Jay's gonna be monitoring it for me in the chat, but I also thought I'd give you all a few questions to think about as well. And these are some of the ones you might wanna be thinking about, particularly if you are library focused. So you might be thinking about to what degree should librarians be involved in learning analytics, what data might libraries have to contribute to understand student learning and success in an academic context, what ethical decisions and there are many need to be made with regard to this work. If we got data back from this process, what kinds of decisions and actions could we make and take and what conflicts might arise as we go into this territory. I wanna acknowledge also that what I'm about to share with you came from two, well, few other places, but primarily from two IMLS funded grants that we had at the school. I was lucky enough to spearhead these, but each of them involved many, many other individuals. The first is library integration in institutional learning analytics or LEVA. And the second one is class connecting libraries and learning analytics for student success. And I want to drop in to chat the links to those projects. There we go. In case you wanna explore those as well, I'm gonna allude to them a few times in the next 30 minutes. And at each of those links, there's more than you might wanna know, but also some useful content about each of these projects, including who was involved, what was accomplished and greater explication of some of the things I'm just gonna be able to nod at today. So I just wanted to make that acknowledgement and also acknowledge my gratitude to IMLS for funding these projects. So let's start with a common definition of what learning analytics are, specific to academic libraries in higher education, which is where my focus is. So learning analytics in higher education has been defined many different ways for I think a good working definition for our next few minutes together tonight is this. The use of institutional level systems that collect individual level student learning data, centralize it in a record store and serve as a united source for research seeking to understand and support student learning and success. The term learning analytics gets used differently in libraries sometimes than this definition. So I wanted to be clear about where I'm coming from for this talk. To give you sort of a really oversimplified map of what that might look like, I present you with this beautiful diagram in soft colors, so as not to be overwhelming. So the idea here is that with learning analytics in higher ed, the data comes from many, many different places, including student information systems, operations data, learning management systems, iPass data, we'll talk about iPass systems in a moment and all kinds of other data coming from different parts of campus. All of that data then is consolidated in an institutional record store or data repository. It can go by a lot of different words, data lake, data puddle, data stream and in one place in the institution where it is or should be protected by policies, procedures, practices, governance, personnel, chief privacy officers, technical security and whatnot. The purpose of bringing it all together is analysis so that educational researchers can run queries and correlations based on research questions or user stories to seek to understand the student's experience. Of course, we don't set it and forget it. This kind of data needs to be continually assessed for bias and error as we try to use this data to understand what helps students be more successful and what might get in the way of their success. The folks who would then be able to view this data perhaps in its native form or more likely in dashboards would be on the right-hand side. Students, faculty, institutional folks broadly across the campus and advisors. And I've alluded to in those boxes why they might need to know that, right? So faculty need to be able to improve their courses and the curriculum overall. The uninstitution should be able to understand what's getting in students' way and dismantle those hurdles, not just for individuals but for large swaths of students, advisors, and students, most importantly, by getting their own data back can start to use that data to make decisions, be more empowered, have more agency over their learning journeys. You'll notice that there are these elements on this diagram that are not the same color as everything else. So there's library data is sort of in a navy blue color and so is the word librarians. And that is because for the most part, generally speaking, library data is not included in institutional learning analytics in institutions of higher education in this country at least. And librarians are often not privy to what the results of the data analysis is even though they would be natural partners in implementing good decisions that come out of the data. I said that I would explain in a moment what an I-PASS system is. This is sort of a flavor of learning analytics that many campuses have rolled out including our own for undergraduates. And these sort of solutions are generally referred to as I-PASS systems, integrated planning and advising for student success. The idea of an I-PASS system is to do some of the things I just talked about to bring together information about students in order to connect students, faculty, advisors and others in many cases librarians, but not usually, more and more so, yes, though. To sort of unite that educational team around students and their journey towards success, give students back information about their pathways and decision points and things that they might be able to reach out to or take advantage of. And ideally this is supposed to happen in close to real time because in a student success journey even a week can be too long. So trying to get sort of slow, higher data speed it up so that people can make decisions on it. There's lots of different companies that have waited into this space and some institutions also have their own homegrown version. So this isn't exactly learning analytics but it is definitely a flavor of it that has a lot in common. So I wanted to include these systems as well in our definition. So overall, like what's the point of all of this? The point of learning analytics is to help educators discover, diagnose and predict challenges to learning and learner success so that we can do something about that, right? Or maybe the decision is inaction but typically an action would be the result of our learning. And this is really important for us to understand better the student experience and also for students to be able to understand the landscape, especially those that don't have another way of interpreting the environment they find themselves in because maybe they're first in family or maybe other challenges are presenting themselves and they have to do a lots of things at one time. And so any assistance and pointers and suggestions that they can come to either on their own by looking at their data or be connected to in a more direct means should be useful. So on that screen it says deploy active interventions to benefit students and interventions is a horrible word. Like it sounds like something you would not want to be a part of. It sounds like, I don't know like surgery or something but what is an intervention in this context? So there's really macro level interventions and individual level interventions. So on a broad large scale level, we're talking about systemic and structural changes to higher education practices, processes, policies so that the learner experience can be improved and obstacles that we inadvertently set in students' ways or maybe inadvertently, I don't know that would be bad but it might be the case can be removed, right? To dismantle and get rid of those obstacles. Also on an individual student level we can facilitate communication. So allowing learners to see their own data and see how their learning behaviors line up with their intended trajectory or what their peers are doing or you can imagine many different ways to present that information. To notify students and their educational partners of important events or milestones. To make connections when students need or want to seek some sort of service or resource on campus but either maybe don't know what exists or don't know how to reach out to that service or resource and otherwise link students with things that they have a right to participate in because they're a member of the community but they might not otherwise know about. In library land and academic libraries, the term analytics as I alluded to earlier does not always mean these things and sometimes the term learning analytics gets used to mean general information literacy assessment, a one-off or episodic correlation study between some sort of library engagement and some sort of metric of success and it's also not primarily about proving that libraries are valuable although sometimes that is a side effect and lots of folks who have to make administrative decisions are interested in to what degree the library is helpful and impactful and how we can do more of that but that's not what it's primarily about. It's about improving that learner experience. So it's important to remember in the context of libraries that learning analytics is only one approach to understanding the student experience. We have always used surveys, focus groups, interviews, ethnographic approaches and lots of other strategies and tools for understanding the student experience but all of those tools have gaps as does learning analytics. And so taken together, used in conjunction we can better understand what's going on but learning analytics is not a panacea and does not necessarily replace the strengths of those other approaches. It can, however, give us an idea of where to apply those other approaches. So focus groups, surveys, interviews are all labor intensive not only for the librarians and other professional staff that will put them together but also for students to participate in them. And so learning analytics might give us a way to understand the environment and know where to apply those sort of in a basic way and then learn where we would want to apply those sort of more why and deep searching types of strategies to delve deeper. We think there's a problem here or there's an unexpected success here, let's find out more then we'll use our other approaches to do that but learning analytics can give us a scan of the situation. And it also is, as I've tried to emphasize a few times primarily about understanding and supporting and improving students' experiences. Okay, so what can this help us do in libraries if we engage in this work? Well, this is where I'm gonna point to those links that I gave you at the outset because what can we do with this is a voluminous piece of thought and communication in and of itself. So I'm just gonna point to a few things in those reports for those of you who are interested in going further. First of all, learning analytics can help us answer a great number of research questions or action research questions that librarians have long had about student learning and success, what libraries can do to support that, what we might be doing that does not support that so we could stop doing it. We could also use the data to take action including instituting better communications with students, improving library collections and services and facilities based on what we find, making better instructional decisions because librarians teach all the time and just better implementing our decisions based on data rather than anecdote or perhaps partial information that we might get from our other traditional approaches. I also think it's really important that this work could integrate librarians into the larger institutional picture. If you are a librarian in an academic context, that's always a goal is to be part of the campus and to be fully integrated into the life of the campus. And so this is another way that librarians can do that. And certainly when the results of larger learning analytics processes and projects come out, the librarians are key people to help implement change because of their connection because of their third safe space on campus. And so there's lots of benefits that librarians can bring to this work overall. And finally, if you like user stories, there's more, almost a hundred in the Lila report of ways that the researchers on that project and the librarians and learning analytics experts that helped with that project could imagine that this kind of work could help students, librarians, advisors, faculty, institutional researchers and institutional leaders and administrators do their work better with this information. But I don't have time to go into all of that tonight or you'd have to hang out with me quite a bit longer. Now, there are tricky spots in this work and I wanted to highlight those as well. Libraries have long valued privacy, user privacy. We still do. And so the idea of collecting individual level data is fraught. That's probably like understating it, but it's a complicated space that I think is unique in some ways. And we have conversations around the privacy of data that I think other professional spheres don't have the same kinds of conversations. So I, again, I can't go into all of those in depth, but I did wanna at least acknowledge those tricky spaces where the terrain is difficult around this work. The first one is misconceptions about learning analytics and we sort of have alluded to that with the misunderstandings of what it even is and what we can do with it. But certainly the privacy issues are another tricky area and understanding the difference between maintaining data at all or getting rid of it as quickly as possible, understanding where residual data lives in our libraries through connections with the supplier community, the vendor community, thinking about what data we would never want to have because someone might come and ask us for it. And librarians hold sacred the responsibility of having information about what people are reading and not sharing that. So thinking through all of those contexts, how do we keep information that is sensitive, confidential, only keep what we need to use them to understand important research questions and how do we make sure that other data is not kept? And so the, let's keep it all and see what it will reveal is not really aligned with the ethos of librarianship. So we have a lot of conversations around that in this space. There's also the sort of notion of knowing more about our students. Actually, you know what, I think I have slides for this. Yes, I do, there we go. So for a long time, librarians have worked without detailed information about their users across the board, including in academic contexts. But we also need to think about the opportunity to have more detailed information about students and what we might be able to do with that information that would be helpful to students. So we might be able to take action and make decisions with them, with students and on behalf of students, if we had more information rather than knowing almost nothing and being left to assumptions or partial information to make decisions on. So the other side of that is also when you know more that also puts a guess a weight, an obligation, a responsibility to do something with it. If you know that there's a problem and you do nothing about it, that is a different space than if you had no idea there was even a problem. So knowing brings more responsibility and we have to as a profession wrestle with that and think about how that changes, how we might do practice. In library spheres, one of the main outputs we hope of interaction with the library is learning. And learning analytics gives us an opportunity not to just look at how persistent or quickly students move through their educational program to completion, but also what are they learning along the way? And so up until this point, we've sort of in libraries tried to correlate, what are we doing in libraries with our students persisting through their program? Do they complete their programs or degrees? And that's really, are they getting the grades? All of those metrics are sort of large grain. They don't get into the details of what was actually learned. And so learning analytics presents us an opportunity to get more into that space. I think one of the things that's most motivating about this work is the opportunity to understand our students better instead of looking at student data as monolithic or having very rudimentary understanding of how different aspects of students' identities influence their success and their strategies for success in higher education and in libraries specifically. This gives us an opportunity to be more knowledgeable about how different aspects of student identities make a difference, right? So not just race and gender, but degree program, major, what year, what else is going on in their curricular life and so on. And how does all of that make a difference on what can we do to sort of take a more nuanced view of students rather than just let's design for average. Let's just throw all the numbers together and aggregate it all and make our best guess about the average. Well, there's no such thing as an average student. And so that puts us in a poor position with regard to making advancements in equity and inclusion. I mentioned the labor involved in understanding the student experience. Also, we have an issue about labor and equity with regard to different kinds of institutions. A big institution like Syracuse might be able to do some of this work. A smaller institution like a smaller liberal arts college or a community college might not have the staff to be able to do this kind of work on one-off episodes. So having a system that will help them gives an opportunity for all to learn this, the detail that we can get from learning analytics. Lots of tricky places about who makes the decisions about data. Right now, the vendor community makes a lot of those decisions maybe institutional leaders to some degree, but mostly library vendors. And if we wanna have ownership in the library and with students that we would need to negotiate that territory, this is sort of the same content. A little bit different, but mostly the same. And then, so all of those are about sort of should we do this work? This last one is about how could we do this work? And one of the things that if you're in a library, you know about libraries is that there are many, many different systems operating at any one time. They spit out data in totally different formats and bringing those together and formatting them in a standard way is, I mean, it doesn't happen, right? So if you try to take library data as it is now and ingest it into a learning record store, it could just be spaghetti, right? Just formatted differently, a mess to try to deal with and normalize. But the second project I talked about and also you have the link in the chat is the class project. And that project resulted in an interoperability standard. It takes care of this problem. I won't go into a bunch of detail because we don't have a lot of time, but Caliper is the name of the interoperability standard. It's a common interoperability standard across educational technologies. You can see the list here on the right, we are the newest profile in their standard. It's a JSON triple, basically with an actor, action and object. And for the library profile, there's three actions, library use, which is designed for spaces. Library resource use, which is designed for collections and use of materials, whether that's physical materials or digital materials in the library and participation. So asking a reference question, attending an exhibit or an instruction session. And it looks like this. In real life, this is a simple Caliper packet. This is a more complicated one. This first one doesn't identify the user, privacy issues, the second one does. So, and it also says what course the person is reading this journal for. So the standard is agnostic in terms of how much data you put in that's a design decision by an individual library organization in collaboration, I would imagine, with their institution. Okay, so if you are involved in education or in libraries, what are some of the things you can do in this space? Well, you can think about what this might look like at your library and at your institution. Think about what research questions you would want to answer. Think about how this fits into your current strategic plan, what you would need to do in terms of educating your colleagues and your staff and how you would act in this new space that's coming. It's coming. And just sort of in terms of a general action plan, you could think about, what questions do I want to ask or answer? What policies or procedures would we need to get ready for this kind of work? What kind of data is okay to include in this kind of work and what would we never want to include or record in any way? And who also do we need to bring into the conversation and clearly at the top of that list would be students because it is their data. Learning analytics isn't new in higher education. It's been around for at least a decade, but it isn't going away either. So this year's EducAWS Horizon Report, which is a major report that comes out of the educational technology and IT realm in academia has listed learning analytics again as a key technology in practice. This has been true for, since at least, I'm going to say, 2011. This year, the section on learning analytics included, and this is the screenshot of the first page of the learning analytics section, our project here at Syracuse, the IMLS funded project on the very first page. We got a shout out, which was great. They did a lot of analysis and asking people about their opinions about learning analytics. You can see that it ranked highly in terms of addressing equity and inclusion, an important aspect that we've only alluded to tonight. And really this work is increasing in importance. Post pandemic, we know for a long time that online learning is increasing, but it's increasing even more quickly now. In the past, libraries have really relied on proximity dependent approaches, and we can no longer really trust that that will get us what we need because we do have that increased student learning, but also there's populations of students that have always been sort of invisible to those approaches. So if you're going to do a focus group with students who come into the library, you never hear from students who aren't in the library and so on. So this is a growing area, despite all those tricky places that we have to figure out. This is a list which I won't share each individual one, but this is a list of what happens if libraries don't pursue in some way involvement in learning analytics, whether it's with library data or just participating in the larger workings of learning analytics at their institutions. I've alluded to some of these, the danger in designing for average and leaving folks at the margins who don't fit whatever average is, missing opportunities to give students back their own data, missing opportunities to talk about privacy in the overall conversation on campus and the like. So these are some of the resources I wanted to share with you. I also wanna give you, put this in chat, two more resources. We're doing on time, okay. This is the library caliper, the caliper library profile and also a conference paper that we wrote about a year ago about some of the issues that I alluded to tonight. There's ACRL, the Association of College and Research Libraries also has a learning analytics toolkit. A lot of the content heavily borrows from these two reports that you see here. Okay, that was a whirlwind. I hope that that was interesting to you. I would love to hear any questions that you have. I'm gonna stop sharing so I can see a little bit better. Jay, do we have any questions come in? We did not have any in the chat come in. Does anyone have any right now? I'd love a question, send me a question. Carly's here, Brenna's here. I bet some of you folks have questions. All right. One question that's kind of been asked at others is just like kind of your path into this industry. Obviously, you mentioned starting as a librarian, obviously now you have much more of a data background. So just kind of what led you into that. Yeah, so before I was a librarian, I was a public school teacher. And so it's sort of baked into how I think about things, continuous improvement and inquiry and using all resources possible to understand the situation and also try to affect change in the future. And it's bothered me for a long time, how many students are not able to complete their educational journeys. They take on debt, but they don't complete to get the credential to take care of that. And this is disproportionately affecting students of lower socioeconomic status, race, and what you would imagine to be the case. And that's not okay. And so any resources we can get to make better informed decisions and take actions to improve the future, I think it's an obligation to do that. I work in this area, but I don't consider myself a data expert. I partner and align myself with folks who have more technical chops than I do. But at the end of the day, as a team, we get the job done. And so for those of you who are maybe interested in data science, but maybe don't think that this is an affinity area for you naturally, having the larger vision is also an important element that is essential. And so I would encourage you to think through that. Oh, here's the questions. Yeah, we just had some questions come in at 7.30. Yeah, but this is the beginning of the student talk. It's fine. The student panel, we have 45 minutes first. So I would say definitely answer the questions. And then for everyone kind of paying attention in the chat, we will shut off the questions for Megan after the two looks like from Carly and Nika. Okay, great. So Carly, hi, Carly. So Carly asked about hesitancy for libraries to share data. Do you see on the horizon some chances with the growing interest in data library and shifting? Yes, I do. So some of the partners that I work with commonly are the University of North Carolina at Charlotte, the University of Michigan, the University of Minnesota, but there are others, the University of Denver. So there are library suppliers like EBSCO that are interested in this space. If you have time, you can look at their new product. It's called Panorama. And I don't have any insight information on that, but I'm just observing it from a distance. You know, I think that the need to address equity and inclusion has to drive some of this work. We need to do better as libraries and doing that. And I've been in the library field for 20 years and we haven't moved the needle nearly far enough. That is an understatement. And so, you know, we need to bring all of our data, but like all of our evidence to bear data being a big part of that. And so I think data librarians having those increased skills makes this less mysterious and more understandable and doable and we have more agency over it. I hope that made sense, Carly. And then could you give us an example of a successful learning analytics project implemented on campus? Yeah, okay. So I would look at the Georgia institutions for examples. There's examples throughout higher ed all over the place of Wayne State is another institution that you could look at there's just tremendous changes in their practice. I mean, just doing learning analytics doesn't solve anything. You have to then use the data to make better decisions for students, right? So it's always in the application. And the Georgia system and Wayne State are two that come to mind and having made big differences in retention and graduation for populations that they had trouble making inroads in previously. So those are two places I would look. It's such early days yet with libraries that I can't give you examples of that yet. But I believe that we will have more examples of those in the coming years. This caliper profile is brand new. And so we're working with the supplier community right now to see how they can implement that as well as individual libraries. So hopefully it'll make a difference. That's certainly the intent.