 Hi, my name is Tracy Takahama-Spinoza and this is a video looking at the AEOLA Learner Outcomes, Module 3, where we're going to consider problem solving. This is one of the greatest roles of the brain. How do you problem-solve? So we're going to be looking at problem solving as it relates to creativity, to decision-making, to different types of strategies, and especially the teacher's role in enhancing problem-solving skills. But we also want to consider what's going on in your brain when you do problem solve so that you understand that there are really different neural networks that are being stimulated by different types of activities, and that all of those have to be working in sync for your brain to successfully problem-solve. So let's look at creativity for a second. Not all problem-solvings require creative solutions, but being able to think creatively increases the probability of resolving problems because you basically have a greater variety of options. You're not just looking for a single way to resolve a problem, but you develop alternative solutions. And the different models that exist, all of them share this idea of figuring out, you know, assessing the situation, do I know what's going on, what is the real goal, and then what are the challenges that are facing me. But most important, how do I explore these options, the different ideas that could resolve the problem in the end? So creativity in problem solving really focuses on the generation of various ideas, multiple ways of possibly resolving the problem at hand. When we look at problem-solving and decision-making, however, we're really looking at completely different networks that instead of option generation or idea generation, we're really looking at memory systems and how you make those choices based on emotional states or consequences of decisions in the past. So this choosing or the choice stage of information processing is a very different type of neural network in the brain than the generation of options. When we consider problem-solving in different strategies, some of you will want to make a table or a list to draw a picture or create a model, or you'll guess things and then you'll check and see if it works or you'll backwards engineer the problem. Other people go on fact-finding missions and do a lot of research and they make sure that they've defined their problem really well. All of these are very good strategies and they're distinct. Different people, they'll associate different processes with different strategies. It's not just one single thing. For example, planning on how you resolve your problem, resolving it, and then double-checking it can be a process that you go through every time you face a problem. You have some actions, so then that makes you create a new plan. You do something different. You check on it and then you act again, so you can basically have a cyclical process, not just a linear thing, a plan-solve check, but that it always begins again. And you know, others have these loopy processes where you verify the problem, you understand how it's structured, you prioritize the issues. And other models remember they were very focused on idea generation for what are the options. Here they basically say, let's prioritize the issues before we come up with different ideas. You develop and analyze your plan and then you implement and you synthesize your findings and then you basically start again. These different strategies are beneficial depending on the types of problems that you're faced with. But the most important thing about all of those different processes is that each of those sub-elements, planning or gathering information or generating ideas, are using distinct neural networks in the brain. So if we use another model, for example, a step model, you know, say the problem, think of solutions, explore consequences, pick the best solution, or identify, define, explore, action, look back, you know, ideal, these are very interesting and catchy models. Other ones talk about finding problems, evaluating, acting, and seeing this other model we talked about, creativity, developing alternative solutions. All of these have some similar elements. For example, this one I think is pretty good because it pretty much incorporates most of the elements that we were looking at in all these other prior models. And what's cool about this one is that we can use it to see what's going on in the brain. So when we're identifying the problem and we identify the causes of the problem, we're using key systems of attention and memory. As we talked about earlier, there is no learning without the systems of attention and memory. So this is pretty interesting that when we go to resolve a problem, the first things we do are pay attention to things and use memory systems to figure out if we already know something about the current problem, right? Then we have to use metacognitive skills and ask ourselves, you know, what do I need to know that I don't already know about the problem? So I know certain things, that's what my memory is telling me, but maybe I need to know new things, right? And then you ask yourself, metacognitively, have I asked all the right questions? Do I know what I need to know before I start looking for the answer? And then we brainstorm solutions. That's that idea generation step, right? And you select from all of those different options the best solution. That again is metacognitive skills. You know, have I considered all of these different options? And then you implement the plan and that's execution. And then you follow up and you evaluate. And that is another reflective process. Now, what's so interesting is if we look at all these different steps of attention, memory, metacognition, execution, reflection, what's so interesting in the brain is that these are different neural circuits. If I look at her memory systems in the brain, it's very distinct from then identifying attention networks in the brain. Those are very different networks, right? Or if I look at metacognitive skills in the brain, you're going to see a different set of pathways being illuminated than if I look at something like reflective practices. So what's really important to realize, you don't need to memorize all these kinds of brain scans, but the really important thing to take into consideration is that the different steps in problem solving require different neural networks. And because they require different neural networks, that means you have to have different types of activities in your class that stimulate those different neural networks. So what is it then that teachers can really do? Here's a handful of very simple recommendations. Number one, hopefully teachers see learning as fluid. Teachers who think that their kids are fixed, you know, are born a certain way and don't change, pass on the wrong message to kids that they are stuck with the brains that they are born with as opposed to realizing that learning is fluid, that intelligence is fluid, that people can change and can and do learn throughout the lifespan. Teachers can also help kids learn to problem solve by believing in their human potential. Your brain cannot not learn. So kids will learn. They just might not learn at the same pace. So believing in your children and this whole process of plasticity is really important in helping kids learn to problem solve. Another key idea, as always, is to be a model. You just can't get apples from a pear tree. So if we are hoping that we are clever problem solvers, working that out in front of kids, helping them see how we struggle at certain stages of problem solving, helping them see how we get over those different challenges we might have with problem solving is really important in modeling the behavior that we hope that they are able to show when they try to problem solve. Another big idea is to award perseverance and celebrate error. When people try and they try hard and they might not achieve in the first run, that's okay. That's part of learning. If you knew everything anyways, you wouldn't need to go to school. But here they're at school and they're gonna make mistakes and that's okay. But helping kids understand that every problem is an opportunity that they should not be fearful of this constructive criticism, that you're giving them feedback because you wanna help them is a really big message to send. So I'd like to suggest everybody puts this up in their classrooms, dare to err, right? Try to do something that's a little bit hard. Go ahead and make mistakes. But we as teachers have to create that environment where students feel like it's okay to make those mistakes. It's okay to try. That's a really hard thing for us to do because as teachers, we're always looking for the right answer. But we should realize that part of the path to understanding and to true learning is helping kids understand how to make better mistakes each time, how to get closer to the solution each time to problem solve by trying different things, which might not be absolutely the right thing, but they may be inching towards a better solution as they dare to make suggestions towards those solutions. And this requires a really big mind shift in our own classes, right? We have to understand and agree and accept, especially where the brain is concerned that learning things means creating new connections. Every single day, you guys are changing kids' brains by making new connections. But sometimes some of those connections are erroneous and that's okay, that's what pruning is for. They've made a misconnection, they'll have to cut that one off and refine other ones. But the idea is that we have to encourage this growth mindset by allowing kids to make those mistakes and understanding that they have room to grow within our class, they can make mistakes. So if you understand how neuroplasticity works and you understand that plasticity itself is the evidence we need to say, yes, growth mindsets do exist, right? That's important. You should also be a model for how to resolve problems and how to show, well, I made a mistake this time or this wasn't the best solution, was it? Or how could I do that better the next time? Being a model is a huge responsibility that we have within schools. Also remember, your brain cannot not learn. So it's always learning and it does and can learn from its mistakes if it's encouraged to do so. And finally, I hope that you do use this mantra in your classroom that kids should dare to air. So with that, I hope you have lots of questions about problem solving and that when we get together this week, we can talk about how all of this relates to your own classrooms. Thanks.