In many of the above examples, once an organizing principle for the system is identified, the details of the solution are quite simple.

use the Neuroscience principle of education for corporate learning systems so instead of just having a classic a classic lesson to teach people

catching a break is necessary in order to refill your mental capacities and as a rule of thumb you can say that it's it's five to one five parts of work one part of doing a break so 50 minutes working 10 minutes catching a break

Many of the coping mechanisms prove useful in certain situations. Some studies suggest that a problem-focused approach can be the most beneficial

THE PROBLEM WITHPROBLEM SOLVING

you don't meet something head-on you meet it around you meet it within you meet it 00:04:24 totally in ecological systems nothing is happening one thing at a time there's not a solution to a problem

The city council president said Grants Pass’s goal was to “make it uncomfortable enough for them in our city so they will want to move on down the road.”

Should Kids Use Apps at All?

don't give them a problem to solve ask them to identify what the problem is and what the context is and what support 00:08:12 is needed

The motto of the Sunday Tramps was Solvitur Ambulando, ‘It is solvedby walking.’

Monday had been a walk around the deer park within the walls ofMagdalen College. C. S. Lewis had said that the circular path was the perfectlength for any problem. It was true.

The sectors become the vehicle to carry the problem-solving governance

you only have to solve a limited set of problems, and so you can write relatively fast.

we were designed by you know evolution through evolution we have become we were i really every organism as we'll 00:45:01 talk about in a minute is a problem-solving organism and if i can't solve problems there's like a you know like fundamentally going against the grain of what it means to be an organism

1) How do I choose to be in relationship to this problem?2) What opportunity is presenting itself through my problem?

When I create a new note, I write and link it as usual. Then I call up a saved search in The Archive via shortcut. I then go through the notes of my favorites and see if the fresh note is usable for one of my favorites. In doing so, I make an effort to find a connection. This effort trains my divergent thinking. Afterward, I try to understand the nature of the connection from the fresh piece of paper. In this way, I train my convergent thinking.

Not all favorites are problems! I don’t phrase everything as a problem. For example, I am writing a collection of short stories set in a prison valley. It is also part of my list of favorites. I think Feynman has 12 favorite problems because as a physicist, you mainly solve problems. But as a writer, you don’t only solve problems, you write texts. There are different types of opportunities, not just problems.

This technique is another demonstration of Feynman’s genius. It is simple and efficient: Maintain a collection of 12 favorite problems. Whenever you learn something new, check if it helps you with one of your 12 favorite problems. Richard Feynman was fond of giving the following advice on how to be a genius. You have to keep a dozen of your favorite problems constantly present in your mind, although by and large they will lie in a dormant state. Every time you hear or read a new trick or a new result, test it against each of your twelve problems to see whether it helps. Every once in a while there will be a hit, and people will say, “How did he do it? He must be a genius!”

Networked thinking is an explorative approach to problem-solving, whose aim is to consider the complex interactions between nodes and connections in a given problem space. Instead of considering a particular problem in isolation to discover a pre-existing solution, networked thinking encourages non-linear, second-order reflection in order to let a new idea emerge.

To cover my knowledge management process would distract you from what works for you. Your question needs more context to be actionable.TL;DR; Whichever knowledge management system gets you paid.I've got 13 notes with the term "knowledge management," 15 with "information gathering," and 7 with "strategic intelligence." Without finishing a MOC, here's off the top of my head:Have a purpose or reason for learning.Ask helpful questions that solve problems.Answer questions as stand-alone notes.Learn from primary sources. Even boring ones.Take notes for your intended audience.Serve a specific audience (get paid.)Write about what people care about.Become a subject matter expert in target areas.Deliver what you know as a service first.Build on your strengths. Knowledge is cheap.It's not a process. More like tips. If demand exists, I'll write a book on the topic in a few years. Might be a good podcast topic.“No man but a blockhead ever wrote, except for money.” -- Samuel Johnson, The Life of Samuel JohnsonRemember, there is no shortage of knowledge. Managing information is like masturbation; it feels good but doesn't do much. Focus on making information drive goal achievement.

Richard Feynman was fond of giving the following advice on how to be a genius. You have to keep a dozen of your favorite problems constantly present in your mind, although by and large they will lie in a dormant state. Every time you hear or read a new trick or a new result, test it against each of your twelve problems to see whether it helps. Every once in a while there will be a hit, and people will say, “How did he do it? He must be a genius!”

Interpersonal competence is the ability to motivate, enable, and facilitate collaborative and participatory sustainability research and problem solving.

definition of competence as a functionally linked complex of knowledge, skills, and attitudes that enable successful task performance and problem solving

Lateral thinking is a manner of solving problems using an indirect and creative approach via reasoning that is not immediately obvious.

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The word “emergency” dates back to the Latin word emergentia, which means “to bring to light.”

The problems that we solved are applicable to a lot of people. Most people are not even aware of these problems, so things can break in unexpected ways (Murphy's law). It's inefficient if everybody has to solve these problems over and over.

How to become a successful physicist

The nature of physics problem-solvingBelow are 29 sets of questions that students and physicists need to ask themselves during the research process. The answers at each step allow them to make the 29 decisions needed to solve a physics problem. (Adapted from reference 33. A. M. Price et al., CBE—Life Sci. Edu. 20, ar43 (2021). https://doi.org/10.1187/cbe.20-12-0276.)A. Selection and planning1. What is important in the field? Where is the field heading? Are there advances in the field that open new possibilities?2. Are there opportunities that fit the physicist’s expertise? Are there gaps in the field that need solving or opportunities to challenge the status quo and question assumptions in the field? Given experts’ capabilities, are there opportunities particularly accessible to them?3. What are the goals, design criteria, or requirements of the problem solution? What is the scope of the problem? What will be the criteria on which the solution is evaluated?4. What are the important underlying features or concepts that apply? Which available information is relevant to solving the problem and why? To better identify the important information, create a suitable representation of core ideas.5. Which predictive frameworks should be used? Decide on the appropriate level of mechanism and structure that the framework needs to be most useful for the problem at hand.6. How can the problem be narrowed? Formulate specific questions and hypotheses to make the problem more tractable.7. What are related problems or work that have been seen before? What aspects of their problem-solving process and solutions might be useful?8. What are some potential solutions? (This decision is based on experience and the results of decisions 3 and 4.)9. Is the problem plausibly solvable? Is the solution worth pursuing given the difficulties, constraints, risks, and uncertainties?Decisions 10–15 establish the specifics needed to solve the problem.10. What approximations or simplifications are appropriate?11. How can the research problem be decomposed into subproblems? Subproblems are independently solvable pieces with their own subgoals.12. Which areas of a problem are particularly difficult or uncertain in the solving process? What are acceptable levels of uncertainty with which to proceed at various stages?13. What information is needed to solve the problem? What approach will be sufficient to test and distinguish between potential solutions?14. Which among the many competing considerations should be prioritized? Considerations could include the following: What are the most important or most difficult? What are the time, materials, and cost constraints?15. How can necessary information be obtained? Options include designing and conducting experiments, making observations, talking to experts, consulting the literature, performing calculations, building models, and using simulations. Plans also involve setting milestones and metrics for evaluating progress and considering possible alternative outcomes and paths that may arise during the problem-solving process.B. Analysis and conclusions16. Which calculations and data analysis should be done? How should they be carried out?17. What is the best way to represent and organize available information to provide clarity and insights?18. Is information valid, reliable, and believable? Is the interpretation unbiased?19. How does information compare with predictions? As new information is collected, how does it compare with expected results based on the predictive framework?20. If a result is different from expected, how should one follow up? Does a potential anomaly fit within the acceptable range of predictive frameworks, given their limitations and underlying assumptions and approximations?21. What are appropriate, justifiable conclusions based on the data?22. What is the best solution from the candidate solutions? To narrow down the list, decide which of those solutions are consistent with all available information, and which can be rejected. Determine what refinements need to be made to the candidate solutions. For this decision, which should be made repeatedly throughout the problem-solving process, the candidate list need not be narrowed down to a single solution.23. Are previous decisions about simplifications and predictive frameworks still appropriate in light of new information? Does the chosen predictive framework need to be modified?24. Is the physicist’s relevant knowledge and the current information they have sufficient? Is more information needed, and if so, what is it? Does some information need to be verified?25. How well is the problem-solving approach working? Does it need to be modified? A physicist should reflect on their strategy by evaluating progress toward the solution and possibly revising their goals.26. How good is the chosen solution? After selecting one from the candidate solutions and reflecting on it, does it make sense and pass discipline-specific tests for solutions to the problem? How might it fail?Decisions 27–29 are about the significance of the work and how to communicate the results.27. What are the broader implications of the results? Over what range of contexts does the solution apply? What outstanding problems in the field might it solve? What novel predictions can it enable? How and why might the solution be seen as interesting to a broader community?28. Who is the audience for the work? What are the audience’s important characteristics?29. What is the best way to present the work to have it understood and to have its correctness and importance appreciated? How can a compelling story be made of the work?

To be a successful physicist requires mastering how to make all 29 decisions, but the reflection decisions (decisions 23–26) are arguably the most difficult to learn.

A much more effective approach is to give them a meaningful problem to struggle with first and then provide them with the knowledge they need to figure it out.99. D. L. Schwartz, T. Martin, Cogn. Instr. 22, 129 (2004). https://doi.org/10.1207/s1532690xci2202_1 When information is presented as useful for solving certain kinds of problems, the brain stores that information so that it is readily accessed and applied when needed to solve novel related problems.

why is there so little correlation between students’ performance in their physics courses and their ability to do physics research?

The experts often noted that research breakthroughs came from recognizing the significance of some additional information that other researchers had overlooked.

My research group interviewed some 50 skilled scientists and engineers (“experts”), including physicists, on how they solved authentic problems in their discipline. We analyzed the interviews in terms of the decisions made during the solving process. Decisions were defined as instances when an expert selected between competing alternatives before taking some action. To my surprise, we found that the same set of 29 decisions occurred over and over (see the box on page 50). Nearly all of them showed up in every interview, and they essentially defined the problem-solving process.3

I'm going to just try to tell you as quickly as I can and in fairly straightforward way the story of how the human mind especially the modern mind 00:00:58 came into being it's a it's a it's a complex story but I think the the bare bones can be exposed rather rather straightforward matter rather quickly 00:01:09 my basic message is that what makes humans so different from other species from all the other species in the biosphere including our very close relatives the great apes is that we 00:01:21 build distributed cognitive networks

A. Watermelon

hatis, certain problems can be formulated clearly within a framework of ideasthat is reasonably clear and well understood; certain partial solutions can beadvanced; and a range of examples can be discovered where these solutionsfail, leaving open for the time being the question whether what is needed isfurther elaboration and sharpening or a radically different approach.

the better we can become at collecting,understanding, and remembering information, the morelikely we are to solve hard problems.

there's a lot of discussion about complex systems you know we've been discussing complex systems and i just want to make a couple of points here because uh 01:31:28 commonly some it is not uncommon that someone will say a complex system well that just means that it's liable to fall apart at any moment you know it's just too complex it's going to crash uh but and that that obviously can 01:31:41 happen you know systems can collapse quite quite true but obviously life would not be doing very well if the if if the evolution builds complexity 01:31:53 in species and you know in organisms and ecosystems if life would be have a rough go of it if it was so fragile that uh complexity became a 01:32:07 burden and and uh you know come and then you know you reach a certain level of complexity and then you fall apart that's not really i don't think i mean that can happen but that's but but complex useful complexity 01:32:19 doesn't make you fall apart it actually just does the opposite it serves what we've been talking about all along and that's problem solving so we are anticipatory organisms we are problem 01:32:31 solving organisms it's our nature most of what the human brain does is to solve problems of one kind or another social problems physical problems whatever and maneuver in the world you 01:32:43 know in a useful way and complexity is what allows that there's a number of studies that i cite here that show that as an organism even as a robot you know 01:32:56 faces uh more difficult pressures from its environment it complexifies and complexifies by complexity then it's it's it implies 01:33:08 a greater number of parts coordinating or cooperating in some way uh to you know solve this new challenge and obviously as a human we're very complex we have 01:33:22 we have complex needs we have we can think not just what's going to happen in the next millisecond but what's going to happen we can think about what's going to happen in 100 years i mean part of this project is to think about what might be 01:33:36 happening over the next hundred years or even a thousand years so as an organism complexifies it become it at least potentially becomes a better adapted to solving more complex 01:33:49 problems so you could and from that sense you could almost ex equate complexity with problem-solving capacity you know at least in a uh you know in a 01:34:01 general sense and then i talked about well that just reminds me of in the free energy calculations that we um have gone over in various papers it's like accuracy is the modeling imperative and 01:34:14 then complexity is tolerated to the extent it facilitates accurate modeling so if you get the one parameter model and you got 99 and it's adequate and it's good then you're good to go and you're gonna go for simplicity 01:34:26 but then what you're saying is actually the um appearance and the hallmark of complexity in the world it means that that organism has the need to solve problems at a given 01:34:40 level of counterfactual depth or inference skill or temporal depth temporal thickness

To solve creative problems with TRIZ, there are three elements you need to know: It’s been solved before.There are consistent patterns of solutions.Solving contradictions creates breakthrough innovation

TRIZ (a Russian acronym for the ‘Theory of Inventive Problem Solving”). Through TRIZ, Altshuller was now able to demonstrate the science behind creative innovation, not only paving the way for new breakthroughs in technology but establishing a framework of immense value to countless other fields.

three steps required to solve the all-importantcorrespondence problem. Step one, according to Shenkar: specify one’s ownproblem and identify an analogous problem that has been solved successfully.Step two: rigorously analyze why the solution is successful. Jobs and hisengineers at Apple’s headquarters in Cupertino, California, immediately got towork deconstructing the marvels they’d seen at the Xerox facility. Soon theywere on to the third and most challenging step: identify how one’s owncircumstances differ, then figure out how to adapt the original solution to thenew setting.

I mean there’s no single answer that will solve all of our future problems. There’s no magic bullet. Instead there are thousands of answers — at least. You can be one of them if you choose to be.'

Gesturing also increases as afunction of difficulty: the more challenging the problem, and the more optionsthat exist for solving it, the more we gesture in response.

This is a widespread mistake among those who think that a sexy note-taking app like Roam will suddenly free their minds, or that they can train themselves into geniuses with enough spaced repetition, or that they can build a zettelkasten capable of thinking original thoughts for them.

his suggests that successful problem solvingmay be a function of flexible strategy application in relation to taskdemands.” (Vartanian 2009, 57)

Technological solutions to social problems seem quicker, cheaper, and simpler to implement than larger social changes.

Usually it is more fruitful to look for formulations of problems that relate heterogeneous things with each other.

Victor Papanek’s Design Problem, 1975.

A series of studies conducted by Frédéric Vallée-Tourangeau, a professor of psychology at Kingston University in Britain; Gaëlle Vallée-Tourangeau, a professor of behavioral science at Kingston; and their colleagues, has explored the benefits of such interactivity. In these studies, experimenters pose a problem; one group of problem solvers is permitted to interact physically with the properties of the problem, while a second group must only think through the problem. Interactivity “inevitably benefits performance,” they report.

Play may trump problem solving. When working on a problem without a specific goal, the student can try lots of things to figure out what works. In contrast, only one answer is needed to solve a problem with a single goal. A playful, exploratory mindset may map out the patterns of interactions better than a narrowly, solution-oriented perspective. As an example of this, Sweller asked students to solve some math problems. One group was asked to solve the problems for a particular variable, and the other group was asked to solve for as many variables as they could. The latter group did better later, which Sweller explained in terms of cognitive load.4

John Sweller’s cognitive load theory argues that problem solving is often inefficient.2 His studies showed that students learned to solve algebra problems faster when they were shown lots of examples of solved problems, rather than trying to solve them on their own.3

You're right, it would solve the Nemo problem perfectly, but break a lot of other things, unfortunately.

The second is that their approach of allowing standards to evolve through practical application, rather than highfalutin conjecture, is an incredibly powerful technique for problem-solving. The number of my ideas that have died on paper as I try to flesh them out are beyond count. It's the Goldilocks conundrum: the feeling that something needs to be just right before other people can see it. The IndieWeb methodology proves that this logic should just be thrown away.

Write modules that solve a problem you know

Doing a HOC properly, as a library should, with hoisted statics and displayName and ref, etc., is a hassle and would add unnecessary bulk.

you took 4 hours to respond, so I implemented it myself

Offsetting the rules of a logic-less template requires a lot of helper methods.

I'm suggesting this is a problem generally. Users will not think of being out of sync with props

This has the merit of simplicity and obviousness, but it's not particularly ergonomic: it signals that we don't consider component themeability to be a problem worth solving properly.

And you don't have to find solutions to the additional problems that CSS-in-JS introduces.

it's important to distinguish managing a problem from fixing it, for these are very different acts: one is a process, the other an event. Solving a problem often requires a bit of both.

Your idea should stem from solving someone’s problem. Ideally, your own problem. It’s important that you choose an idea which interests you. Interest is key to fuelling motivation which is crucial when making a web app. It takes effort building web apps and it’s important you have fun during the process.

Learning Domains

It is critical to understand that within systems, there is no isolation from the context, though we often view context as the invisible elephant in the room. When context is not addressed explicitly, equity issues are overlooked, and conversations about diversity in the science curriculum become only necessary for the poor, or students of color, or bilingual students. Issues of equity and context must be integrated in a wider systemic approach for the implementation of the NGSS to be deemed useful. We have to allow for boundary crossing and interdisciplinary connections into domains that make context and students from lower socioeconomic backgrounds, girls, students of cultural and linguistic diversity, and students in urban, suburban, and rural areas want to engage in science and see themselves in science. We believe that a culturally responsive approach to the implementation of the NGSS will achieve this goal.

Within the vignette and the experiences of the four teachers, there is a fundamental equity and diversity issue that is shared among them: whose responsibility is it to address equity and diversity? How do we address it in science and within our particular contexts, and with our particular student populations? What supports must be present to allow us to promote equity and diversity in our teaching, learning, and curriculum? What supports are present in the NGSS to assist all teachers to teach in culturally responsive ways so that teachers meet the educational science needs of all students? Our position and the ways in which we address these questions center on implementation of the NGSS with equity and diversity as theoretical and pedagogical foundations to science teaching. In this way, equity and diversity becomes a vision and goal for implementation.

Every English class starts with a moment of quiet after which students are asked to share their energy and stress levels.

In English, juniors are grouped with seniors, which helps the younger students learn how the process works by watching and learning from the older students

on the mathematical process and not just the “right answer.”

group tests, which, like the class worksheets, are designed to be harder than the individual assignment

effective classroom geography, focus on the process, build accountability, let students teach one another, and encourage students to be in tune with one another.

resilient by aiding them with identifying their resources (peers) and testing their theories to see if they are on the right track all while developing habits of mind that form the foundation of scholarship.

Playing games with my brother taught me that connections can be made with another person through virtual reality. Things like cooperation, shared problem-solving, and communication in gaming can strengthen relationships. Most importantly, gaming taught me that no matter the differences between me and another person, we can find common ground through play.

1. Explore the current situation. Paint a picture in words by including the “presenting problem,” the impact it is having, the consequences of not solving the problem, and the emotions the problem is creating for those involved.

projectors refer to “people who find a way out of their difficulties by coming up with novel ideas” (Novak, 2008, p. 3)

In short, online reading compre-hension is online research. Second, online reading also becomes tightly integrated with writing as we communicate with others to learn more about the questions we explore and as we communicate our own inter-pretations. A third difference is that new technologies such as browsers, search engines, wikis, blogs, e-mail, and many others are required. Addi-tional skills and strategies are needed to use each of these technologies effectively

Affiliations— memberships, formal and informal, in online communities centeredaround various forms of media, such as Friendster, Facebook, message boards,metagaming, game clans, or MySpace).Expressions— producing new creative forms, such as digital sampling, skinning andmodding, fan videomaking, fan fiction writing, zines, mash-ups).Collaborative Problem-solving— working together in teams, formal and informal,to complete tasks and develop new knowledge (such as through Wikipedia, alternativereality gaming, spoiling).Circulations — Shaping the flow of media (such as podcasting, blogging).

“It’s more complicated than that.” No kidding. You could nail a list of caveats to any sentence in this essay. But the complexity of these problems is no excuse for inaction. It’s an invitation to read more, learn more, come to understand the situation, figure out what you can build, and go build it. That’s why this essay has 400 hyperlinks. It’s meant as a jumping-off point. Jump off it. There’s one overarching caveat. This essay employed the rhetoric of “problem-solving” throughout. I was trained as an engineer; engineers solve problems. But, at least for the next century, the “problem” of climate change will not be “solved” — it can only be “managed”. This is a long game. One more reason to be thinking about tools, infrastructure, and foundations. The next generation has some hard work ahead of them.

in every community or organization, there are a few individuals or groups whoseuncommon but successful behaviors and strategies have enabled them to find better solutions to problems than their neighbors who face the same challenges and barriersand have access to same resources.

This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence.

If things go wrong, do not sweep them aside. Confront the problems, get to the root of the difficulties, and wrestle with these resolutely. Go for long-term success, and do not be deterred by criticisms.