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  2. Worked-example effect - Wikipedia

    en.wikipedia.org/wiki/Worked-example_effect

    The worked-example effect is a learning effect predicted by cognitive load theory. [1] [full citation needed] Specifically, it refers to improved learning observed when worked examples are used as part of instruction, compared to other instructional techniques such as problem-solving [2] [page needed] and discovery learning.

  3. Singapore math - Wikipedia

    en.wikipedia.org/wiki/Singapore_math

    A bar model used to solve an addition problem. This pictorial approach is typically used as a problem-solving tool in Singapore math. Singapore math teaches students mathematical concepts in a three-step learning process: concrete, pictorial, and abstract. [3] This learning process was based on the work of an American psychologist, Jerome Bruner.

  4. Problem solving - Wikipedia

    en.wikipedia.org/wiki/Problem_solving

    Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields.

  5. Effective method - Wikipedia

    en.wikipedia.org/wiki/Effective_method

    In logic, mathematics and computer science, especially metalogic and computability theory, an effective method [1] or effective procedure is a procedure for solving a problem by any intuitively 'effective' means from a specific class. [2] An effective method is sometimes also called a mechanical method or procedure. [3]

  6. Problem-based learning - Wikipedia

    en.wikipedia.org/wiki/Problem-based_learning

    Problem-based learning (PBL) is a teaching method in which students learn about a subject through the experience of solving an open-ended problem found in trigger material. The PBL process does not focus on problem solving with a defined solution, but it allows for the development of other desirable skills and attributes.

  7. Markov decision process - Wikipedia

    en.wikipedia.org/wiki/Markov_decision_process

    Similar to reinforcement learning, a learning automata algorithm also has the advantage of solving the problem when probability or rewards are unknown. The difference between learning automata and Q-learning is that the former technique omits the memory of Q-values, but updates the action probability directly to find the learning result.

  8. How to Solve It - Wikipedia

    en.wikipedia.org/wiki/How_to_Solve_It

    How to Solve It suggests the following steps when solving a mathematical problem: . First, you have to understand the problem. [2]After understanding, make a plan. [3]Carry out the plan.

  9. Computational thinking - Wikipedia

    en.wikipedia.org/wiki/Computational_thinking

    Computational thinking (CT) refers to the thought processes involved in formulating problems so their solutions can be represented as computational steps and algorithms. [1] In education, CT is a set of problem-solving methods that involve expressing problems and their solutions in ways that a computer could also execute. [2]