Abstract: Though quite challenging, training a deep neural network for automatically solving Math Word Problems (MWPs) has increasingly attracted attention due to its significance in investigating how ...

The original version of this story appeared in Quanta Magazine. In 1939, upon arriving late to his statistics course at UC Berkeley, George Dantzig—a first-year graduate student—copied two problems ...

This video teaches a step-by-step method to solve any circuit problem with confidence and accuracy. Learn how to analyze circuits systematically, apply fundamental laws correctly, and avoid common ...

Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

Catastrophizing is fixating on the worst possible outcome of a situation, even if unlikely. The author shares personal experiences with catastrophizing, particularly regarding a recent health ...

Do you sense something problematic about the word “problematic”? The way it’s used has changed a great deal in recent years, so much that it can now seem a little shifty. The journey that brought us ...

Word problems try and tell students a story about the math problem in front of them. They are a useful way to connect abstract numbers to concrete situations, so students can learn early on to apply ...

Standard computer implementations of Dantzig's simplex method for linear programming are based upon forming the inverse of the basic matrix and updating the inverse ...

Working memory is like a mental chalkboard we use to store temporary information while executing other tasks. Scientists worked with more than 200 elementary students to test their working memory, ...

Practical word problems are often considered one of the most complex parts of elementary school mathematics. They require students to understand the context of a math problem, identify what the ...