Chain-of-Thought (CoT) prompting has enhanced the performance of Large Language Models (LLMs) across various reasoning tasks.

These student-constructed problems foster collaboration, communication, and a sense of ownership over learning.

Four simple strategies—beginning with an image, previewing vocabulary, omitting the numbers, and offering number sets—can have a big impact on learning.

Hong Kong, China, 14th Nov 2025 – AskMath announced the launch of an AI Math Solver designed to provide detailed problem-solving guidance for a variety of mathematical queries. The platform delivers ...

Axiom says its AI found solutions to several long-standing math problems, a sign of the technology’s steadily advancing reasoning capabilities.

(THE CONVERSATION) Among high school students and adults, girls and women are much more likely to use traditional, step-by-step algorithms to solve basic math problems – such as lining up numbers to ...

What if the secrets to the universe’s most perplexing mathematical riddles were no longer locked away, but instead cracked open by an artificial mind? In a new development, OpenAI’s o3-mini model has ...

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