Do you stare at a math word problem and feel completely stuck? You're not alone. These problems mix reading comprehension ...

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

AI systems are beginning to produce proof ideas that experts take seriously, even when final acceptance is still pending.

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

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.

Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.

Teacher shares how students can quickly recognize and classify mixed-concept numericals chapter-wise. , Education, Times Now ...

Large language models struggle to solve research-level math questions. It takes a human to assess just how poorly they ...

Most people in the math education space agree that students need to be fluent with basic math facts. By the time kids are in ...

Experts say Legos are still a powerful tool for early childhood education, fostering STEM skills, creativity, and even mental ...