We need to better understand how LLMs address moral questions if we're to trust them with more important tasks.

From deep research to image generation, better prompts unlock better outcomes. Here's the step-by-step formula.

More than 900 students at UC San Diego needed catch-up math classes in the fall of 2025 compared to 32 five years earlier.

It’s a breakthrough in the field of random walks.

After years of assigning the kind of homework she had done as a student and observing students’ disengagement with it, a teacher overhauled how she assigns math practice.

In other words, you want to construct a polyhedral torus with faces that are shapes such as triangles or rectangles. Your peculiar-looking shape will be trickier to construct than one with a smooth ...

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

Mathematicians finally understand the behavior of an important class of differential equations that describe everything from ...

These low-floor, high-ceiling problems support differentiation, challenging all students by encouraging flexible thinking and allowing for multiple solution paths.

The most recent TIMSS assessment underscores the seriousness of our problem. Canadian Grade 4 students performed below both U.S. students and the international median at nearly every math benchmark ...

Math anxiety is a significant challenge for students worldwide. While personalized support is widely recognized as the most ...

Large Language Models predict text; they do not truly calculate or verify math. High scores on known Datasets do not always mean real understanding. Small changes in numbers can break Language Models ...