Algebra is a core part of mathematics that develops critical thinking and problem‑solving skills. Among its many topics, inequalities stand out as both essential and challenging for students. Whether ...

In an age of quick sound bites and crisis-driven narratives, the story of South Africa's education system calls for a richer ...

The latest snapshot of wealth inequality comes as billionaire fortunes continue to grow rapidly, both in the U.S. and abroad. An Oxfam International report released this week found that billionaire ...

When the latest national achievement scores come out, people want to look at the change since the last time. Are things going up or down? But that short-term focus on the averages loses sight of ...

A mystery novel, a history book, and a fantasy epic may have little in common in plot or style. But count the words inside them and a strange regularity appears: many new words show up early, then ...

Does sharing salaries in job postings help address the gender pay gap? March 15 was Equal Pay Day, the first in a series of reminders of how persistent the pay gap has been. More states and cities ...

Mathematics and computer science give two complementary ways to engage with our modern world. Mathematics teaches you the timeless vocabulary of reason that underlies all sciences. Computer science ...

Applied mathematics is the application of mathematical techniques to describe real-world systems and solve technologically relevant problems. This can include the mechanics of a moving body, the ...

This chapter provides new evidence on educational inequality and reviews the literature on the causes and consequences of unequal education. We document large achievement gaps between children from ...

Bihar, India's most flood-prone state, faces a relentless cycle of poverty exacerbated by recurring floods. A comprehensive report by Megh Pyne Abhiyan highlights the severe economic impact on ...

GraphStorm is an enterprise-grade graph machine learning (GML) framework designed for scalability and ease of use. It simplifies the development and deployment of GML models on industry-scale graphs ...

We propose a novel deep learning framework, STGCN, to tackle time series prediction problem in traffic domain. Instead of applying regular convolutional and recurrent units, we formulate the problem ...