A white paper from University of Phoenix explores emotional intelligence as a driver of organizational wellness, by research Fellow Chanell Russell.

For K-12 students with disabilities, ensuring they receive appropriate support for learning is critical to their success, which can raise questions about the best type of school for them, such as a traditional public school, charter school or private school.

A new study examined students with disabilities in Michigan charter schools, finding that when students with disabilities switched from traditional public to charter schools, they perform just as well, despite spending less time in intensive programs and more time in general education classrooms.

Academic performance and attendance improved for both students with and without disabilities after entering charter schools. This research raises important considerations about resource usage and how to best balance inclusive practices with specific targeted support for students with disabilities.

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has recently emerged as a promising approach for OOD generalization. However, the exploration within graph data remains constrained by the complex nature of graphs. The invariant features at both the attribute and structural levels, combined with the absence of prior knowledge regarding environmental factors, make the invariance and sufficiency conditions of invariant learning hard to satisfy on graph data. Existing studies, such as data augmentation or causal intervention, either suffer from disruptions to invariance during the graph manipulation process or face reliability issues due to a lack of supervised signals for causal parts.