Curriculum Prioritization, Most Essential Learning Competencies (MELCs), COVID-19, Curriculum Coherence, Teacher Agency Share and Cite: Malihan, J.C. (2026) Relearning What Matters: The MELCs as a ...

Abstract: Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims to learn modality-invariant features from unlabeled cross-modality data. However, existing approaches lack ...

Across the sample, cognitive load was negatively correlated with learning performance (large effect size), reinforcing its role as a key mediator of digital learning outcomes. Conclusions: Both ...

1 Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States 2 Rogel Cancer Center, University of Michigan, Ann Arbor, MI, United States ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...

Competing with big box stores can often feel like trying to win the World Series with a rookie roster. The top players have massive networks, seemingly endless budgets, and delivery timelines that ...

Institutions should be thinking about how all kinds of learners fit into their learning environments and avoid viewing online and in-person courses as distinct environments, according to Stephanie ...

With the continuous advancement of Artificial intelligence (AI), robots as embodied intelligent systems are increasingly becoming more present in daily life like households or in elderly care. As a ...

Abstract: The current study proposes the use of a hybrid deep learning model to predict delivery modalities (normal, caesarean, emergency, and aided delivery) from maternal health data. The model ...

AI institutions develop heterogeneous models for specific tasks but face data scarcity challenges during training. Traditional Federated Learning (FL) supports only homogeneous model collaboration, ...