Tech & Engineering
Updates every hour. Last Updated: 30-Dec-2025 07:11 ET (30-Dec-2025 12:11 GMT/UTC)
New study identifies ten key questions shaping the future of classroom analysis
ECNU Review of EducationWhile the classroom has long been described as the “black box” of education, classroom analysis aims to reveal what truly happens inside it. A new study led by East China Normal University identifies ten key questions at the frontiers of classroom analysis, offering a guideline for future research and practice. This study suggests that defining guiding values, constructing high-quality analytical frameworks, leveraging multimodal data, and ensuring ethical standards are essential to advance classroom research globally.
- Journal
- ECNU Review of Education
ECNU Review of Education reveals cultural pathways to improving teacher noticing in collaborative lesson study
ECNU Review of EducationIn an era where student-centered instruction and competency-based learning are gaining traction globally, enhancing teacher capacity remains a pivotal challenge. Recognizing this, a team of Chinese education researchers has turned to framing theory to better understand how collaborative professional development models—particularly lesson study—can drive meaningful shifts in teachers’ instructional practice.
- Journal
- ECNU Review of Education
New AI-driven tool could help find heart disease drugs faster
Medical Research Council (MRC) Laboratory of Medical SciencesPeer-Reviewed Publication
- Journal
- Nature
- Funder
- Medical Research Council, British Heart Foundation
Low-power memristor array for real-time edge computing in smart power grid inspections
Science China PressPeer-Reviewed Publication
Researchers developed an Ag/Sb2O3/Au memristor array that mimics brain-like computing, performing on-device image feature extraction with low power consumption, promising smarter and faster electric grid inspections.
- Journal
- Science Bulletin
A physics-constrained AI framework enables accurate thermal field inversion for chiplet-based packaging with sparse data
ELSPPeer-Reviewed Publication
Researchers at Shanghai University have developed a physics-constrained, data-efficient artificial intelligence framework that enables accurate thermal field inversion in chiplet-based packaging systems using only limited temperature measurements. The approach addresses a critical challenge in advanced heterogeneous integration, where increasing power density and material heterogeneity complicate thermal monitoring and reliability assessment.
Chiplet-based packaging integrates multiple heterogeneous chiplets into a single system, offering improved flexibility, yield, and cost efficiency compared to traditional system-on-chip designs. However, the resulting increase in power density and deterioration of heat dissipation conditions can lead to localized overheating, threatening system stability and long-term reliability. Accurately reconstructing the temperature field of such systems from sparse sensor data is therefore essential, yet remains a difficult inverse problem in practical engineering applications.
- Journal
- AI & Materials
AIT signs five new partnerships to strengthen water, sanitation, and digital municipal services during IWA Water and Development Congress and Exhibition 2025
Asian Institute of TechnologyBusiness Announcement