Results 41 to 50 of about 65,604 (247)

The Effect of Physical Activities on Physical Education Learning Outcomes

Journal of Education, Health and Sport, 2019
This study aimed to find the effect of physical activity on academic performance of physical education. The research method used in this research is quantitative approach, survey method with test and measurement technique. The population of the research was students at a public secondary school in East Jakarta, and 216 students of 6 classes grade eight
P, Eva Julianti, Dlis, Firmansyah, Asmawi, Moch   +2 more
openaire   +4 more sources

Gaussian Process Assisted Active Learning of Physical Laws [PDF]

Technometrics, 2020
27 pages, 5 figures, 10 ...
Jiuhai Chen, Lulu Kang, Guang Lin 0001
openaire   +3 more sources

Pathways and pitfalls: a qualitative study of student experiences in biomedical science education

FEBS Open Bio, EarlyView.
Biomedical science students from underrepresented backgrounds face barriers including financial strain, disrupted laboratory access and cultural exclusion. Peer networks provide vital support when institutional systems are difficult to navigate. To create inclusive learning environments and achieve academic success, educators should blend active, hands‐
Olivia J. Russell, Cassy Ross, Panagiota S. Filippou, Bruno Silvester Lopes, Dominic Gilchrist, Paul Dean, Kamar Ameen‐Ali, Tora K. Smulders‐Srinivasan, Ahmad A. Khundakar   +8 more
wiley   +1 more source

Efficient Exploration of Microstructure-Property Spaces via Active Learning

Frontiers in Materials, 2022
In materials design, supervised learning plays an important role for optimization and inverse modeling of microstructure-property relations. To successfully apply supervised learning models, it is essential to train them on suitable data.
Lukas Morand, Norbert Link, Tarek Iraki, Johannes Dornheim, Johannes Dornheim, Dirk Helm   +5 more
doaj   +1 more source

Artificial Intelligence in Physics Courses to Support Active Learning [PDF]

Proceedings of the 2024 10th International Conference on e-Society, e-Learning and e-Technologies (ICSLT)
The integration of generative artificial intelligence (AI), particularly Large Language Models (LLMs) like OpenAI's ChatGPT and Microsoft's Copilot, is transforming educational methodologies, including undergraduate physics courses for engineering students.
Víctor Robledo-Rella, Bee-Yen Toh
openaire   +2 more sources

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Active Learning in Physics: From 101, to Progress, and Perspective

Advanced Quantum Technologies, 2023
Abstract Active learning (AL) is a family of machine learning (ML) algorithms that predates the current era of artificial intelligence. Unlike traditional approaches that require labeled samples for training, AL iteratively selects unlabeled samples to be annotated by an expert.
Ding, Yongcheng, Martín‐Guerrero, José D., Vives‐Gilabert, Yolanda, Chen, Xi   +3 more
openaire   +3 more sources

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Physically active learning and school-based physical activity interventions in reducing sedentary time among secondary school students: literature review

Pedagogy of Health
Background and Study Aim. Sedentary behavior has become a growing concern among secondary school students in contemporary educational settings. Learning activities, screen use, and classroom routines often require students to remain seated for prolonged ...
Trisnar Adi Prabowo, Mar'atul Afifah, Asyidika Vito Indarto, Zakwan Yumna Dhuha Pahlavi, Achmad Zakaria, Febriansyah Dwi Cahyo   +5 more
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source