Results 61 to 70 of about 22,942 (236)

Impact of reducing intrinsic cognitive load on learning in a mathematical domain

Applied Cognitive Psychology, 2006
AbstractThis paper examines the effectiveness of instructional strategies that lower cognitive load by reducing task complexity (intrinsic cognitive load). Three groups of 13‐year‐old students were required to learn a mathematical task under different conditions.
openaire   +2 more sources

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Using eye movements, electrodermal activities, and heart rates to predict different types of cognitive load during reading with background music

Scientific Reports
The triarchic model of cognitive load postulates three types of cognitive load—extraneous, intrinsic, and germane load. While various approaches have been proposed to measure the three types of cognitive load, most measurements are intrusive.
Ying Que, Yueyuan Zheng, Janet H. Hsiao, Xiao Hu   +3 more
doaj   +1 more source

Mechanism‐Driven Nanoformulations for Cognitive Impairment Induced by Intermittent Hypoxia and Periodontitis

Advanced Materials, EarlyView.
Clinically, intermittent hypoxia (IH) is often accompanied by periodontitis, which accelerates cognitive impairment induced by IH. Novel Janus mesoporous gold‐silica nanoformulations (RVG‐Au&mSiO2‐TPP‐VB) enable intranasal delivery, achieve hierarchical targeting to neuronal mitochondria, effectively scavenge reactive oxygen species, inhibit the HIF‐1α/
Kai‐Run Zhang, Tianbao Zhu, An‐Qi Liu, Jia‐Jia Deng, Ya‐Li Han, Sheng‐Cai Qi, Xue Liu, Tian‐Yi Jiang, Ming‐Rui Zhai, Yu‐Ying He, Xiu‐Juan Li, Hong‐Ting Da, Rui Xu, Xiaomin Li, Jun Gao, Yue‐Hua Liu   +15 more
wiley   +1 more source

Optoelectronic Nanofluidic Neural Networks for Ionic Computing

Advanced Materials, EarlyView.
An ion‐based optoelectronic nanofluidic memristor enables neuromorphic computing in aqueous environments. With tunable ionic memory and multimodal synaptic plasticity, it realizes densely connected ionic neural networks capable of image classification, motion prediction, logic computation, and real‐time in‐sensor computing, advancing fully connected ...
Yaxin Huang, Zhiyuan Du, Changjin Wu, Binglin Zeng, Yingnan Cao, Mingliang Li, Liren Zhang, Qingxin Guo, Chao Huang, Can Li, Jinyao Tang   +10 more
wiley   +1 more source

TEORI BEBAN KOGNITIF JOHN SWELLER DAN IMPLIKASINYA DALAM PEMBELAJARAN BAHASA ARAB PADA JENJANG PENDIDIKAN DASAR

Fashluna
This study aims to explain the concept of Cognitive Load Theory developed by John Sweller and its implications for Arabic language learning at the elementary education level.
Ahmad Syagif
doaj   +1 more source

BEBAN KOGNITIF MAHASISWA DALAM PEMBELAJARAN FUNGSI TERINTEGRASI STRUKTUR TUMBUHAN BERBASIS DIMENSI BELAJAR

Jurnal Ilmu Pendidikan, 2014
: The Student Cognitive Load in Teaching and Learning of Plant Function Integrated with Plant Structure Using Learning Dimensions. This study measured the student cognitive load in teaching and learning of plant fuction integrated with plant structure ...
Adi Rahmat1, Anna Fitri Hindriana2
doaj   +1 more source

Soft Skins With Reversible Thickness Morphing: Materials, Mechanisms, and Applications

Advanced Materials, EarlyView.
Evolution of electronic skin (e‐skin) technologies toward adaptive, multifunctional soft skins. Phase I highlights early rigid and discrete sensory interfaces. Phase II shows the transition toward flexible, stretchable, and large‐area e‐skin. Phase III captures the emergence of computational e‐skin.
Oliver Ozioko, Chiamaka Akah, Ravinder Dahiya   +2 more
wiley   +1 more source

A Review on Sensor Technologies, Control Approaches, and Emerging Challenges in Soft Robotics

Advanced Robotics Research, EarlyView.
This review provides an introspective of sensors and controllers in soft robotics. Initially describing the current sensing methods, then moving on to the control methods utilized, and finally ending with challenges and future directions in soft robotics focusing on the material innovations, sensor fusion, and embedded intelligence for sensors and ...
Ean Lovett, Maxwell Hammond, Niloufar Seyfi, Amirreza Fahim Golestaneh, Venanzio Cichella, Caterina Lamuta   +5 more
wiley   +1 more source

Analysing Virtual Labs Through Integrated Multi-Channel Eye-Tracking Technology: A Proposal for an Explanatory Fit Model

Applied Sciences
This study deals with an analysis of the cognitive load indicators produced in virtual simulation tasks through supervised and unsupervised machine learning techniques.
María Consuelo Sáiz-Manzanares, Raúl Marticorena-Sánchez, Javier Sáez-García, Irene González-Díez   +3 more
doaj   +1 more source