Results 61 to 70 of about 562,162 (281)

Effects of self-regulated vocabulary learning process on self-efficacy [PDF]

, 2013
Researchers, especially in the field of educational psychology, have argued that self-efficacy plays an important role in self-regulated learning. As such, teaching of self-regulated learning often focuses on enhancing self-efficacy. However, few studies
Mizumoto Atsushi, 水本 篤
core   +2 more sources

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Student perception of teacher encouragement of self-regulated learning and its relationship with self-regulation learning strategies

Frontiers in Education
IntroductionSelf-regulated learning significantly impacts academic achievement and learning effectiveness; however, a significant portion of students do not engage in optimal self-regulated learning.
Slavica Šimić Šašić, Maša Atlaga
doaj   +1 more source

Interaction Effects of Gender and Motivational Beliefs on Self-Regulated Learning: A Study at ICT-Integrated Schools

Malaysian Journal of Learning and Instruction, 2016
Purpose â€“ This study aimed to examine the interaction effects of gender and motivational beliefs on students’ self-regulated learning. Specifically, three types of motivational beliefs under the Expectancy-Value Model were examined, namely self ...
Melissa Ng Lee Yen Abdullah
doaj   +1 more source

Professional Learning in Massive Open Online Courses [PDF]

, 2014
This study explores the role of Massive Open Online Courses (MOOCs) in supporting and enabling professional learning, or learning for work. The research examines how professionals self-regulate their learning in MOOCs.
Littlejohn, Allison, Milligan, Colin, Ukadike, Obiageli   +2 more
core  

Ultrahigh‐Yield, Multifunctional, and High‐Performance Organic Memory for Seamless In‐Sensor Computing Operation

Advanced Functional Materials, EarlyView.
Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim, Jaehyoung Ko, Namju Kim, Quynh H. Nguyen, Hoyeon Lee, Joohwan Eo, Seongeon Jin, Ji Eon Kwon, Seung‐Yeol Jeon, Youngdo Jeong, Dongseok Kwon, Sung Gap Im, Sanghan Lee, Byung Chul Jang, Yongho Joo   +14 more
wiley   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Learning achievement reviewed from self regulated learning, future orientation, and parental support

COUNS-EDU: The International Journal of Counseling and Education, 2020
This study aimed to answer the main problem whether learning achievement could be viewed from self-regulated learning, future orientation and parental support to obtain empirical support. This research used quantitative methods, the sample of 103 people.
Yuzarion Yuzarion, Aulia Kartika Agustiana, Alfaiz Alfaiz, Hengki Yandri, Musdizal Musdizal, Rahmadianti Aulia   +5 more
doaj   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Fostering self-regulated learning [PDF]

, 2021
Self-regulated learning skills are crucial to achieve academic success, especially for higher education students who spend ample time studying on their own, at their own place or in the university library. Two learning strategies, that is, retrieval practice and distributed practice, have been found to be particularly effective in fostering long-term ...
openaire   +2 more sources