The relationship between learning environment characteristics and academic engagement of 777 Grade 6 children located in 41 learning environments was explored. Questionnaires were used to tap learning environment perceptions of children, their academic engagement, and their ethnic-cultural background. The basis of the learning environment questionnaire was the International System for Teacher Observation and Feedback (ISTOF). Factor analysis indicated three factors: the teacher as a helpful and good instructor (having good instructional skills, clear instruction), the teacher as promoter of active learning and differentiation, and the teacher as manager and organizer of classroom activities. Multilevel analysis indicated that about 12% of the differences in engagement between children was related to the learning environment. All the mentioned learning environment characteristics mattered, but the teacher as a helpful, good instructor was most important followed by the teacher as promoter of active learning and differentiation.
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http://dx.doi.org/10.2466/09.10.11.PR0.109.4.259-284 | DOI Listing |
Sci Rep
January 2025
Department of Artificial Intelligence and Data Science, College of Computer Science and Engineering, University of Hail, Hail, Saudi Arabia.
In the present digital scenario, the explosion of Internet of Things (IoT) devices makes massive volumes of high-dimensional data, presenting significant data and privacy security challenges. As IoT networks enlarge, certifying sensitive data privacy while still employing data analytics authority is vital. In the period of big data, statistical learning has seen fast progressions in methodological practical and innovation applications.
View Article and Find Full Text PDFIn cybersecurity, anomaly detection in tabular data is essential for ensuring information security. While traditional machine learning and deep learning methods have shown some success, they continue to face significant challenges in terms of generalization. To address these limitations, this paper presents an innovative method for tabular data anomaly detection based on large language models, called "Tabular Anomaly Detection via Guided Prompts" (TAD-GP).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, PA, USA.
Auditory perception requires categorizing sound sequences, such as speech or music, into classes, such as syllables or notes. Auditory categorization depends not only on the acoustic waveform, but also on variability and uncertainty in how the listener perceives the sound - including sensory and stimulus uncertainty, the listener's estimated relevance of the particular sound to the task, and their ability to learn the past statistics of the acoustic environment. Whereas these factors have been studied in isolation, whether and how these factors interact to shape categorization remains unknown.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Computer Science, College of Computer and Information Sciences, King Saud University, 11543, Riyadh, Saudi Arabia.
Understanding the nuanced emotions and points of view included in user-generated content remains challenging, even though text data analysis for mental health is a crucial instrument for assessing emotional well-being. Most current models neglect the significance of integrating viewpoints in comprehending mental health in favor of single-task learning. To offer a more thorough knowledge of mental health, in this study, we present an Opinion-Enhanced Hybrid BERT Model (Opinion-BERT), built to handle multi-task learning for simultaneous sentiment and status categorization.
View Article and Find Full Text PDFNat Commun
January 2025
Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute & Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, P. R. China.
The unsatisfactory ionic conductivity of solid polymer electrolytes hinders their practical use as substitutes for liquid electrolytes to address safety concerns. Although various plasticizers have been introduced to improve lithium-ion conduction kinetics, the lack of microenvironment understanding impedes the rational design of high-performance polymer electrolytes. Here, we design a class of Hofmann complexes that offer continuous two-dimensional lithium-ion conduction channels with functional ligands, creating highly conductive electrolytes.
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