Intrinsic value is related to intrinsic motivation and influences learners' decisions to begin, continue, and return to learning tasks. In the context of a fully online foreign language English course, we used structural equation modeling to explore the motivation for asynchronous collaborative writing practice, motivation for video-synchronous speaking practice, course satisfaction, and the mediating effect course satisfaction has on behavioral intentions to use language learning technology. Cross-sectional survey results ( = 186) revealed that students who were motivated by asynchronous online collaborative writing were more likely to enjoy online learning in general when compared to students who reported motivation for video-synchronous online speaking practice. Moreover, the relationship between motivation for collaborative writing and behavioral intentions to use language learning technology was mediated by course satisfaction. A follow-up open-ended survey ( = 65) revealed that students held positive views for online second language writing and speaking practice overall but for distinctly different reasons. The findings are discussed in terms of their theoretical implications for modeling e-learning approaches with significance for promoting instructional training effectiveness and transformative learning.
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http://dx.doi.org/10.1007/s10639-020-10369-z | DOI Listing |
J Neurodev Disord
January 2025
Graduate Neuroscience Program, University of California, Riverside, CA, USA.
Background: Fragile X syndrome (FXS) is a leading known genetic cause of intellectual disability and autism spectrum disorders (ASD)-associated behaviors. A consistent and debilitating phenotype of FXS is auditory hypersensitivity that may lead to delayed language and high anxiety. Consistent with findings in FXS human studies, the mouse model of FXS, the Fmr1 knock out (KO) mouse, shows auditory hypersensitivity and temporal processing deficits.
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January 2025
Department of Colorectal Surgery, Ningbo Medical Center Lihuili Hospital, Ningbo, 315000, China.
Recent studies suggest the role of gut microbes in bile acid metabolism in the development and progression of colorectal cancer. However, the surveys of the association between fecal bile acid concentrations and colorectal cancer (CRC) have been inconsistent. We searched online to identify relevant cross-sectional and case-control studies published online in the major English language databases (Medline, Embase, Web of Science, AMED, and CINAHL) up to January 1, 2024.
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January 2025
Chubu Institute for Advanced Studies, Chubu University, Kasugai, Aichi, Japan.
Event-based surveillance is crucial for the early detection and rapid response to potential public health risks. In recent years, social networking services (SNS) have been recognized for their potential role in this domain. Previous studies have demonstrated the capacity of SNS posts for the early detection of health crises and affected individuals, including those related to infectious diseases.
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January 2025
Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, La Laguna, Spain.
This study investigated how exposure to Caucasian and Chinese faces influences native Mandarin-Chinese speakers' learning of emotional meanings for English L2 words. Participants were presented with English pseudowords repeatedly paired with either Caucasian faces or Chinese faces showing emotions of disgust, sadness, or neutrality as a control baseline. Participants' learning was evaluated through both within-modality (i.
View Article and Find Full Text PDFTrends Genet
January 2025
Computer Science Division, University of California, Berkeley, CA, USA; Department of Statistics, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA, USA. Electronic address:
Large language models (LLMs) are having transformative impacts across a wide range of scientific fields, particularly in the biomedical sciences. Just as the goal of natural language processing is to understand sequences of words, a major objective in biology is to understand biological sequences. Genomic language models (gLMs), which are LLMs trained on DNA sequences, have the potential to significantly advance our understanding of genomes and how DNA elements at various scales interact to give rise to complex functions.
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