This study is a systematic review of 20 years of research on the usage of virtual reality (VR) in K‐12 and higher education settings, which aims to consolidate, evaluate, and communicate evidence ...that can inform both the theory and practice of VR‐based instruction. A total of 149 articles were selected from three major academic databases using search strings and manual screening protocols. The literature analysis emphasized four interrelated aspects of VR‐based instruction: instructional context, instructional design, technological affordances, and research findings. The results revealed evolving trends in the VR literature in terms of publication patterns, pedagogical assumptions, equipment usage, and research methodologies, as well as the contextual factors behind VR adoption in education. Additionally, a meta‐analysis was conducted to examine the efficacy of VR‐based instruction, with results indicating an overall medium effect and several moderating factors. Finally, practical implications and a future research agenda for VR‐based instruction are discussed.
Lay Description
What is currently known about the subject matter
VR is a promising educational technology with several learning benefits.
Research findings on VR‐based education have been conditional and inconclusive.
Contemporary research on VR in K‐12 and higher education settings lacks a comprehensive review and meta‐analysis.
What this paper adds
This paper systematically reviewed 20 years of empirical research on VR application in K‐12 and higher education.
This paper revealed evolving trends in the VR literature in terms of publication patterns, pedagogical assumptions, and equipment usage.
This paper synthesised the key pedagogical and technological features of VR interventions.
This paper reported an overall medium effect size of VR‐based instruction and several moderating factors.
Implications of this study for practitioners
Decision to adopt VR technology should be based on the careful assessment of learning domains and tasks.
Embedded functions for learning assessment, collaboration, and data collection are recommended for future VR interventions.
Research in VR is needed with focus on advanced technology, cross‐disciplinary comparison, holistic instructional process, and cost‐benefit analysis.
The increasing prevalence of mental health issues among children and adolescents has prompted a growing number of researchers and practitioners to explore digital technology interventions, which ...offer convenience, diversity, and proven effectiveness in addressing such problems. However, the existing literature reveals a significant gap in comprehensive reviews that consolidate findings and discuss the potential of digital technologies in enhancing mental health.
To clarify the latest research progress on digital technology to promote mental health in the past decade (2013-2023), we conducted two studies: a systematic review and meta-analysis. The systematic review is based on 59 empirical studies identified from three screening phases, with basic information, types of technologies, types of mental health issues as key points of analysis for synthesis and comparison. The meta-analysis is conducted with 10 qualified experimental studies to determine the overall effect size of digital technology interventions and possible moderating factors.
The results revealed that (1) there is an upward trend in relevant research, comprising mostly experimental and quasi-experimental designs; (2) the common mental health issues include depression, anxiety, bullying, lack of social emotional competence, and mental issues related to COVID-19; (3) among the various technological interventions, mobile applications (apps) have been used most frequently in the diagnosis and treatment of mental issues, followed by virtual reality, serious games, and telemedicine services; and (4) the meta-analysis results indicated that digital technology interventions have a moderate and significant effect size (
= 0.43) for promoting mental health.
Based on these findings, this study provides guidance for future practice and research on the promotion of adolescent mental health through digital technology.
https://inplasy.com/inplasy-2023-12-0004/, doi: 10.37766/inplasy2023.12.0004.
Polyamines (PAs) markedly affect the cereal’s grain filling characteristics under drought stress. But little is known that the regulatory mechanism that governs this process. So, in the present ...study, drought was imposed, and exogenous spermidine (Spd) was applied at anthesis. The grain filling characteristics of and gene expression in the grains were measured. The research purpose of this study was to investigate whether and how the PAs regulated the grain filling in wheat under drought stress. In the present study, external Spd markedly relieved the inhibitory action of drought stress on grain filling. Moreover, RNA-seq analysis revealed that the effects of drought and exogenous Spd on grain filling in wheat were strongly related to protein processing in the endoplasmic reticulum, phenylalanine metabolism, hormone signaling, and starch and sucrose metabolism. In addition, under drought stress, the exogenous Spd significantly promoted the synthesis of cytokinin (CTK) and starch in wheat grains of plants. In contrast, exogenous Spd significantly decreased ethylene (ETH) synthesis in the grains of plants under drought stress. Beside this, exogenous Spd application notably promoted the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) and decreased the malondialdehyde (MDA) content in the grains of plants under drought stress. In summary, the promoting action of Spd on the grain filling characteristics in wheat under drought stress was notably related to an increase in endogenous zeatin (Z) + zeatin riboside (ZR) contents, the synthesis of starch from sucrose, the activities of antioxidant enzymes and a decrease in ETH synthesis in the grains.
Background
As climate change events become more frequent, drought is an increasing threat to agricultural production and food security. Crop rhizosphere microbiome and root exudates are critical ...regulators for drought adaptation, yet our understanding on the rhizosphere bacterial communities and root exudate composition as affected by drought stress is far from complete. In this study, we performed 16S rRNA gene amplicon sequencing and widely targeted metabolomic analysis of rhizosphere soil and root exudates from two contrasting rice genotypes (Nipponbare and Luodao 998) exposed to drought stress.
Results
A reduction in plant phenotypes was observed under drought, and the inhibition was greater for roots than for shoots. Additionally, drought exerted a negligible effect on the alpha diversity of rhizosphere bacterial communities, but obviously altered their composition. In particular, drought led to a significant enrichment of Actinobacteria but a decrease in Firmicutes. We also found that abscisic acid in root exudates was clearly higher under drought, whereas lower jasmonic acid and
L
-cystine concentrations. As for plant genotypes, variations in plant traits of the drought-tolerant genotype Luodao 998 after drought were smaller than those of Nipponbare. Interestingly, drought triggered an increase in
Bacillus
, as well as an upregulation of most organic acids and a downregulation of all amino acids in Luodao 998. Notably, both Procrustes analysis and Mantel test demonstrated that rhizosphere microbiome and root exudate metabolomic profiles were highly correlated. A number of differentially abundant genera responded to drought and genotype, including
Streptomyces
,
Bacillus
and some members of Actinobacteria, were significantly associated with organic acid and amino acid contents in root exudates. Further soil incubation experiments showed that
Streptomyces
was regulated by abscisic acid and jasmonic acid under drought.
Conclusions
Our results reveal that both drought and genotype drive changes in the compositions of rice rhizosphere bacterial communities and root exudates under the greenhouse condition, and that organic acid exudation and suppression of amino acid exudation to select specific rhizosphere bacterial communities may be an important strategy for rice to cope with drought. These findings have important implications for improving the adaptability of rice to drought from the perspective of plant–microbe interactions.
The response of plants to waterlogging stress is a complex process, with ethylene playing a crucial role as a signaling molecule. However, it remains unclear how ethylene is initially triggered in ...response to waterlogging stress when plants are continuously waterlogged for less than 12 hours. Here, we have shown that ethylene-induced autophagy leads to the degradation of damaged mitochondria (the main organelles producing reactive oxygen species (ROS)) to reduce ROS production during oxidative stress in
, which improves the survival rate of root cells in the early stages of waterlogging stress. Waterlogging stress activated ethylene-related genes, including
,
,
,
, and
, and ethylene content of plants increased significantly within 24 h of continuous waterlogging. As stress duration increased, increased amounts of ROS accumulated in
roots, and the activity of antioxidant enzymes initially increased and then decreased. Concurrently, the level of ethylene-induced autophagy, which participates in antioxidant defense, is higher in wild-type plants than in the octuple
mutant
(
). Exogenous application of 1-aminocyclopropanecarboxylic acid (ACC), resulted in a more pronounced manifestation of autophagy in the stele of
roots. Compared with the waterlogging treatment group or the ACC treatment group, the waterlogging + ACC treatment can induce autophagy to occur earlier and expand the autophagic range to the epidermis of
roots. Overall, our results provide insight into the important role of ethylene-induced autophagy in enhancing the antioxidative capacity of
during the early stages of waterlogging stress. Furthermore, we suggest ethylene as a potential candidate for mitigating the deleterious effects caused by waterlogging in
.
To investigate the current situation of sense of security, psychological capital and job performance of medical staff in Guangdong Province, and to explore the mediating role of psychological capital ...on the relationship between sense of security and job performance of medical staff.
In this study, 969 health care workers were selected from February 2023 to April 2023 from 37 hospitals in Guangdong Province, China, using purposive sampling method. The Sense of Security Scale for Medical Staff (SSS-MS), psychological capital scale (PCS) in Chinese version and the Chinese version of job performance scale (JPS) were used in this study. We use SPSS 26.0 for statistical analysis and Amos 24.0 for structural equation modeling (SEM). The control variables entering SEM were selected by regression analysis. SEM analysis confirmed psychological capital scale's mediating function in the link between work performance scale and Sense of Security.
The overall SSS-MS, PCS, and JPS scores were 67.42 ± 16.136, 87.06 ± 15.04, and 77.87 ± 10.50, respectively. The results of Pearson's correlation analysis showed that there was a positive relationship between PCS and JPS (
= 0.722,
< 0.01), SSS-MS and JPS (
= 0.312,
< 0.01), and SSS-MS and PCS (
= 0.424,
< 0.01). PCS demonstrated a fully mediating influence on the link between medical workers' SSS-MS and JPS, according to structural equation modeling.
The JPS of medical personnel in Guangdong Province is at a medium level, with much room for improvement. PCS is positively impacted by a sense of security. There is a supportive correlation between PCS, JPS, and SSS-MS. Furthermore, PCS fully mediates the relationship between medical staff members' JPS and their SSS-MS. The Job Diamond-Resource model and Conservation of Resource theory are further validated and supplemented by the findings of this study, which also gives managers a theoretical foundation for enhancing medical staff performance.
The dual-channel graph convolutional neural networks based on hybrid features jointly model the different features of networks, so that the features can learn each other and improve the performance ...of various subsequent machine learning tasks. However, current dual-channel graph convolutional neural networks are limited by the number of convolution layers, which hinders the performance improvement of the models. Graph convolutional neural networks superimpose multi-layer graph convolution operations, which would occur in smoothing phenomena, resulting in performance decreasing as the increasing number of graph convolutional layers. Inspired by the success of residual connections on convolutional neural networks, this paper applies residual connections to dual-channel graph convolutional neural networks, and increases the depth of dual-channel graph convolutional neural networks. Thus, a dual-channel deep graph convolutional neural network (D2GCN) is proposed, which can effectively avoid over-smoothing and improve model performance. D2GCN is verified on CiteSeer, DBLP, and SDBLP datasets, the results show that D2GCN performs better than the comparison algorithms used in node classification tasks.
This study provides a comprehensive review of the application of virtual reality (VR) in social and emotional learning (SEL) for children and adolescents over the past decade (January 2013-May 2023), ...with a specific interest in the relations between their technological and instructional design features. A search in Web of Science resulted in 32 relevant articles that were then manually screened. Coding analysis was conducted from four perspectives: participant characteristics, research design, technological features, and instructional design. The analysis provides insights into the VR literature regarding publication trends, target populations, technological features, instructional scenarios, and tasks. To test the effectiveness of VR interventions for promoting SEL, a meta-analysis was also conducted, which revealed an overall medium effect size and significant moderating effects of SEL disorder type and instructional task. Finally, based on the research results, the practical implications of and future research directions for applying VR in SEL were discussed.
At present, the research on complex social networks has attracted extensive attention from scholars, and community detection is an important research direction in the study of network structure. ...Network data is often high-dimensional and very large, which makes it very difficult to process. Therefore, it is of great significance for community detection to represent network structure with low-dimensional vector. And many real world social networks contain overlapping communities. In this paper, we propose an overlapping community detection method based on network representation learning and density peaks, called NRLDP. First, it uses network representation learning technology to represent the unweighted network or weighted network with low-dimensional vectors. Then, it applies the density peaks clustering algorithm to overlapping community detection, uses cosine similarity to calculate the distance between nodes, and improves the local density calculation method. Finally, it selects the core node according to the relative distance and local density, and allocates the remaining nodes to achieve overlapping community detection of unweighted network or weighted network. Compared with relevant community detection methods on real world social networks and synthetic networks of LFR Benchmark, the results of the experiment show that our proposed approach is effective and accurate.
PDF
