Effects of a Technology-Supported Decision, Reflection, and Interaction Approach on Nursing Students' Learning Achievement and Self-Efficacy in Professional Training: A Pilot Study.

In professional training, it is important to provide students with opportunities to make judgments on practical cases. However, most training courses are conducted in a one-to-many teaching mode, and it is not easy to consider the needs of individual students. In this study, a technology-supported Decision, Reflection, and Interaction (DRI)-based professional training approach is proposed to cope with this problem for those courses aiming at fostering students' competence in making correct judgments when facing real cases. To verify the effectiveness of the proposed method, an experiment was conducted. Two classes of 38 students from a nursing school were the participants. One class was an experimental group using the DRI-based professional training approach, and the other class was the control group using the conventional technology-assisted training approach. The experimental results showed that applying the proposed approach significantly improved the students' learning achievement and self-efficacy more than the conventional technology-assisted approach. In addition, based on the interview results, the students generally believed that learning through the DRI-based professional training approach benefited them from several perspectives, including "increasing the value of activities", "enhancing the planning and expensive capacity of conspicuous approaches", "promoting decision-making", "improving learning reflection", and "providing students with personalized interaction".

Effects of robot-assisted digital storytelling on hospitalized children's communication during the COVID-19 pandemic.

This study proposed a robot-assisted digital storytelling approach to reduce hospitalized children's anxiety about intravenous injections and to improve their therapeutic communication and therapeutic engagement. In order to verify the effectiveness of the robot-assisted digital storytelling approach, a randomized controlled study was implemented. A total of 47 children from a regional hospital were randomly assigned to an experimental group (n = 21) and a control group (n = 26). The experimental group adopted the robot-assisted digital storytelling approach in health education for intravenous injections, while the control group received video-based health education. The study results indicated that the proposed robot-assisted digital storytelling approach not only reduced the children's anxiety, but also had positive effects on children's communication about intravenous injections, emotions during hospitalization, and therapeutic engagement. As a consequence, it is suggested that educators and researchers consider adopting robot-assisted digital storytelling to facilitate nursing clinical health education for children.

Critical research trends of mobile technology-supported English language learning: A review of the top 100 highly cited articles.

Around the world, the number of English speakers and the significance of the English language are constantly increasing. Among various technology-supported instructional styles, Mobile Learning (M-Learning) has been recognized as a promising approach to enhance students' competencies and skills in the English language. By examining previous literature, a number of reviews have been performed to investigate the role of M-learning in the English language. However, none of these studies has highlighted the trends, opportunities, and challenges identified in the most cited articles that focused solely on the English language. Therefore, to address these limitations, this study performed a review of the top 100 most cited articles, published between 2007 and 2020, indexed by the Web of Science, and addressing the English language only. The results revealed that most research in Mobile English Language Learning (M-ELL) followed an experimental design and employed a single mobile learning implementation. Additionally, the current study identified a number of research areas that require additional research attention. For example, further research is needed among students learning from home, more qualitative research is needed, and additional research is required to improve students' higher-order thinking skills. The outcomes of this study provide a reference to researchers and educators who intend to use mobile technologies in the area of language education, especially in the context of the English language.

Research Trends in Artificial Intelligence-Associated Nursing Activities Based on a Review of Academic Studies Published From 2001 to 2020.

The present study referred to the technology-based learning model to conduct a systematic review of the dimensions of nursing activities, research samples, research methods, roles of artificial intelligence, applied artificial intelligence algorithms, evaluation measure of algorithms, and research foci. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses procedure, this study obtained and analyzed a total of 102 high-quality artificial intelligence-associated nursing activities studies published from 2001 to 2020 in the Web of Science database. The results showed: (1) In terms of nursing activities, nursing management was explored the most, followed by nursing assessment; (2) quantitative methods were most frequently adopted in artificial intelligence-associated nursing activities studies to investigate issues related to patients, followed by nursing staff; (3) the most adopted roles of artificial intelligence in artificial intelligence-associated nursing activities studies were profiling and prediction, followed by assessment and evaluation; (4) artificial intelligence-associated nursing activities studies frequently mixed applied artificial intelligence algorithms and evaluation measure of algorithms; (5) in the dimension of research foci, most studies mainly paid attention to the design or evaluation of the artificial intelligence systems/instruments, followed by investigating the correlation and affect issues. Based on the findings, several recommendations are raised as a reference for future researchers, educators, and policy makers.

Bibliometric analysis of core competencies associated nursing management publications.

AIMS: This study aimed to identify high-impact papers on global nursing to determine and analyse the publication of articles on core competencies in nursing-related journals and the research trends in the era of globalization. BACKGROUND: Bibliometrics has been shown to be an effective method for analysing publications. Through bibliometrics, nursing managers and researchers can understand the trends of high-impact international nursing core competencies research, identify mainstream research directions and obtain relevant knowledge and information, thereby facilitating the translation of research outcomes into nursing management practice. EVALUATION: The study adopted bibliometric analysis and the VOSviewer software to explore dynamic publication trends and analyse the current situation of nursing research from a comprehensive development perspective, which was realized by searching for nursing core competencies papers in the Web of Science (WoS) database, calculating citations and determining the trends of the most influential papers. KEY ISSUES: Nursing core competencies research grew rapidly between 1997 and 2022. Countries with the most core competencies publications were the United States, England, Australia and Canada. The Journal of Nursing Management has attracted substantial attention from researchers worldwide. Education, Management and Nurses were the most frequently used keywords in the study. A total of 534 papers were retrieved from the WoS database with the main research fields, including nursing, business economics, public environmental occupational health and health care science services. CONCLUSION: Equipping nursing graduates with core competencies has always been an important goal of global medical and nursing education. This study analysed papers across 35 years, most of which were published in the Journal of Nursing Management. In addition, the study identified some of the main research topics of nursing management, such as the integration of education with nursing management and the cultivation of nurses' core competencies. The study also provides a fresh review of highly cited articles. The results of the study show that high-quality articles play the role of improving both the quality and the quantity of related research. By analysing the trends of the research on core competencies, this study lays a bibliometric foundation for researchers regarding international journals, hot topics and relevant fields. In addition, the highly cited articles reveal new perspectives for the nursing field, providing inspiration for nursing management and education researchers. IMPLICATIONS FOR NURSING MANAGEMENT: This study provides scholars and managers with an overview of the current situation of nursing management research and the development of benchmark journals. The study provides researchers not only with a better understanding of various international journals, allowing them to transition out of traditional thinking in the era of science and technology, but also with innovative thinking by combining research with nursing management. The results of this study invite nursing managers to study relevant topics of core competencies and integrate information technology to education, management and nurses, thereby contributing to nursing management and educational research.

An MDRE approach to promoting students' learning performances in the era of the pandemic: A quasi-experimental design.

Educators have indicated the need to foster students' ability to solve problems by acquiring up-to-date knowledge as well as promoting their competences for making decisions from diverse perspectives based on the acquired knowledge. Traditional courses mainly use lecture-based instruction without providing sufficient opportunities for students to practice and interact with the teacher; therefore, it is difficult to deliver such up-to-date knowledge via traditional instruction, not to mention fostering students' critical thinking. In this study, the Mobile technology-supported Decision, Reflection and Exercise (MDRE) model is proposed to address this problem. Moreover, a learning system is developed based on the proposed approach. To evaluate the effectiveness of the proposed approach, a quasi-experiment was conducted in a university with a two-group pretest posttest design to assess participants' learning achievement, critical thinking and learning satisfaction. The participants were two classes of undergraduate students. One class with 37 students was the experimental group learning with the MDRE learning approach, whereas the other class with 37 students was the control group learning with the conventional technology-based learning approach. Analysis of covariance was performed to evaluate the effect of the intervention on the target outcomes. It was found that the experimental group showed better learning achievement, critical thinking and learning satisfaction than the control group. This implies that the MDRE approach has good potential in helping learners think from diverse perspectives and promoting their learning performance and engagement, which is important in higher education aimed at fostering students' competence of acquiring up-to-date knowledge for solving problems.

A scholarly network of AI research with an information science focus: Global North and Global South perspectives.

This paper primarily aims to provide a citation-based method for exploring the scholarly network of artificial intelligence (AI)-related research in the information science (IS) domain, especially from Global North (GN) and Global South (GS) perspectives. Three research objectives were addressed, namely (1) the publication patterns in the field, (2) the most influential articles and researched keywords in the field, and (3) the visualization of the scholarly network between GN and GS researchers between the years 2010 and 2020. On the basis of the PRISMA statement, longitudinal research data were retrieved from the Web of Science and analyzed. Thirty-two AI-related keywords were used to retrieve relevant quality articles. Finally, 149 articles accompanying the follow-up 8838 citing articles were identified as eligible sources. A co-citation network analysis was adopted to scientifically visualize the intellectual structure of AI research in GN and GS networks. The results revealed that the United States, Australia, and the United Kingdom are the most productive GN countries; by contrast, China and India are the most productive GS countries. Next, the 10 most frequently co-cited AI research articles in the IS domain were identified. Third, the scholarly networks of AI research in the GN and GS areas were visualized. Between 2010 and 2015, GN researchers in the IS domain focused on applied research involving intelligent systems (e.g., decision support systems); between 2016 and 2020, GS researchers focused on big data applications (e.g., geospatial big data research). Both GN and GS researchers focused on technology adoption research (e.g., AI-related products and services) throughout the investigated period. Overall, this paper reveals the intellectual structure of the scholarly network on AI research and several applications in the IS literature. The findings provide research-based evidence for expanding global AI research.

The effectiveness of the virtual patient-based social learning approach in undergraduate nursing education: A quasi-experimental study.

BACKGROUND: In nursing education, knowledge and competence in conducting physical assessments are crucial. Therefore, physical assessment knowledge has become a fundamental and essential education program for nursing students. However, most of the current nursing courses are taught via a didactic teaching approach, making it difficult for students to think deeply about relevant issues due to the lack of interaction and context. This may, in turn, have an impact on learning effectiveness and clinical judgment. OBJECTIVE: A virtual patient (VP)-based social learning approach is proposed to enhance nursing students' performance and clinical judgment in education programs. DESIGN: A quasi-experiment method was adopted to evaluate the effectiveness of the proposed approach. PARTICIPANTS: A total of 40 senior nursing students participated in the study (VP-based social learning approach group = 20, control group = 20). METHODS: The study involved a pre- and post-test to examine students' learning achievements, self-efficacy, and communication skills. The experimental group adopted the VP-based learning approach, while the control group adopted the conventional didactic learning approach. ANCOVA was employed to compare the performances of the two groups. RESULTS: The experimental results indicate that using a VP for learning can enhance students' learning achievements, self-efficacy, and communication skills. In addition, based on the analysis of the results, students generally believed that learning with a VP makes learning more enjoyable. CONCLUSION: The VP-based social learning approach would be an effective strategy to train nursing students who have limited opportunities to experience real clinical situations, in particular during the COVID-19 pandemic.

Factors influencing university teachers' use of a mobile technology-enhanced teaching (MTT) platform.

The main purpose of this study was to examine the critical factors influencing university teachers' use of a mobile technology-enhanced teaching (MTT) platform during the new coronavirus (COVID-19) epidemic. An integrated model with multiple factors drawing from the theoretical models and learning theories was proposed in this study to examine university teachers' intentions to use an MTT platform. The multiple factors included the individual factor (e.g., growth mindset, help seeking, and self-efficacy), the social factor (e.g., social norms), and the technological acceptance factor (e.g., perceived usefulness and perceived ease of use). The survey method was used to collect data on university teachers' perceptions of the MTT platform use, and a two-step structural equation modeling approach was used for the data analysis. Based on the path analysis of a total of 214 valid responses, the results identified that growth mindset, help seeking, and self-efficacy from the individual factor, as well as perceived usefulness from the technology acceptance factor were the significant determinants of university teachers' intentions to adopt the MTT. The contributions of this study are twofold. First, the proposed model was derived from multiple literature sources, providing a sound theoretical foundation to understand MTT platform use from an academic angle. Second, university teachers' viewpoints are a unique observation of their actual platform use, providing practical insights into the improvement and maintenance of MTT-related platforms for all educators. The findings are especially valuable during the post-COVID-19 era.

A Mobile-Assisted Peer Assessment Approach for Evidence-Based Nursing Education.

Students who learn evidence-based nursing can assist the healthcare team to make proper medical decisions and provide patients with valuable advice, thus optimizing the quality of patient care in specific situations. In clinical work, nursing staff members participate in decision making by searching for relevant empirical nursing literature, a basic ability required to enter clinical practice. In traditional instruction, nursing students are taught the Problem, Intervention, Comparison, and Outcome method to learn to use library resources and gather empirical nursing knowledge for decision making. However, it is a challenge for most students to have sufficient practice to make decisions correctly and to have opportunities to perceive medical cases from diverse perspectives. Therefore, we propose a peer assessment-based Problem, Intervention, Comparison, and Outcome approach to help nursing students locate correct evidence and make appropriate decisions about patient care. We performed an experiment with our approach in a nursing university training program. The experimental results reveal that the subjects learning with the proposed approach show better evidence-based nursing knowledge, learning attitude, and critical thinking ability than those learning with the traditional approach.

Directions of the 100 most cited nursing student education research: A bibliometric and co-citation network analysis.

AIMS: To identify and analyze the 100 most cited articles on nursing student education (NSE) that were published in nursing journals. BACKGROUND: The citation frequency of an article indicates its scientific impact. Analyzing highly cited articles on NSE enabled researchers to identify mainstream research types and acquire relevant information and knowledge. DESIGN: A retrospective bibliometric analysis with co-citation network analysis. DATA SOURCES: We searched for journal articles on NSE from the Web of Science, and analyzed the 100 most cited articles (date of search: June 3, 2020). REVIEW METHODS: The theme, article type, journal, country, source of institutional articles, and publication year were counted and analyzed. The citation relationships among the most 100 cited articles of NSE were calculated and visualized. RESULTS: Articles included in this study were mostly empirical quantitative studies with a cross-sectional design, and were published in international nursing journals between 2000 and 2020. Their authors were mostly from the United States and the United Kingdom. According to the co-citation network analysis, four main research directions were identified: workplace mental health, simulation learning, spiritual care, and medication administration. CONCLUSION: Workplace mental health was the major research topic on NSE. This research topic has spanned two decades (2000-2020). These articles were mainly published in the Journal of Advanced Nursing and Nurse Education Today. Some recent research topics, such as simulation learning and spiritual care were also identified. Findings provide a fresh review of the highly cited NSE articles, including the visualization of the NSE network.

Knowledge Maps: an Online Tool for Knowledge Mapping with Automated Feedback.

Concept and knowledge maps have been shown to improve students' learning by emphasising meaningful relationships between phenomena. A user-friendly online tool that enables assessment of students' maps with automated feedback might therefore have significant benefits for learning. For that purpose, we developed an online software platform known as Knowledge Maps. Two pilot studies were performed to evaluate the usability and efficacy of Knowledge Maps. Study A demonstrated significantly improved perceptions of learning after using Knowledge Maps to learn pathology. Study B showed significant improvement between pre-test and post-test scores in an anatomy course. These preliminary studies indicate that this software is readily accepted and may have potential benefits for learning.

Torque generation through the random movement of an asymmetric rotor: A potential rotational mechanism of the γ subunit of F(1)-ATPase.

The rotation of the γ subunit of F(1)-ATPase is stochastic, processive, unidirectional, reversible through an external torque, and stepwise with a slow rotation. We propose a mechanism that can explain these properties of the rotary molecular motor, and that can determine the direction of rotation. The asymmetric structures of the γ subunit, both at the tip of the shaft (C and N termini) and at the part (ε subunit) protruding from the α(3)ß(3) subunits, are critical. The torque required for stochastic rotation is generated from the impulsive reactive force due to the random collisions between the γ subunit and the quasihexagonal α(3)ß(3) subunits. The rotation is the result of the random motion of the confined asymmetric γ subunit. The steps originate from the chemical reactions of the γ subunit and physical interaction between the γ subunit and the flexible protrusions of the α(3)ß(3) subunits. An external torque as well as a configurational modification in the γ subunit (the central rotor) can reverse the rotational direction. We demonstrate the applicability of the mechanism to a macroscopic simulation system, which has the essential ingredients of the F(1)-ATPase structure, by reproducing the dynamic properties of the rotation.

Entropic force on granular chains self-extracting from one-dimensional confinement.

The entropic forces on the self-retracting granular chains, which are confined in channels with different widths, are determined. The time dependence of the length of chain remaining in the channel Lin(t) is measured. The entropic force is treated as the only parameter in fitting the solution of the nonlinear equation of motion of Lin(t) to the experimental data. The dependence of the entropic force on the width of the confining channel can be expressed as a power-law with an exponent of 1.3, which is consistent with the previous theoretical predictions for the entropy loss due to confinement.

Gate effects on DNA translocation through silicon dioxide nanopore.

The effects of gate voltage on the translocation of DNA molecules through a nanopore are studied. A twenty-fold increase in the translocation time is observed with a positive gate voltage applied, without changing too much of the ionic current. The amplitude of the current blockage by the DNA molecules was reduced by roughly the same factor. At the same time, the number of the blocking events decreases significantly. The applied gate voltage also modulates the scatter plot of the amplitude of the current blockage against the dwell time. The observations are consistent with the recent theoretical results.

A pilot study on conducting mobile learning activities for clinical nursing courses based on the repertory grid approach.

In clinical nursing courses, students are trained to identify the status of the target patients. The mastery of such ability and skills is very important since patients frequently need to be cared for immediately. In this pilot study, a repertory grid-oriented clinical mobile learning system is developed for a nursing training program. With the assistance of the mobile learning system, the nursing school students are able to learn in an authentic learning scenario, in which they can physically face the target patients, with the personal guidance and supplementary materials from the learning system to support them. To show the effectiveness of this innovative approach, an experiment has been conducted on the "respiratory system" unit of a nursing course. The experimental results show that the innovative approach is helpful to students in improving their learning achievements. Moreover, from the questionnaire surveys, it was found that most students showed favorable attitudes toward the usage of the mobile learning system and their participation in the training program.

Collapse kinetics of vibrated granular chains.

The kinetics of the collapse of the coil state into condensed states is studied with vibrated granular chain composed of N metal beads partially immersed in water. The radius of gyration of the chain, R(g) is measured. For short chains (N < 140), disk-like condensed state is formed and R(g) decreases with time such that the function ΔR(g)(2) (≡ R(g)(2) - R(g)(2)(∞)) = A e(-t/τ), where the relaxation time τ follows a power-law dependence on the chain length N with an exponent γ = 1.9 ± 0.2. For the chains with length N ≥ 300, rod-like clusters are observed during the initial stage of collapse and R(g)(2) = R(g)(2)(0) - Bt(ß), with ß = 0.6 ± 0.1. In the coarsening stage, the exponential dependence of ΔR(g)(2) on time still holds, however, the relaxation time τ fluctuates and has no simple dependence on N. Furthermore, the time dependence of the averaged radius of gyration of the individual clusters, R(g,cl) can be described by the theory of Lifshitz and Slyozov. A peak in the structure function of long chains is observed in the initial stage of the collapse transition. The collapse transition in the bead chains is a first order phase transition. However, features of the spinodal decomposition are also observed.

A Delphi-based approach to developing expert systems with the cooperation of multiple experts.

Knowledge acquisition has been a critical bottleneck in building knowledge-based systems. In past decades, several methods and systems have been proposed to cope with this problem. Most of these methods and systems were proposed to deal with the acquisition of domain knowledge from single expert. However, as multiple experts may have different experiences and knowledge on the same application domain, it is necessary to elicit and integrate knowledge from multiple experts in building an effective expert system. Moreover, the recent literature has depicted that "time" is an important parameter that might significantly affect the accuracy of inference results of an expert system; therefore, while discussing the elicitation of domain expertise from multiple experts, it becomes an challenging and important issue to take the "time" factor into consideration. To cope with these problems, in this study, we propose a Delphi-based approach to eliciting knowledge from multiple experts. An application on the diagnosis of Severe Acute Respiratory Syndrome has depicted the superiority of the novel approach.