Students'demand for online learning has exploded during the post-COvID-19 pandemic era.However,due to their poor learning experience,students'dropout rate and learning performance of online learning are not al...Students'demand for online learning has exploded during the post-COvID-19 pandemic era.However,due to their poor learning experience,students'dropout rate and learning performance of online learning are not always satisfactory.The technical advantages of Beyond Fifth Generation(B5G)can guarantee a good multimedia Quality of Experience(QoE).As a special case of multimedia services,online learning takes into account both the usability of the service and the cognitive development of the users.Factors that affect the Quality of Online Learning Experience(OL-QoE)become more complicated.To get over this dilemma,we propose a systematic scheme by integrating big data,Machine Learning(ML)technologies,and educational psychology theory.Specifically,we first formulate a general definition of OL-QoE by data analysis and experimental verification.This formula considers both the subjective and objective factors(i.e.,video watching ratio and test scores)that most affect OLQoE.Then,we induce an extended layer to the classic Broad Learning System(BLS)to construct an Extended Broad Learning System(EBLS)for the students'OL-QoE prediction.Since the extended layer can increase the width of the BLS model and reduce the redundant nodes of BLS,the proposed EBLS can achieve a trade-off between the prediction accuracy and computation complexity.Finally,we provide a series of early intervention suggestions for different types of students according to their predicted OL-QoE values.Through timely interventions,their OL-QoE and learning performance can be improved.Experimental results verify the effectiveness oftheproposed scheme.展开更多
Over the past few years,China’s higher education institutions have experienced remarkable growth in online teaching.However,it remains uncertain whether and how the sense of presence perceived by students affects the...Over the past few years,China’s higher education institutions have experienced remarkable growth in online teaching.However,it remains uncertain whether and how the sense of presence perceived by students affects their online learning outcomes when teachers use online teaching media for communication.This sense specifically pertains to the extent to which students perceive themselves as“real persons”and establish connections with others.Therefore,this study constructs a conceptual model elucidating the impact of presence on students’online learning outcomes and empirically examines the mechanism through which three types of presence influence students’online learning.The test results of the structural equation modeling(SEM)indicate that:(a)teaching presence,social presence,and cognitive presence all exhibit significantly positive outcomes on students’online learning outcomes;(b)these three types of presence can also indirectly and positively influence students’online learning outcomes through the mediating effect of flow experience and learning satisfaction;and(c)flow experience and learning satisfaction play a sequential mediating role in the process by which presence impacts students’online learning outcomes.We hope that the relevant research findings may contribute to unveiling the“black box”of the impact of presence on students’online learning outcomes and offer valuable insights for college educators to overcome online teaching constraints and enhance online teaching quality.展开更多
Objective:To analyze the technical indexes of students’online learning behavior analysis based on Kirkman’s evaluation model,sort out the basic indexes of online learning behavior,and extract scientific and efficien...Objective:To analyze the technical indexes of students’online learning behavior analysis based on Kirkman’s evaluation model,sort out the basic indexes of online learning behavior,and extract scientific and efficient evaluation indexes of online learning effect through statistical analysis.Methods:The online learning behavior data of Physiology of nursing students from 2021-2023 and the first semester of 22 nursing classes(3 and 4)were collected and analyzed.The preset learning behavior indexes were analyzed by multi-dimensional analysis and a correlation analysis was conducted between the indexes and the final examination scores to screen for the dominant important indexes for online learning effect evaluation.Results:The study found that the demand for online learning of nursing students from 2021-2023 increased and the effect was statistically significant.Compared with the stage assessment results,the online learning effect was statistically significant.Conclusion:The main indicators for evaluating and classifying online learning behaviors were summarized.These two indicators can help teachers predict which part of students need learning intervention,optimize the teaching process,and help students improve their learning behavior and academic performance.展开更多
To evaluate the efficacy of online learning and explore the impact of long-term use of electronic products on facial skin as well as eyes.A cross-sectional survey was conducted to 180 sophomores in Xi′an Jiaotong Uni...To evaluate the efficacy of online learning and explore the impact of long-term use of electronic products on facial skin as well as eyes.A cross-sectional survey was conducted to 180 sophomores in Xi′an Jiaotong University by cluster random sampling from September to October 2021.The questionnaire covering study condition,skin lesion and Ocular Surface Disease Index.χ_(2) test was used to compare the facial skin condition among different groups,and spearman correlation test was used to test the correlation of rank data.During online education,students′learning pressure is reduced,their autonomy is improved,and the learning efficiency is reduced.There were differences in the incidence of facial itching and papules among different groups.Duration of use of electronic products was positively correlated with the facial itching,with an r value of 0.231(P<0.05);the proportion of pigmentation in non-blue light protection groups(12.8%)was higher than that in blue light protection groups(1.7%),the difference was statistically significant(χ_(2)=8.384,P<0.05).The prevalence of dry eye among college students is 66.7%,and the proportion of moderate to severe dry eye is 34.5%.The study autonomy has been improved during online teaching.Long-term use of electronic products and no blue light protection have an impact on facial skin.Students should enhance the knowledge of skin-care and eye-care and develop better habits.展开更多
In emerging applications such as industrial control and autonomous driving,end-to-end deterministic quality of service(QoS)transmission guarantee has become an urgent problem to be solved.Internet congestion control a...In emerging applications such as industrial control and autonomous driving,end-to-end deterministic quality of service(QoS)transmission guarantee has become an urgent problem to be solved.Internet congestion control algorithms are essential to the performance of applications.However,existing congestion control schemes follow the best-effort principle of data transmission without the perception of application QoS requirements.To enable data delivery within application QoS constraints,we leverage an online learning mechanism to design Crimson,a novel congestion control algorithm in which each sender continuously observes the gap between current performance and pre-defined QoS.Crimson can change rates adaptively that satisfy application QoS requirements as a result.Across many emulation environments and real-world experiments,our proposed scheme can efficiently balance the different trade-offs between throughput,delay and loss rate.Crimson also achieves consistent performance over a wide range of QoS constraints under diverse network scenarios.展开更多
BACKGROUND The coronavirus disease 2019(COVID-19)epidemic disrupted education systems by forcing systems to shift to emergency online leaning.Online learning satisfaction affects academic achievement.Many factors affe...BACKGROUND The coronavirus disease 2019(COVID-19)epidemic disrupted education systems by forcing systems to shift to emergency online leaning.Online learning satisfaction affects academic achievement.Many factors affect online learning satisfaction.However there is little study focused on personal characteristics,mental status,and coping style when college students participated in emergency online courses.regression analyses were performed to identify factors that affected online learning satisfaction.RESULTS Descriptive findings indicated that 62.9%(994/1580)of students were satisfied with online learning.Factors that had significant positive effects on online learning satisfaction were online learning at scheduled times,strong exercise intensity,good health,regular schedule,focusing on the epidemic less than one hour a day,and maintaining emotional stability.Positive coping styles were protective factors of online learning satisfaction.Risk factors for poor satisfaction were depression,neurasthenia,and negative coping style.CONCLUSION College students with different personal characteristics,mental status,and coping style exhibited different degrees of online learning satisfaction.Our findings provide reference for educators,psychologists,and school adminis-trators to conduct health education intervention of college students during emergency online learning.展开更多
As the field of artificial intelligence continues to evolve,so too does the application of multimodal learning analysis and intelligent adaptive learning systems.This trend has the potential to promote the equalizatio...As the field of artificial intelligence continues to evolve,so too does the application of multimodal learning analysis and intelligent adaptive learning systems.This trend has the potential to promote the equalization of educational resources,the intellectualization of educational methods,and the modernization of educational reform,among other benefits.This study proposes a construction framework for an intelligent adaptive learning system that is supported by multimodal data.It provides a detailed explanation of the system’s working principles and patterns,which aim to enhance learners’online engagement in behavior,emotion,and cognition.The study seeks to address the issue of intelligent adaptive learning systems diagnosing learners’learning behavior based solely on learning achievement,to improve learners’online engagement,enable them to master more required knowledge,and ultimately achieve better learning outcomes.展开更多
The combination of online teaching and traditional offline teaching can maximize the advantages of both.Based on the blended teaching of English Reading course,39 students were selected as the research subjects to stu...The combination of online teaching and traditional offline teaching can maximize the advantages of both.Based on the blended teaching of English Reading course,39 students were selected as the research subjects to study the relationship between their online learning attitudes and their grades in the final examination.Judged from the number of times for each student to download teaching resources,the number of assignments submitted online,and the quality of the submitted assignments,each student’s attitude toward online learning was examined comprehensively,and a correlation analysis was conducted through SPSS Statistics 21.0 to explore the influence of online learning attitude on English reading performance.Through data collection and analysis of the online learning attitudes over a 16-week period,a significant positive correlation was found between the online learning attitudes and the English reading grades,indicating that the online learning attitude in the blended learning model plays a crucial role in improving the English reading skill,and students should maintain a positive attitude toward online teaching in blended learning.展开更多
Blended teaching, which integrates the advantages of online and offline teaching, has become the main direction of higher education teaching reform. In the era of education big data, research on the online learners’ ...Blended teaching, which integrates the advantages of online and offline teaching, has become the main direction of higher education teaching reform. In the era of education big data, research on the online learners’ behavior based on data mining has attracted more and more attention from higher education researchers. However, in the field of foreign language teaching, research on the relationship between online learning behaviors and learning outcomes in the blended teaching mode is still at an early stage. Taking the course College English Listening in Zhejiang Yuexiu University (ZYU) as an example, this study conducted a comprehensive data analysis of online learning behaviors of 152 students of ZYU to explore the influence of online learning behaviors on learning outcomes in the blended teaching mode by utilizing Microsoft Excel and SPSS.20 statistic software. The result shows that the number of course login, the quantity and the quality of forum replies, the number of note submission, the quality of the notes, the average score of vocabulary tests, the number of the times of taking listening tests and the average score of listening tests are all significantly and positively correlated with students’ learning outcomes, while the study does not find a correlation between students’ learning outcomes and the number of the times of taking vocabulary tests, the total length of online learning and the length of video viewing. Based on the study results, implications are put forward to give reference for the teaching design and the management of the foreign language blended courses.展开更多
An ontology and metadata for online learning resource repository management is constructed. First, based on the analysis of the use-case diagram, the upper ontology is illustrated which includes resource library ontol...An ontology and metadata for online learning resource repository management is constructed. First, based on the analysis of the use-case diagram, the upper ontology is illustrated which includes resource library ontology and user ontology, and evaluated from its function and implementation; then the corresponding class diagram, resource description framework （RDF） schema and extensible markup language （XML） schema are given. Secondly, the metadata for online learning resource repository management is proposed based on the Dublin Core Metadata Initiative and the IEEE Learning Technologies Standards Committee Learning Object Metadata Working Group. Finally, the inference instance is shown, which proves the validity of ontology and metadata in online learning resource repository management.展开更多
Nonlinear loads in the power distribution system cause non-sinusoidal currents and voltages with harmonic components.Shunt active filters(SAF) with current controlled voltage source inverters(CCVSI) are usually used t...Nonlinear loads in the power distribution system cause non-sinusoidal currents and voltages with harmonic components.Shunt active filters(SAF) with current controlled voltage source inverters(CCVSI) are usually used to obtain balanced and sinusoidal source currents by injecting compensation currents.However,CCVSI with traditional controllers have a limited transient and steady state performance.In this paper,we propose an adaptive dynamic programming(ADP) controller with online learning capability to improve transient response and harmonics.The proposed controller works alongside existing proportional integral(PI) controllers to efficiently track the reference currents in the d-q domain.It can generate adaptive control actions to compensate the PI controller.The proposed system was simulated under different nonlinear(three-phase full wave rectifier) load conditions.The performance of the proposed approach was compared with the traditional approach.We have also included the simulation results without connecting the traditional PI control based power inverter for reference comparison.The online learning based ADP controller not only reduced average total harmonic distortion by 18.41%,but also outperformed traditional PI controllers during transients.展开更多
Purpose:Opinion mining and sentiment analysis in Online Learning Community can truly reflect the students’learning situation,which provides the necessary theoretical basis for following revision of teaching plans.To ...Purpose:Opinion mining and sentiment analysis in Online Learning Community can truly reflect the students’learning situation,which provides the necessary theoretical basis for following revision of teaching plans.To improve the accuracy of topic-sentiment analysis,a novel model for topic sentiment analysis is proposed that outperforms other state-of-art models.Methodology/approach:We aim at highlighting the identification and visualization of topic sentiment based on learning topic mining and sentiment clustering at various granularitylevels.The proposed method comprised data preprocessing,topic detection,sentiment analysis,and visualization.Findings:The proposed model can effectively perceive students’sentiment tendencies on different topics,which provides powerful practical reference for improving the quality of information services in teaching practice.Research limitations:The model obtains the topic-terminology hybrid matrix and the document-topic hybrid matrix by selecting the real user’s comment information on the basis of LDA topic detection approach,without considering the intensity of students’sentiments and their evolutionary trends.Practical implications:The implication and association rules to visualize the negative sentiment in comments or reviews enable teachers and administrators to access a certain plaint,which can be utilized as a reference for enhancing the accuracy of learning content recommendation,and evaluating the quality of their services.Originality/value:The topic-sentiment analysis model can clarify the hierarchical dependencies between different topics,which lay the foundation for improving the accuracy of teaching content recommendation and optimizing the knowledge coherence of related courses.展开更多
This article is based on research conducted for the European CommissionEducation & Training 2020 working group on digital and online learning(ET2020 WG-DOL) specifically regarding policy challenges, such as thefol...This article is based on research conducted for the European CommissionEducation & Training 2020 working group on digital and online learning(ET2020 WG-DOL) specifically regarding policy challenges, such as thefollowing: 1) Targeted policy guidance on innovative and open learningenvironments under outcome;2) Proposal for a quality assurance modelfor open and innovative learning environments, its impact on specificassessment frameworks and its implication for EU recognition and transparencyinstruments. The article aims to define quality in open, flexible,and online learning, particularly in open education, open educationalresources (OER), and massive open online courses (MOOC). Hence,quality domains, characteristics, and criteria are outlined and discussed,as well as how they contribute to quality and personal learning so thatlearners can orchestrate and take responsibility for their own learningpathways. An additional goal is to identify the major stakeholders directlyinvolved in open online education and to describe their visions, communalities,and conflicts regarding quality in open, flexible, and online learning.The article also focuses on quality in periods of crisis, such as duringthe pandemic in 2020. Finally, the article discusses the rationale and needfor a model of quality in open, flexible, and online learning based on threemajor criteria for quality: excellence, impact, and implementation fromthe learner’s perspective.展开更多
In the post-Covid-19 pandemic era,it is more difficult for some Chinese schools in Europe to provide online extra classes for overseas Chinese children after school hours,as they did previously.To meet students'mu...In the post-Covid-19 pandemic era,it is more difficult for some Chinese schools in Europe to provide online extra classes for overseas Chinese children after school hours,as they did previously.To meet students'multifaceted learning needs,online extra classes teaching,including online Chinese language classes and some online art classes,is increasingly being offered as a supplement to the diversity of teaching activities in Chinese schools in Europe,with the ultimate goal of improving the learning abilities of overseas Chinese children while relieving pressure on teaching resources in schools.Children’s learning self-efficacy in online extracurricular courses has its own uniqueness,which can be considered from three dimensions,including learning confidence,learning ability,and self-assessment ability.This study aims to examine the factors influencing the self-efficacy of overseas Chinese children and to make optimization suggestions for better teaching methods.In search of that,an online questionnaire survey with 127 participants from overseas Chinese children agedtowas collected.The findings indicate that the role of learning confidence in overseas Chinese children outweighs their learning ability and self-assessment ability.Gender and age have a negligible effect on self-efficacy but have an impact on learning confidence.Chinese schools in Europe do not need to show gender differences when conducting classroom activities in online teaching to improve the online self-efficacy of Chinese children,and efforts should also be made to keep the courage of older students to trial and error.Teachers are expected to investigate more aspects of their students'personalities in future classrooms rather than sticking to a consistent and unchanging teaching model.展开更多
Background:In response to the need to mitigate the increase in Coronavirus Disease 2019(COVID-19)cases,nursing students undertake online learning in almost all nursing education institutions in Indonesia.These student...Background:In response to the need to mitigate the increase in Coronavirus Disease 2019(COVID-19)cases,nursing students undertake online learning in almost all nursing education institutions in Indonesia.These students face distinctive learning experiences,which have not yet been identified in the Indonesian context.This study aimed to explore students’experiences of online learning during the COVID-19 pandemic.Methods:We used a descriptive exploratory design.Eleven students from three nursing education institutions in Indonesia were interviewed through telephone calls or video conference applications.Results:One main theme,Gaining access in resource-limited circumstances,was developed to describe students’experience of online learning during the COVID-19 pandemic.This theme was supported by five subthemes:struggling for internet connection;becoming familiar with the applications;flexibility;supported by others;and dealing with limitations.Conclusions:This current study provides insights into what support should be provided for nursing students to manage limitations in the online learning process.展开更多
At the beginning of 2020,the“COVID-19”came out.Affected by the outbreaks,the universities have to carry out online teaching.Online learning provides students with full freedom and personalized learning space,but at ...At the beginning of 2020,the“COVID-19”came out.Affected by the outbreaks,the universities have to carry out online teaching.Online learning provides students with full freedom and personalized learning space,but at the same time,it also brings problems such as weak feelings between teachers and students and lack of learning experience.To solve these problems,this paper adopts the methods of questionnaire survey,experimental control and behavioral modeling.This paper studies how teachers’emotional support behavior affects students’learning process and learning emotion in online learning environment,and proposes that teachers’emotional support behavior is appealed and desired by students.Positive teachers’emotional support behavior can promote students’learning process and improve students’learning emotion.展开更多
Objective:This project has mainly studied the online learning engagement of undergraduate nursing students and analyzes influencing factors of online learning and teaching mode during the Novel Coronavirus(COVID-19).T...Objective:This project has mainly studied the online learning engagement of undergraduate nursing students and analyzes influencing factors of online learning and teaching mode during the Novel Coronavirus(COVID-19).This research has significant references for improving the efficiency and quality of the online learning mode of students.Methods:In this study,212 undergraduate nursing students were selected from a comprehensive university in Jilin Province by combining convenience sampling and cluster sampling methods.And these students were conducted with a general information questionnaire,Online Academic Emotion Scale,and Online Learning Engagement Scale.The influencing factors of this teaching mode were analyzed by multiple linear stepwise regression.Results:The total score of online learning engagement of undergraduate students was 53.85±7.38,which positively correlated with positive high arousal emotion and negative high arousal emotion,but weakly negatively correlated with negative low arousal emotion(r=0.661,0.246,-0.187,P<0.001).Grade,type of online class,online learning time,and positively high arousal emotion were mainly affected the online learning engagement of undergraduate nursing students,which explained 78.5%of the total variation(P<0.001).Conclusion:The online learning engagement of undergraduate nursing students was above the middle level under the background of the COVID-19 pandemic.Lectures and professors who teach undergraduate nursing students,should integrate the individuation characters of nursing students,and motivate their positively high arousal emotion to improve online learning engagement of students to ensure the quality of online teaching mode.展开更多
The method of statistical analysis is employed in this paper to research the interests of online cadre learners, including learners from administrative organizations directly governed by the provincial government, Zun...The method of statistical analysis is employed in this paper to research the interests of online cadre learners, including learners from administrative organizations directly governed by the provincial government, Zunyi city and the state-owned enterprises directly governed by the provincial government in 2011 through the courseware of Guizhou Cadre Online Learning School. The difference in willingness to study in this manner between people of differing ages is examined through data analysis.展开更多
●We examined the results of a large-scale national survey of online secondary education in China.The online survey of 33,194 high school students and 5,667 teachers has provided comprehensive and representative data ...●We examined the results of a large-scale national survey of online secondary education in China.The online survey of 33,194 high school students and 5,667 teachers has provided comprehensive and representative data regarding the quality of online education and its implementation during the pandemic.●Questionnaire surveys administered to students and teachers in different grades and comparative analysis of different cohorts revealed group heterogeneity of the online learning effect.●The findings have elucidated the emergency teaching situation in China during the pandemic,yielding targeted suggestions for school education following the resumption of classes.展开更多
Air environmental information plays an important role during plant growth and reproduction, prompt and accurate prediction of atmospheric environmental data is helpful for agricultural robots to make a timely decision...Air environmental information plays an important role during plant growth and reproduction, prompt and accurate prediction of atmospheric environmental data is helpful for agricultural robots to make a timely decision. For efficiency, an online learning method for predicting air environmental information was presented in this work. This method combines the advantages of convolutional neural network (CNN) and experience replay technique: CNN is used to extract features from raw data and predict atmospheric environmental information, experience replay technique can store environmental data over some time and update the hyperparameters of CNN. To validate the effects of this method, this online method was compared with three different predictive methods (including random forest, multi-layer perceptron, and support vector regression) using a public dataset (Jena). According to results, a suitable sample sequence size (e.g., 16) has a smaller number of training sessions and stable results, a larger replay memory size (e.g., 200) can provide enough samples to capture useful features, and 6 d of historical information is the best setting for training predictor. Compared with traditional methods, the method proposed in this study is the only method applied for various conditions.展开更多
基金supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX20_0733)Education Reform Foundation of Jiangsu Province(Grant No.2021JSJG364)+1 种基金Key Education Reform Foundation of NJUPT(Grant No.JG00220JX02,JG00218JX03,JG00215JX01,JG00214JX52)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Students'demand for online learning has exploded during the post-COvID-19 pandemic era.However,due to their poor learning experience,students'dropout rate and learning performance of online learning are not always satisfactory.The technical advantages of Beyond Fifth Generation(B5G)can guarantee a good multimedia Quality of Experience(QoE).As a special case of multimedia services,online learning takes into account both the usability of the service and the cognitive development of the users.Factors that affect the Quality of Online Learning Experience(OL-QoE)become more complicated.To get over this dilemma,we propose a systematic scheme by integrating big data,Machine Learning(ML)technologies,and educational psychology theory.Specifically,we first formulate a general definition of OL-QoE by data analysis and experimental verification.This formula considers both the subjective and objective factors(i.e.,video watching ratio and test scores)that most affect OLQoE.Then,we induce an extended layer to the classic Broad Learning System(BLS)to construct an Extended Broad Learning System(EBLS)for the students'OL-QoE prediction.Since the extended layer can increase the width of the BLS model and reduce the redundant nodes of BLS,the proposed EBLS can achieve a trade-off between the prediction accuracy and computation complexity.Finally,we provide a series of early intervention suggestions for different types of students according to their predicted OL-QoE values.Through timely interventions,their OL-QoE and learning performance can be improved.Experimental results verify the effectiveness oftheproposed scheme.
基金the project“Research on the Evaluation Mechanism of College Ideological and Political Education:A Perspective on Teacher-Student Development,”funded by Zhejiang Provincial College Ideological and Political Education Research Project.
文摘Over the past few years,China’s higher education institutions have experienced remarkable growth in online teaching.However,it remains uncertain whether and how the sense of presence perceived by students affects their online learning outcomes when teachers use online teaching media for communication.This sense specifically pertains to the extent to which students perceive themselves as“real persons”and establish connections with others.Therefore,this study constructs a conceptual model elucidating the impact of presence on students’online learning outcomes and empirically examines the mechanism through which three types of presence influence students’online learning.The test results of the structural equation modeling(SEM)indicate that:(a)teaching presence,social presence,and cognitive presence all exhibit significantly positive outcomes on students’online learning outcomes;(b)these three types of presence can also indirectly and positively influence students’online learning outcomes through the mediating effect of flow experience and learning satisfaction;and(c)flow experience and learning satisfaction play a sequential mediating role in the process by which presence impacts students’online learning outcomes.We hope that the relevant research findings may contribute to unveiling the“black box”of the impact of presence on students’online learning outcomes and offer valuable insights for college educators to overcome online teaching constraints and enhance online teaching quality.
基金Analysis and Research on Online Learning in Higher Vocational Colleges Based on Kirkpatrick Model-Taking the Course of Physiology as an Example(Project No.:D/2021/03/91)The excellent teaching team of Physiology of Suzhou Vocational College of Health Science and Technology in 2019(Project number:JXTD201912).
文摘Objective:To analyze the technical indexes of students’online learning behavior analysis based on Kirkman’s evaluation model,sort out the basic indexes of online learning behavior,and extract scientific and efficient evaluation indexes of online learning effect through statistical analysis.Methods:The online learning behavior data of Physiology of nursing students from 2021-2023 and the first semester of 22 nursing classes(3 and 4)were collected and analyzed.The preset learning behavior indexes were analyzed by multi-dimensional analysis and a correlation analysis was conducted between the indexes and the final examination scores to screen for the dominant important indexes for online learning effect evaluation.Results:The study found that the demand for online learning of nursing students from 2021-2023 increased and the effect was statistically significant.Compared with the stage assessment results,the online learning effect was statistically significant.Conclusion:The main indicators for evaluating and classifying online learning behaviors were summarized.These two indicators can help teachers predict which part of students need learning intervention,optimize the teaching process,and help students improve their learning behavior and academic performance.
文摘To evaluate the efficacy of online learning and explore the impact of long-term use of electronic products on facial skin as well as eyes.A cross-sectional survey was conducted to 180 sophomores in Xi′an Jiaotong University by cluster random sampling from September to October 2021.The questionnaire covering study condition,skin lesion and Ocular Surface Disease Index.χ_(2) test was used to compare the facial skin condition among different groups,and spearman correlation test was used to test the correlation of rank data.During online education,students′learning pressure is reduced,their autonomy is improved,and the learning efficiency is reduced.There were differences in the incidence of facial itching and papules among different groups.Duration of use of electronic products was positively correlated with the facial itching,with an r value of 0.231(P<0.05);the proportion of pigmentation in non-blue light protection groups(12.8%)was higher than that in blue light protection groups(1.7%),the difference was statistically significant(χ_(2)=8.384,P<0.05).The prevalence of dry eye among college students is 66.7%,and the proportion of moderate to severe dry eye is 34.5%.The study autonomy has been improved during online teaching.Long-term use of electronic products and no blue light protection have an impact on facial skin.Students should enhance the knowledge of skin-care and eye-care and develop better habits.
基金supported by the National Natural Science Foundation of China under Grant 62132009 and 61872211。
文摘In emerging applications such as industrial control and autonomous driving,end-to-end deterministic quality of service(QoS)transmission guarantee has become an urgent problem to be solved.Internet congestion control algorithms are essential to the performance of applications.However,existing congestion control schemes follow the best-effort principle of data transmission without the perception of application QoS requirements.To enable data delivery within application QoS constraints,we leverage an online learning mechanism to design Crimson,a novel congestion control algorithm in which each sender continuously observes the gap between current performance and pre-defined QoS.Crimson can change rates adaptively that satisfy application QoS requirements as a result.Across many emulation environments and real-world experiments,our proposed scheme can efficiently balance the different trade-offs between throughput,delay and loss rate.Crimson also achieves consistent performance over a wide range of QoS constraints under diverse network scenarios.
基金The study protocol was approved by the Ethics Committee of Hebei General University and complied strictly with ethical requirements.Ethics Review No.2020 scientific ethics No.30.
文摘BACKGROUND The coronavirus disease 2019(COVID-19)epidemic disrupted education systems by forcing systems to shift to emergency online leaning.Online learning satisfaction affects academic achievement.Many factors affect online learning satisfaction.However there is little study focused on personal characteristics,mental status,and coping style when college students participated in emergency online courses.regression analyses were performed to identify factors that affected online learning satisfaction.RESULTS Descriptive findings indicated that 62.9%(994/1580)of students were satisfied with online learning.Factors that had significant positive effects on online learning satisfaction were online learning at scheduled times,strong exercise intensity,good health,regular schedule,focusing on the epidemic less than one hour a day,and maintaining emotional stability.Positive coping styles were protective factors of online learning satisfaction.Risk factors for poor satisfaction were depression,neurasthenia,and negative coping style.CONCLUSION College students with different personal characteristics,mental status,and coping style exhibited different degrees of online learning satisfaction.Our findings provide reference for educators,psychologists,and school adminis-trators to conduct health education intervention of college students during emergency online learning.
文摘As the field of artificial intelligence continues to evolve,so too does the application of multimodal learning analysis and intelligent adaptive learning systems.This trend has the potential to promote the equalization of educational resources,the intellectualization of educational methods,and the modernization of educational reform,among other benefits.This study proposes a construction framework for an intelligent adaptive learning system that is supported by multimodal data.It provides a detailed explanation of the system’s working principles and patterns,which aim to enhance learners’online engagement in behavior,emotion,and cognition.The study seeks to address the issue of intelligent adaptive learning systems diagnosing learners’learning behavior based solely on learning achievement,to improve learners’online engagement,enable them to master more required knowledge,and ultimately achieve better learning outcomes.
文摘The combination of online teaching and traditional offline teaching can maximize the advantages of both.Based on the blended teaching of English Reading course,39 students were selected as the research subjects to study the relationship between their online learning attitudes and their grades in the final examination.Judged from the number of times for each student to download teaching resources,the number of assignments submitted online,and the quality of the submitted assignments,each student’s attitude toward online learning was examined comprehensively,and a correlation analysis was conducted through SPSS Statistics 21.0 to explore the influence of online learning attitude on English reading performance.Through data collection and analysis of the online learning attitudes over a 16-week period,a significant positive correlation was found between the online learning attitudes and the English reading grades,indicating that the online learning attitude in the blended learning model plays a crucial role in improving the English reading skill,and students should maintain a positive attitude toward online teaching in blended learning.
文摘Blended teaching, which integrates the advantages of online and offline teaching, has become the main direction of higher education teaching reform. In the era of education big data, research on the online learners’ behavior based on data mining has attracted more and more attention from higher education researchers. However, in the field of foreign language teaching, research on the relationship between online learning behaviors and learning outcomes in the blended teaching mode is still at an early stage. Taking the course College English Listening in Zhejiang Yuexiu University (ZYU) as an example, this study conducted a comprehensive data analysis of online learning behaviors of 152 students of ZYU to explore the influence of online learning behaviors on learning outcomes in the blended teaching mode by utilizing Microsoft Excel and SPSS.20 statistic software. The result shows that the number of course login, the quantity and the quality of forum replies, the number of note submission, the quality of the notes, the average score of vocabulary tests, the number of the times of taking listening tests and the average score of listening tests are all significantly and positively correlated with students’ learning outcomes, while the study does not find a correlation between students’ learning outcomes and the number of the times of taking vocabulary tests, the total length of online learning and the length of video viewing. Based on the study results, implications are put forward to give reference for the teaching design and the management of the foreign language blended courses.
基金The Advanced University Action Plan of the Minis-try of Education of China (2004XD-03).
文摘An ontology and metadata for online learning resource repository management is constructed. First, based on the analysis of the use-case diagram, the upper ontology is illustrated which includes resource library ontology and user ontology, and evaluated from its function and implementation; then the corresponding class diagram, resource description framework （RDF） schema and extensible markup language （XML） schema are given. Secondly, the metadata for online learning resource repository management is proposed based on the Dublin Core Metadata Initiative and the IEEE Learning Technologies Standards Committee Learning Object Metadata Working Group. Finally, the inference instance is shown, which proves the validity of ontology and metadata in online learning resource repository management.
文摘Nonlinear loads in the power distribution system cause non-sinusoidal currents and voltages with harmonic components.Shunt active filters(SAF) with current controlled voltage source inverters(CCVSI) are usually used to obtain balanced and sinusoidal source currents by injecting compensation currents.However,CCVSI with traditional controllers have a limited transient and steady state performance.In this paper,we propose an adaptive dynamic programming(ADP) controller with online learning capability to improve transient response and harmonics.The proposed controller works alongside existing proportional integral(PI) controllers to efficiently track the reference currents in the d-q domain.It can generate adaptive control actions to compensate the PI controller.The proposed system was simulated under different nonlinear(three-phase full wave rectifier) load conditions.The performance of the proposed approach was compared with the traditional approach.We have also included the simulation results without connecting the traditional PI control based power inverter for reference comparison.The online learning based ADP controller not only reduced average total harmonic distortion by 18.41%,but also outperformed traditional PI controllers during transients.
基金supported by the Teaching Research Major Projects of Anhui Province(2018jyxm1446)the Natural Scientific Project of Anhui Provincial Department of Education(KJ2019A0371)+1 种基金the Anhui Demonstration Experiment Training Center Project(2018sxzx58)the Demonstration Projects for Massive Open Online Course of Anhui Province(2018mooc278)。
文摘Purpose:Opinion mining and sentiment analysis in Online Learning Community can truly reflect the students’learning situation,which provides the necessary theoretical basis for following revision of teaching plans.To improve the accuracy of topic-sentiment analysis,a novel model for topic sentiment analysis is proposed that outperforms other state-of-art models.Methodology/approach:We aim at highlighting the identification and visualization of topic sentiment based on learning topic mining and sentiment clustering at various granularitylevels.The proposed method comprised data preprocessing,topic detection,sentiment analysis,and visualization.Findings:The proposed model can effectively perceive students’sentiment tendencies on different topics,which provides powerful practical reference for improving the quality of information services in teaching practice.Research limitations:The model obtains the topic-terminology hybrid matrix and the document-topic hybrid matrix by selecting the real user’s comment information on the basis of LDA topic detection approach,without considering the intensity of students’sentiments and their evolutionary trends.Practical implications:The implication and association rules to visualize the negative sentiment in comments or reviews enable teachers and administrators to access a certain plaint,which can be utilized as a reference for enhancing the accuracy of learning content recommendation,and evaluating the quality of their services.Originality/value:The topic-sentiment analysis model can clarify the hierarchical dependencies between different topics,which lay the foundation for improving the accuracy of teaching content recommendation and optimizing the knowledge coherence of related courses.
文摘This article is based on research conducted for the European CommissionEducation & Training 2020 working group on digital and online learning(ET2020 WG-DOL) specifically regarding policy challenges, such as thefollowing: 1) Targeted policy guidance on innovative and open learningenvironments under outcome;2) Proposal for a quality assurance modelfor open and innovative learning environments, its impact on specificassessment frameworks and its implication for EU recognition and transparencyinstruments. The article aims to define quality in open, flexible,and online learning, particularly in open education, open educationalresources (OER), and massive open online courses (MOOC). Hence,quality domains, characteristics, and criteria are outlined and discussed,as well as how they contribute to quality and personal learning so thatlearners can orchestrate and take responsibility for their own learningpathways. An additional goal is to identify the major stakeholders directlyinvolved in open online education and to describe their visions, communalities,and conflicts regarding quality in open, flexible, and online learning.The article also focuses on quality in periods of crisis, such as duringthe pandemic in 2020. Finally, the article discusses the rationale and needfor a model of quality in open, flexible, and online learning based on threemajor criteria for quality: excellence, impact, and implementation fromthe learner’s perspective.
基金This paper is funded by research project of National College Student Innovation and Entrepreneurship Project of Wenzhou University in 2022,“A Study of Teaching Practices and Validity of Online Extra Classes of Chinese Schools in Europe”under Project No.202210351019 and research project of Wenzhou University Student Scientific Research Project(“Challenge Cup”Special Project)in 2022“Qiaozhiqiao-Chinese Ethnic Identity Education of Overseas Chinese Children”under Project No.2022kx220.
文摘In the post-Covid-19 pandemic era,it is more difficult for some Chinese schools in Europe to provide online extra classes for overseas Chinese children after school hours,as they did previously.To meet students'multifaceted learning needs,online extra classes teaching,including online Chinese language classes and some online art classes,is increasingly being offered as a supplement to the diversity of teaching activities in Chinese schools in Europe,with the ultimate goal of improving the learning abilities of overseas Chinese children while relieving pressure on teaching resources in schools.Children’s learning self-efficacy in online extracurricular courses has its own uniqueness,which can be considered from three dimensions,including learning confidence,learning ability,and self-assessment ability.This study aims to examine the factors influencing the self-efficacy of overseas Chinese children and to make optimization suggestions for better teaching methods.In search of that,an online questionnaire survey with 127 participants from overseas Chinese children agedtowas collected.The findings indicate that the role of learning confidence in overseas Chinese children outweighs their learning ability and self-assessment ability.Gender and age have a negligible effect on self-efficacy but have an impact on learning confidence.Chinese schools in Europe do not need to show gender differences when conducting classroom activities in online teaching to improve the online self-efficacy of Chinese children,and efforts should also be made to keep the courage of older students to trial and error.Teachers are expected to investigate more aspects of their students'personalities in future classrooms rather than sticking to a consistent and unchanging teaching model.
基金supported by Universitas Tanjungpura Pontianak,Indonesia (No. 2367/UN22.9/PG/2020)
文摘Background:In response to the need to mitigate the increase in Coronavirus Disease 2019(COVID-19)cases,nursing students undertake online learning in almost all nursing education institutions in Indonesia.These students face distinctive learning experiences,which have not yet been identified in the Indonesian context.This study aimed to explore students’experiences of online learning during the COVID-19 pandemic.Methods:We used a descriptive exploratory design.Eleven students from three nursing education institutions in Indonesia were interviewed through telephone calls or video conference applications.Results:One main theme,Gaining access in resource-limited circumstances,was developed to describe students’experience of online learning during the COVID-19 pandemic.This theme was supported by five subthemes:struggling for internet connection;becoming familiar with the applications;flexibility;supported by others;and dealing with limitations.Conclusions:This current study provides insights into what support should be provided for nursing students to manage limitations in the online learning process.
基金Higher Education Society of Shaanxi Province 2019 Higher Education Science Research Project(XGH19120:Wisdom Teaching Scene in Cloud model evaluation system key technology research)2019 school-level Higher Education Science Research Project(GJY-2019-YB-20).
文摘At the beginning of 2020,the“COVID-19”came out.Affected by the outbreaks,the universities have to carry out online teaching.Online learning provides students with full freedom and personalized learning space,but at the same time,it also brings problems such as weak feelings between teachers and students and lack of learning experience.To solve these problems,this paper adopts the methods of questionnaire survey,experimental control and behavioral modeling.This paper studies how teachers’emotional support behavior affects students’learning process and learning emotion in online learning environment,and proposes that teachers’emotional support behavior is appealed and desired by students.Positive teachers’emotional support behavior can promote students’learning process and improve students’learning emotion.
文摘Objective:This project has mainly studied the online learning engagement of undergraduate nursing students and analyzes influencing factors of online learning and teaching mode during the Novel Coronavirus(COVID-19).This research has significant references for improving the efficiency and quality of the online learning mode of students.Methods:In this study,212 undergraduate nursing students were selected from a comprehensive university in Jilin Province by combining convenience sampling and cluster sampling methods.And these students were conducted with a general information questionnaire,Online Academic Emotion Scale,and Online Learning Engagement Scale.The influencing factors of this teaching mode were analyzed by multiple linear stepwise regression.Results:The total score of online learning engagement of undergraduate students was 53.85±7.38,which positively correlated with positive high arousal emotion and negative high arousal emotion,but weakly negatively correlated with negative low arousal emotion(r=0.661,0.246,-0.187,P<0.001).Grade,type of online class,online learning time,and positively high arousal emotion were mainly affected the online learning engagement of undergraduate nursing students,which explained 78.5%of the total variation(P<0.001).Conclusion:The online learning engagement of undergraduate nursing students was above the middle level under the background of the COVID-19 pandemic.Lectures and professors who teach undergraduate nursing students,should integrate the individuation characters of nursing students,and motivate their positively high arousal emotion to improve online learning engagement of students to ensure the quality of online teaching mode.
文摘The method of statistical analysis is employed in this paper to research the interests of online cadre learners, including learners from administrative organizations directly governed by the provincial government, Zunyi city and the state-owned enterprises directly governed by the provincial government in 2011 through the courseware of Guizhou Cadre Online Learning School. The difference in willingness to study in this manner between people of differing ages is examined through data analysis.
文摘●We examined the results of a large-scale national survey of online secondary education in China.The online survey of 33,194 high school students and 5,667 teachers has provided comprehensive and representative data regarding the quality of online education and its implementation during the pandemic.●Questionnaire surveys administered to students and teachers in different grades and comparative analysis of different cohorts revealed group heterogeneity of the online learning effect.●The findings have elucidated the emergency teaching situation in China during the pandemic,yielding targeted suggestions for school education following the resumption of classes.
基金funded by the National Key Research and Development Program(Grant No.2022YFD2002202)Beijing Innovation Consortium of Agriculture Research System(BAIC08-2024-FQ04)+2 种基金Key Laboratory of Agricultural Sensors,Ministry of Agriculture and Rural Affairs(Grant No.PT2024-46)China Postdoctoral Science Foundation(Grant No.BX20230048)Postdoctoral fund of Beijing Academy of Agriculture and Forestry Sciences(Grant No.2023-ZZ-025).
文摘Air environmental information plays an important role during plant growth and reproduction, prompt and accurate prediction of atmospheric environmental data is helpful for agricultural robots to make a timely decision. For efficiency, an online learning method for predicting air environmental information was presented in this work. This method combines the advantages of convolutional neural network (CNN) and experience replay technique: CNN is used to extract features from raw data and predict atmospheric environmental information, experience replay technique can store environmental data over some time and update the hyperparameters of CNN. To validate the effects of this method, this online method was compared with three different predictive methods (including random forest, multi-layer perceptron, and support vector regression) using a public dataset (Jena). According to results, a suitable sample sequence size (e.g., 16) has a smaller number of training sessions and stable results, a larger replay memory size (e.g., 200) can provide enough samples to capture useful features, and 6 d of historical information is the best setting for training predictor. Compared with traditional methods, the method proposed in this study is the only method applied for various conditions.
