Mobile learning is a kind of learning mode by using mobile devices, and it is an indispensable way of learning strategy in colleges and universities. The authors conducted the interviews and questionnaires about the teaching situation, learning strategies, using of network resources, and so on. Next, the authors checked and verified carefully the feedback data from classroom teaching. In the process of investigation, the students were divided into two groups. The authors analyzed the mean and standard deviation of the two groups of data tables. According to the data reliability analysis, exploratory factor analysis, significance analysis, the authors propose the teaching mode of “one heart, two sides and six links(OHTSSL)” based on mobile learning strategy. In order to construct new cognitive content and train students' innovation ability, teacher and students must implement the mobile learning strategy in classroom teaching. Teacher and students execute teaching process of six links based on OHTSSL teaching mode.
{"title":"Mobile Learning Strategy Based on Principal Component Analysis","authors":"Qiongjie Kou, Quanyou Zhang, Laiqun Xu, Yaohui Li, Yong Feng, Huiting Wei","doi":"10.4018/ijisss.311862","DOIUrl":"https://doi.org/10.4018/ijisss.311862","url":null,"abstract":"Mobile learning is a kind of learning mode by using mobile devices, and it is an indispensable way of learning strategy in colleges and universities. The authors conducted the interviews and questionnaires about the teaching situation, learning strategies, using of network resources, and so on. Next, the authors checked and verified carefully the feedback data from classroom teaching. In the process of investigation, the students were divided into two groups. The authors analyzed the mean and standard deviation of the two groups of data tables. According to the data reliability analysis, exploratory factor analysis, significance analysis, the authors propose the teaching mode of “one heart, two sides and six links(OHTSSL)” based on mobile learning strategy. In order to construct new cognitive content and train students' innovation ability, teacher and students must implement the mobile learning strategy in classroom teaching. Teacher and students execute teaching process of six links based on OHTSSL teaching mode.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133629931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integration of education and network technology will increase students' diversified and personalized learning methods. In view of the convenience of online learning, this paper analyzes the situation and methods of online learning. Analytic hierarchy process (AHP) is used to analyze the online learning model, and the education evaluation system is constructed by using relevant evaluation indexes, so as to improve the efficiency of students' online learning. Furthermore, the hierarchical structure of online learning model is analyzed, and a comprehensive learning index system is constructed. The experimental results are as follows: (1) In the weight of evaluation indicators, the learning method of brushing online course is the favorite way of students, and the weight is as high as 0.5. (2) In the application of university teaching system, the popularity of rain classroom teaching method accounts for 3.84% of the relevant weight. (3) In consistency test and comprehensive weight analysis, the weight of the whole evaluation index is less than 0.1.
{"title":"Construction and Analysis of Evaluation Index System of College Students' Online Learning Based on Analytic Hierarchy Processes","authors":"L. Cheng","doi":"10.4018/ijisss.311858","DOIUrl":"https://doi.org/10.4018/ijisss.311858","url":null,"abstract":"The integration of education and network technology will increase students' diversified and personalized learning methods. In view of the convenience of online learning, this paper analyzes the situation and methods of online learning. Analytic hierarchy process (AHP) is used to analyze the online learning model, and the education evaluation system is constructed by using relevant evaluation indexes, so as to improve the efficiency of students' online learning. Furthermore, the hierarchical structure of online learning model is analyzed, and a comprehensive learning index system is constructed. The experimental results are as follows: (1) In the weight of evaluation indicators, the learning method of brushing online course is the favorite way of students, and the weight is as high as 0.5. (2) In the application of university teaching system, the popularity of rain classroom teaching method accounts for 3.84% of the relevant weight. (3) In consistency test and comprehensive weight analysis, the weight of the whole evaluation index is less than 0.1.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114072627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Online classrooms have been widely used during the COVID-19 epidemic. However, due to the intuitive, practical, and emotional characteristics of dance majors, online classroom teaching still has certain limitations. Through the advantages of online classroom teaching during the epidemic prevention and control stage, the problems faced and their solutions are summarized and reflected. The article analyzes the advantages, existing problems, and solutions of online dance teaching, and designs an online dance learning platform quality assessment. After using the online learning platform, students' enthusiasm for dance learning has improved a lot, and students are more interested in dance teaching. The satisfaction of the effect has increased from 76% to 85%, and the detection efficiency of the platform is very high. The experimental results also show that in the context of the new crown epidemic, the use of online learning platforms can not only stimulate students' interest in learning, but also improve the quality of teaching.
{"title":"Teaching Effect Analysis and Behavior Detection of an Online Dance Learning Platform in the Context of COVID-19","authors":"Guangle Yin, Lu Wang","doi":"10.4018/ijisss.311859","DOIUrl":"https://doi.org/10.4018/ijisss.311859","url":null,"abstract":"Online classrooms have been widely used during the COVID-19 epidemic. However, due to the intuitive, practical, and emotional characteristics of dance majors, online classroom teaching still has certain limitations. Through the advantages of online classroom teaching during the epidemic prevention and control stage, the problems faced and their solutions are summarized and reflected. The article analyzes the advantages, existing problems, and solutions of online dance teaching, and designs an online dance learning platform quality assessment. After using the online learning platform, students' enthusiasm for dance learning has improved a lot, and students are more interested in dance teaching. The satisfaction of the effect has increased from 76% to 85%, and the detection efficiency of the platform is very high. The experimental results also show that in the context of the new crown epidemic, the use of online learning platforms can not only stimulate students' interest in learning, but also improve the quality of teaching.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131345926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to grasp the employment psychology of college students more accurately and solve their inner anxiety, the Apripri algorithm of association rules constructs the correlation analysis model of college students' mental health and employment based on data mining. The diagnosis accuracy of association rules for network fault is 98.47%, and the diagnosis time is 0.21s. In the performance comparison experiments of different models, the mean value is above 0.8, the precision is 0.86, the precision is 0.84, the recall is 0.84, and the F1 value is 0.87. It shows that the means of this paper meet the research requirements. In the comparative experiments of different algorithm performance indicators, the accuracy of the mean is 0.87, the precision is 0.85, the recall is 0.84, and the F1 value is 0.88. The means of this paper meet the research requirements.
{"title":"Research on the Relationship Between College Students' Mental Health and Employment Based on Data Mining","authors":"Bin Liu","doi":"10.4018/ijisss.311860","DOIUrl":"https://doi.org/10.4018/ijisss.311860","url":null,"abstract":"In order to grasp the employment psychology of college students more accurately and solve their inner anxiety, the Apripri algorithm of association rules constructs the correlation analysis model of college students' mental health and employment based on data mining. The diagnosis accuracy of association rules for network fault is 98.47%, and the diagnosis time is 0.21s. In the performance comparison experiments of different models, the mean value is above 0.8, the precision is 0.86, the precision is 0.84, the recall is 0.84, and the F1 value is 0.87. It shows that the means of this paper meet the research requirements. In the comparative experiments of different algorithm performance indicators, the accuracy of the mean is 0.87, the precision is 0.85, the recall is 0.84, and the F1 value is 0.88. The means of this paper meet the research requirements.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132822874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Hu, Ifrah Malik, M. Irshad, S. M. Noman, Ghadeer W. Khader, A. Murthy
Cultural disparities in the educational process are being examined as science and technology rapidly change, as well as large-scale transformations in the economy. Support in the form of funds is being given to graduate education in Canada. In contrast, China began a little later but has also been focusing on education. As a result, the comparison focuses on similarities and differences. The authors examine and contrast the differences in the educational processes across history to see if there are any common threads. One of the most fundamental differences is the assessment dynamics that have molded the beliefs and processes that are used on various scales. When talking about assessment culture, the authors are talking about how it may help students learn and succeed. However, despite the high levels of migration across nations like China, the United States, and Canada, little is known about the variety of evaluation methods kids encounter as they migrate from one environment to another.
{"title":"Cross-Cultural Educational Disparities Between China and North America Based on Science and Technology Revolutions","authors":"B. Hu, Ifrah Malik, M. Irshad, S. M. Noman, Ghadeer W. Khader, A. Murthy","doi":"10.4018/ijisss.313924","DOIUrl":"https://doi.org/10.4018/ijisss.313924","url":null,"abstract":"Cultural disparities in the educational process are being examined as science and technology rapidly change, as well as large-scale transformations in the economy. Support in the form of funds is being given to graduate education in Canada. In contrast, China began a little later but has also been focusing on education. As a result, the comparison focuses on similarities and differences. The authors examine and contrast the differences in the educational processes across history to see if there are any common threads. One of the most fundamental differences is the assessment dynamics that have molded the beliefs and processes that are used on various scales. When talking about assessment culture, the authors are talking about how it may help students learn and succeed. However, despite the high levels of migration across nations like China, the United States, and Canada, little is known about the variety of evaluation methods kids encounter as they migrate from one environment to another.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131050848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Innovative technology represented by artificial intelligence drives the change of educational concept and practice, the transformation of learning environment and teaching methods to intelligence, and online learning enters the era of learner sovereignty. In this paper, rough set algorithm is used to build an online learning quality evaluation index system, and online learning quality and satisfaction are evaluated and analyzed based on artificial intelligence. The results show that the accuracy of rough set algorithm is the highest, and the recall rate of rough set algorithm is the highest in different data sets, showing an overall upward trend, the highest recall rate is 93.58%. The weight percentages of the first-level indicators are curriculum environment experience (15%), of curriculum content experience (38%), of curriculum activity experience (26%), curriculum interaction experience (6%) and learning effect experience(15%). The corresponding evaluation scores are reflected accordingly, which can objectively describe the online quality evaluation.
{"title":"Analysis and Satisfaction Evaluation of Online Learning Based on Artificial Intelligence","authors":"Huang Li","doi":"10.4018/ijisss.311856","DOIUrl":"https://doi.org/10.4018/ijisss.311856","url":null,"abstract":"Innovative technology represented by artificial intelligence drives the change of educational concept and practice, the transformation of learning environment and teaching methods to intelligence, and online learning enters the era of learner sovereignty. In this paper, rough set algorithm is used to build an online learning quality evaluation index system, and online learning quality and satisfaction are evaluated and analyzed based on artificial intelligence. The results show that the accuracy of rough set algorithm is the highest, and the recall rate of rough set algorithm is the highest in different data sets, showing an overall upward trend, the highest recall rate is 93.58%. The weight percentages of the first-level indicators are curriculum environment experience (15%), of curriculum content experience (38%), of curriculum activity experience (26%), curriculum interaction experience (6%) and learning effect experience(15%). The corresponding evaluation scores are reflected accordingly, which can objectively describe the online quality evaluation.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129389466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blended online English learning has become a way to expand English outside the classroom. In the future, the blended learning approach allows students to learn English knowledge without the constraints of time, place and teacher subjects in traditional classroom teaching. However, there are still many problems in online English teaching in colleges and universities. The top three learning evaluation methods are: online exams, classroom assignments, and online answering tasks. Other learning evaluation methods are arranged in descending order. They are to evaluate their own English learning, to draw a conceptual map of learning knowledge, and to accept the teacher's opinion for advice. The performance of the three models has declined, and the performance of the online learning teaching model is still the highest among the three models. The accuracy of the online learning teaching model is 73.81%, indicating that the performance of online learning and teaching is the best.
{"title":"Construction of a Multi-Dimensional Evaluation System of English Online Learning Teaching Quality Based on Blended Learning","authors":"Lina Wang, Leiming Shi","doi":"10.4018/ijisss.311855","DOIUrl":"https://doi.org/10.4018/ijisss.311855","url":null,"abstract":"Blended online English learning has become a way to expand English outside the classroom. In the future, the blended learning approach allows students to learn English knowledge without the constraints of time, place and teacher subjects in traditional classroom teaching. However, there are still many problems in online English teaching in colleges and universities. The top three learning evaluation methods are: online exams, classroom assignments, and online answering tasks. Other learning evaluation methods are arranged in descending order. They are to evaluate their own English learning, to draw a conceptual map of learning knowledge, and to accept the teacher's opinion for advice. The performance of the three models has declined, and the performance of the online learning teaching model is still the highest among the three models. The accuracy of the online learning teaching model is 73.81%, indicating that the performance of online learning and teaching is the best.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131306843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the rapid development of neural network has been widely used in major research areas, this paper will neural network convolution layer structure into the importance of students' mental health and influencing factors. In order to analyze the influencing factors of students' mental health, this paper analyzes the mental health status of different students from the perspective of neural network. Firstly, the main definitions and concepts of students' mental health are put forward, and the methods of evaluating and measuring mental health are analyzed. Secondly, the related structure of neural network and two different neural network model algorithms are described in detail, and the forward propagation and backward propagation algorithms of neural network are proposed (which provide support for the data research through neural network later). Finally, the correlation function of neural network is used to analyze the influencing factors of contemporary students' mental health.
{"title":"Analysis of the Importance and Influence of Student Mental Health Based on Neural Networks","authors":"Pinni Liu","doi":"10.4018/ijisss.311857","DOIUrl":"https://doi.org/10.4018/ijisss.311857","url":null,"abstract":"With the rapid development of neural network has been widely used in major research areas, this paper will neural network convolution layer structure into the importance of students' mental health and influencing factors. In order to analyze the influencing factors of students' mental health, this paper analyzes the mental health status of different students from the perspective of neural network. Firstly, the main definitions and concepts of students' mental health are put forward, and the methods of evaluating and measuring mental health are analyzed. Secondly, the related structure of neural network and two different neural network model algorithms are described in detail, and the forward propagation and backward propagation algorithms of neural network are proposed (which provide support for the data research through neural network later). Finally, the correlation function of neural network is used to analyze the influencing factors of contemporary students' mental health.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131584450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The enrollment expansion of colleges and universities and the acceleration of today's social process bring fierce competition to students. Colleges and universities should attach great importance to the mental health and employment anxiety of graduate students. In order to better explore the relationship between them, this paper uses artificial intelligence (AI) to evaluate students' psychology. The results show that: (1) When the crossover probability P value is less than 1, the psychology tends to be stable, and the emotion simulation conforms to the law of emotion change. (2) The accuracy of this model is higher than 82%, and the weighted fuzzy reasoning method can effectively analyze psychological symptoms. (3) After iteration, CNN has different recognition degrees for six emotions. (4) Finally, according to the emotional analysis given by the model, the source of students' psychological problems is discussed, and it is found that these students have different degrees of bad academic behavior; while they are anxious about employment, the employment rate is not satisfactory.
{"title":"Application of Artificial Intelligence in Academic Mental Health and Employment Evaluation","authors":"Xi Zhang","doi":"10.4018/ijisss.311861","DOIUrl":"https://doi.org/10.4018/ijisss.311861","url":null,"abstract":"The enrollment expansion of colleges and universities and the acceleration of today's social process bring fierce competition to students. Colleges and universities should attach great importance to the mental health and employment anxiety of graduate students. In order to better explore the relationship between them, this paper uses artificial intelligence (AI) to evaluate students' psychology. The results show that: (1) When the crossover probability P value is less than 1, the psychology tends to be stable, and the emotion simulation conforms to the law of emotion change. (2) The accuracy of this model is higher than 82%, and the weighted fuzzy reasoning method can effectively analyze psychological symptoms. (3) After iteration, CNN has different recognition degrees for six emotions. (4) Finally, according to the emotional analysis given by the model, the source of students' psychological problems is discussed, and it is found that these students have different degrees of bad academic behavior; while they are anxious about employment, the employment rate is not satisfactory.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130145526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For further research of steam pressure aerated concrete board carrying capacity, puts forward construction on the basis of deep learning autoclaved aerated concrete board pressure performance research methods. Through the autoclaved aerated concrete the bearing capacity of single correlation coefficient, the relationship between the nodal force and node displacement and the relationship between them, the calculation of the autoclaved aerated concrete stiffness, obtain the autoclaved aerated concrete board yield condition. The linear buckling and nonlinear buckling of the AUTOclaved aerated concrete sandwich panel are analyzed, and the bearing capacity of the autoclaved aerated concrete sandwich panel is calculated to realize the bearing capacity analysis. The test results show that this method can effectively improve the bearing stability of autoclaved aerated concrete sandwich.
{"title":"Study on Bearing Capacity of Autoclaved Aerated Concrete Partition Board Based on Deep Learning","authors":"Q. Jiao","doi":"10.4018/ijisss.290546","DOIUrl":"https://doi.org/10.4018/ijisss.290546","url":null,"abstract":"For further research of steam pressure aerated concrete board carrying capacity, puts forward construction on the basis of deep learning autoclaved aerated concrete board pressure performance research methods. Through the autoclaved aerated concrete the bearing capacity of single correlation coefficient, the relationship between the nodal force and node displacement and the relationship between them, the calculation of the autoclaved aerated concrete stiffness, obtain the autoclaved aerated concrete board yield condition. The linear buckling and nonlinear buckling of the AUTOclaved aerated concrete sandwich panel are analyzed, and the bearing capacity of the autoclaved aerated concrete sandwich panel is calculated to realize the bearing capacity analysis. The test results show that this method can effectively improve the bearing stability of autoclaved aerated concrete sandwich.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131273086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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