Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201865
M. Wu, Hongge Zhao, Xiaoyu Yan, Yun Guo, Kai Wang
Blended learning is increasingly used in college teaching, and formative evaluation has become the main method for assessing student performance. Based on the formative evaluation data of an existing course, how to model, analyze and predict the possible problems of students in the future learning process and give recommendations on learning strategy are problems worthy of in-depth study. In this paper, Apriori algorithm was used to perform association analysis on the formative evaluation data of the Fundamentals of Programming course in Nankai University, the results indicate that there are strong association rules between SPOC video scores, case study assignments scores, etc. K-Means algorithm was used to perform cluster analysis on SPOC platform scores, offline course scores and final exam scores, the results indicate that the advantages and disadvantages of students of different categories are consistent in two semesters. Finally, the clustering results of the first semester were added to the data set, Random Forest was used for feature selection, and four ensemble learning models were trained respectively to predict final exam grades. The results show that the XGBoost model works best, the accuracy of predicting the final exam grades of two semesters is 77.02% and 80.10%, respectively.
{"title":"Student Achievement Analysis and Prediction Based on the Whole Learning Process","authors":"M. Wu, Hongge Zhao, Xiaoyu Yan, Yun Guo, Kai Wang","doi":"10.1109/ICCSE49874.2020.9201865","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201865","url":null,"abstract":"Blended learning is increasingly used in college teaching, and formative evaluation has become the main method for assessing student performance. Based on the formative evaluation data of an existing course, how to model, analyze and predict the possible problems of students in the future learning process and give recommendations on learning strategy are problems worthy of in-depth study. In this paper, Apriori algorithm was used to perform association analysis on the formative evaluation data of the Fundamentals of Programming course in Nankai University, the results indicate that there are strong association rules between SPOC video scores, case study assignments scores, etc. K-Means algorithm was used to perform cluster analysis on SPOC platform scores, offline course scores and final exam scores, the results indicate that the advantages and disadvantages of students of different categories are consistent in two semesters. Finally, the clustering results of the first semester were added to the data set, Random Forest was used for feature selection, and four ensemble learning models were trained respectively to predict final exam grades. The results show that the XGBoost model works best, the accuracy of predicting the final exam grades of two semesters is 77.02% and 80.10%, respectively.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127567999","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201716
Mingxiao Lu, Peipei Gao, Hongge Zhao, Kai Wang
The O-AMAS model is an effective teaching model developed by Nankai Effective Teaching in 2017, which is guided by students' learning outcomes, and driven by the positive interactions between teachers and students. The Flipped Classroom is an effective teaching method with students as the main body, which has been proven by many researches. This paper describes the application of a new pedagogical method which combines the O-AMAS effective teaching model and the Flipped Classroom in the "Database Technology and Application" course to activate students' enthusiasm and participation in learning and improve the teaching effectiveness.
{"title":"The Application of O-AMAS Effective Teaching Model and Flipped Classroom in Database Technology and Application Course","authors":"Mingxiao Lu, Peipei Gao, Hongge Zhao, Kai Wang","doi":"10.1109/ICCSE49874.2020.9201716","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201716","url":null,"abstract":"The O-AMAS model is an effective teaching model developed by Nankai Effective Teaching in 2017, which is guided by students' learning outcomes, and driven by the positive interactions between teachers and students. The Flipped Classroom is an effective teaching method with students as the main body, which has been proven by many researches. This paper describes the application of a new pedagogical method which combines the O-AMAS effective teaching model and the Flipped Classroom in the \"Database Technology and Application\" course to activate students' enthusiasm and participation in learning and improve the teaching effectiveness.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"549 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116233087","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201671
R. Yang, Jimei Li, Meijie Du
With the rapid development of computer, big data, artificial intelligence and other technologies, the talent demand of enterprises for enterprise information system (EIS) is increasing, and various skills certification based on EIS software is also developing rapidly, so talent training and job skill analysis are crucial. At present, job competency evaluation has been widely used in enterprises, but the research of job skill analysis based on EIS is still in its infancy. Based on the operation data of the users in the EIS software, this paper constructs the job skill model and establishes the informatization index, which is conducive to objectively evaluate the operation standard and skill level of the staff in different posts, and then helps the enterprises to accurately identify the talents, helps the operators to understand their own skill level and educators teach according to their aptitude, so as to improve the quality of teaching and learning, and to effectively meet the needs of enterprises.
{"title":"Development of Job Skill Model Based on EIS—Take Purchasing Role as an Example","authors":"R. Yang, Jimei Li, Meijie Du","doi":"10.1109/ICCSE49874.2020.9201671","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201671","url":null,"abstract":"With the rapid development of computer, big data, artificial intelligence and other technologies, the talent demand of enterprises for enterprise information system (EIS) is increasing, and various skills certification based on EIS software is also developing rapidly, so talent training and job skill analysis are crucial. At present, job competency evaluation has been widely used in enterprises, but the research of job skill analysis based on EIS is still in its infancy. Based on the operation data of the users in the EIS software, this paper constructs the job skill model and establishes the informatization index, which is conducive to objectively evaluate the operation standard and skill level of the staff in different posts, and then helps the enterprises to accurately identify the talents, helps the operators to understand their own skill level and educators teach according to their aptitude, so as to improve the quality of teaching and learning, and to effectively meet the needs of enterprises.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"67 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126404430","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201746
Kun Tian, Wen Liu, Ying He, Ming Yang, Danhua Zhao
The nature of teaching lies in the instructive interactions between a teacher and a student. Consequently, the quality of teaching (or teaching effectiveness) is decided by the characteristics of both the teacher and the student. We try to build a fundamental modeling framework that captures this nature of teaching and makes it possible the formal modeling as well as the calculation and predication of teaching effectiveness. Moreover, leveraging on machine learning methods, application of the framework does not require full implementations of its models.
{"title":"On the Modeling and Predication of Teaching Effectiveness with Machine Learning","authors":"Kun Tian, Wen Liu, Ying He, Ming Yang, Danhua Zhao","doi":"10.1109/ICCSE49874.2020.9201746","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201746","url":null,"abstract":"The nature of teaching lies in the instructive interactions between a teacher and a student. Consequently, the quality of teaching (or teaching effectiveness) is decided by the characteristics of both the teacher and the student. We try to build a fundamental modeling framework that captures this nature of teaching and makes it possible the formal modeling as well as the calculation and predication of teaching effectiveness. Moreover, leveraging on machine learning methods, application of the framework does not require full implementations of its models.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126365499","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201720
Hao Wang
In recent years, with the rise of "Big Data", all kinds of industry have turned around with the help of "Internet +", and the deep integration of tourism and "Internet +" has also conformed to this trend of the times. With the advent of the mass tourism era, big data has played an increasingly important role in the tourism industry. With the development of big data technology, smart tourism has become a hot spot in tourism information construction. In addition to integrating tourism resources and strengthening infrastructure construction, how to make destination tourism marketing has become a new topic in front of the government tourism authorities.
{"title":"Research on the Application of Big Data in Smart Marketing of All-for-one Tourism","authors":"Hao Wang","doi":"10.1109/ICCSE49874.2020.9201720","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201720","url":null,"abstract":"In recent years, with the rise of \"Big Data\", all kinds of industry have turned around with the help of \"Internet +\", and the deep integration of tourism and \"Internet +\" has also conformed to this trend of the times. With the advent of the mass tourism era, big data has played an increasingly important role in the tourism industry. With the development of big data technology, smart tourism has become a hot spot in tourism information construction. In addition to integrating tourism resources and strengthening infrastructure construction, how to make destination tourism marketing has become a new topic in front of the government tourism authorities.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131759502","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201853
Ruixia Cao, Lu Sun
Machine learning has a wide range of applications in many fields, and a good application prospect makes it more urgent to carry out machine learning teaching. In the process of building machine learning courses, this paper not only follows the CDIO teaching concept, but also uses the student behavior data as the real data source of the practice link. Through refined theoretical analysis, real experimental cases and complete development process, students will master the application skills of machine learning.
{"title":"Design and Practice of Machine Learning Course Based on CDIO and Student Behavior Data","authors":"Ruixia Cao, Lu Sun","doi":"10.1109/ICCSE49874.2020.9201853","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201853","url":null,"abstract":"Machine learning has a wide range of applications in many fields, and a good application prospect makes it more urgent to carry out machine learning teaching. In the process of building machine learning courses, this paper not only follows the CDIO teaching concept, but also uses the student behavior data as the real data source of the practice link. Through refined theoretical analysis, real experimental cases and complete development process, students will master the application skills of machine learning.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131805608","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201652
Qingmin Wei, Mingyong Li, Kaiyue Xiang, Xue Qiu
The rapid development of Artificial Intelligence (AI) technology has made education enter a new era, and it also puts forward new requirements and challenges to the professional development of Information Technology(IT) teachers in primary and secondary schools. The study analyzes the connotation and status of the application of Artificial Intelligence technology in the field of education and Artificial Intelligence Education in primary and secondary schools, the impact of artificial intelligence education applications on the professional development of Information Technology teachers in primary and secondary schools, the connection between Artificial Intelligence Education and the development of Information Technology teachers in primary and secondary schools. Then, based on the above analysis, strategies for the professional development of Information Technology teachers in primary and secondary schools are proposed, which mainly include internal strategies for teachers themselves and external strategies for national policies, local policies, local education bureaus, schools, and corporate institutions. Hope that these strategies can promote the professional development of Information Technology teachers in primary and secondary schools.
{"title":"Analysis and strategies of the Professional Development of Information Technology Teachers under the Vision of Artificial Intelligence","authors":"Qingmin Wei, Mingyong Li, Kaiyue Xiang, Xue Qiu","doi":"10.1109/ICCSE49874.2020.9201652","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201652","url":null,"abstract":"The rapid development of Artificial Intelligence (AI) technology has made education enter a new era, and it also puts forward new requirements and challenges to the professional development of Information Technology(IT) teachers in primary and secondary schools. The study analyzes the connotation and status of the application of Artificial Intelligence technology in the field of education and Artificial Intelligence Education in primary and secondary schools, the impact of artificial intelligence education applications on the professional development of Information Technology teachers in primary and secondary schools, the connection between Artificial Intelligence Education and the development of Information Technology teachers in primary and secondary schools. Then, based on the above analysis, strategies for the professional development of Information Technology teachers in primary and secondary schools are proposed, which mainly include internal strategies for teachers themselves and external strategies for national policies, local policies, local education bureaus, schools, and corporate institutions. Hope that these strategies can promote the professional development of Information Technology teachers in primary and secondary schools.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131392280","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201643
Xiaonan Liu, Lina Jing, Lixin Wang, Meiling Wang
Quantum Fourier Transform is a key part of many quantum computing, and it involves phase estimation, ordering and factoring. Especially in large number decomposition, periodic data can be transformed into a normal distribution of probability amplitudes. If Quantum Fourier Transform can be implemented on a large scale, it will be a threat to the security of the current RSA cryptosystem. However, the physical implementation of quantum computers currently faces many difficulties, and it is still far away from quantum computers that can exert huge computing power. Therefore, it can only be simulated by classical computers. This article uses the supercomputer independently developed by China, Sunway TaihuLight, to simulate the Quantum Fourier Transform. Based on the heterogeneous and parallel characteristics of SW26010 processor, 46 qubits Quantum Fourier Transform are simulated using MPI, the acceleration thread library, calculation and communication hiding strategy, with the acceleration ratio reaching 6.45 times.
{"title":"Quantum Fourier Transform Simulation on Sunway TaihuLight","authors":"Xiaonan Liu, Lina Jing, Lixin Wang, Meiling Wang","doi":"10.1109/ICCSE49874.2020.9201643","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201643","url":null,"abstract":"Quantum Fourier Transform is a key part of many quantum computing, and it involves phase estimation, ordering and factoring. Especially in large number decomposition, periodic data can be transformed into a normal distribution of probability amplitudes. If Quantum Fourier Transform can be implemented on a large scale, it will be a threat to the security of the current RSA cryptosystem. However, the physical implementation of quantum computers currently faces many difficulties, and it is still far away from quantum computers that can exert huge computing power. Therefore, it can only be simulated by classical computers. This article uses the supercomputer independently developed by China, Sunway TaihuLight, to simulate the Quantum Fourier Transform. Based on the heterogeneous and parallel characteristics of SW26010 processor, 46 qubits Quantum Fourier Transform are simulated using MPI, the acceleration thread library, calculation and communication hiding strategy, with the acceleration ratio reaching 6.45 times.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133210878","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201815
Jun Qin, Sheng Liang, Yanyan Song, Ping Zong
The replica technology in cloud storage can not only maintain the high availability of the system, but also improve the overall performance of the system. This paper analyzes the limitations of the existing replica placement strategy in heterogeneous environment, and proposes a reasonable replica placement improvement strategy based on the comprehensive performance evaluation value of the node. The experimental results show that the improved replica placement strategy can make the replica distribution more reasonable and balanced on the premise of ensuring the overall availability of the system.
{"title":"Study on Replica Strategy of Big Data Storage based on Cloud Environment","authors":"Jun Qin, Sheng Liang, Yanyan Song, Ping Zong","doi":"10.1109/ICCSE49874.2020.9201815","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201815","url":null,"abstract":"The replica technology in cloud storage can not only maintain the high availability of the system, but also improve the overall performance of the system. This paper analyzes the limitations of the existing replica placement strategy in heterogeneous environment, and proposes a reasonable replica placement improvement strategy based on the comprehensive performance evaluation value of the node. The experimental results show that the improved replica placement strategy can make the replica distribution more reasonable and balanced on the premise of ensuring the overall availability of the system.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132818227","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}
Pub Date : 2020-08-01DOI: 10.1109/ICCSE49874.2020.9201885
Fan Xu, Lan Wang, Jian-Ting Gao
In recent years, artificial intelligence is changing the traditional teaching model with irresistible force. It intelligently transforms and reshapes the entire teaching process. Artificial intelligence technology as an auxiliary teaching tool and means provides unprecedented development opportunities for teaching. Under this background, the research on the development and reform of the teaching model has become very urgent. This article starts with the teaching model and technical system of educational artificial intelligence and summarizes the application content of existing artificial intelligence technology in education. At the same time, combined with the needs of the subject, some ideas of applying artificial intelligence technology to subject teaching are put forward. Expect to play a guiding role in the exploration of new teaching models in different disciplines.
{"title":"Thoughts on Application of Artificial Intelligence in Teaching of Different Disciplines","authors":"Fan Xu, Lan Wang, Jian-Ting Gao","doi":"10.1109/ICCSE49874.2020.9201885","DOIUrl":"https://doi.org/10.1109/ICCSE49874.2020.9201885","url":null,"abstract":"In recent years, artificial intelligence is changing the traditional teaching model with irresistible force. It intelligently transforms and reshapes the entire teaching process. Artificial intelligence technology as an auxiliary teaching tool and means provides unprecedented development opportunities for teaching. Under this background, the research on the development and reform of the teaching model has become very urgent. This article starts with the teaching model and technical system of educational artificial intelligence and summarizes the application content of existing artificial intelligence technology in education. At the same time, combined with the needs of the subject, some ideas of applying artificial intelligence technology to subject teaching are put forward. Expect to play a guiding role in the exploration of new teaching models in different disciplines.","PeriodicalId":350703,"journal":{"name":"2020 15th International Conference on Computer Science & Education (ICCSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129521458","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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