Pub Date : 2021-11-01DOI: 10.1109/ITME53901.2021.00101
Jie Yang, Hong Wang
In recent years, with the development of artificial intelligence and information technology, we are gradually stepping into the era of big data, in which education-related data has developed sufficiently in terms of quantity and content. To be able to use machine learning techniques to assist educators to help improve the current quality of education and teaching, more and more researchers have started to data-mine educational data. In this paper, various algorithms of machine learning are applied to the field of education to process the data of students' teaching performance and then model it using various algorithms of machine learning to predict the students' performance and provide some suggestions to the teachers to improve the students' performance. The main contributions of this paper are as follows: Firstly, this paper carries out necessary preprocessing operations on the original data to remove some dirty data or missing data. Then, a variety of machine learning algorithms are used to model students' academic performance. By comparing the prediction accuracy, recall rate, and F1 score of the model, the Gradient Boosting Decision Tree Classifier is finally obtained as the optimal model. We then integrated the three best machine learning models as the base models and proposed a new Stacking learning method with better results. Finally, this paper analyzes the interpretability of the Gradient Boosting Decision Tree Classifier, evaluates the importance of different characteristics, and finally concludes that “Visited resources”, “Raised hand”, “Student Absence Days”, and “Viewing announcements” are the most important factors affecting students' performance. This model has an advanced effect and good interpretability.
{"title":"Interpretability Analysis of Academic Achievement Prediction Based on Machine Learning","authors":"Jie Yang, Hong Wang","doi":"10.1109/ITME53901.2021.00101","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00101","url":null,"abstract":"In recent years, with the development of artificial intelligence and information technology, we are gradually stepping into the era of big data, in which education-related data has developed sufficiently in terms of quantity and content. To be able to use machine learning techniques to assist educators to help improve the current quality of education and teaching, more and more researchers have started to data-mine educational data. In this paper, various algorithms of machine learning are applied to the field of education to process the data of students' teaching performance and then model it using various algorithms of machine learning to predict the students' performance and provide some suggestions to the teachers to improve the students' performance. The main contributions of this paper are as follows: Firstly, this paper carries out necessary preprocessing operations on the original data to remove some dirty data or missing data. Then, a variety of machine learning algorithms are used to model students' academic performance. By comparing the prediction accuracy, recall rate, and F1 score of the model, the Gradient Boosting Decision Tree Classifier is finally obtained as the optimal model. We then integrated the three best machine learning models as the base models and proposed a new Stacking learning method with better results. Finally, this paper analyzes the interpretability of the Gradient Boosting Decision Tree Classifier, evaluates the importance of different characteristics, and finally concludes that “Visited resources”, “Raised hand”, “Student Absence Days”, and “Viewing announcements” are the most important factors affecting students' performance. This model has an advanced effect and good interpretability.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"71 1","pages":"475-479"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80546912","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 : 2021-11-01DOI: 10.1109/ITME53901.2021.00078
Haizhu Wu, Cailin Li, Shaowei Qin, Lifeng Zhao
Long ncRNAs (IncRNAs) play essential regulatory roles in almost all biological processes by modulating gene expression at the transcriptional and posttranscriptional levels. Post-translational modification (PTM) also plays critical roles in regulating gene expression and protein function. To study the role of PTM-associated IncRNAs in the genesis of Populus euphratica Oliver heterophyll, we analyzed the four heteromorphic leaves of P. euphratica using miRNA-seq and RNA-seq. Then based on the function of IncRNA targets, the identified IncRNAs were enriched by GO analysis. Finally, according to ceRNA theory, the IncRNA-miRNA-mRNA networks were constructed in P. euphratica heterophyll genesis. It was found that 84 IncRNAs regulated PTM by antagonizing 51 miRNAs, and these RNAs could coregulate the genesis of P. euphratica heterophyll through mainly protein phosphorylation modification and ubiquitination. Our results can provide a comprehensive landscape of IncRNA regulatory roles in plant morphogenesis.
{"title":"Network analysis of lncRNAs involved in protein modification in the occurrence of Populus euphratica Oliv. heteromorphic leaves","authors":"Haizhu Wu, Cailin Li, Shaowei Qin, Lifeng Zhao","doi":"10.1109/ITME53901.2021.00078","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00078","url":null,"abstract":"Long ncRNAs (IncRNAs) play essential regulatory roles in almost all biological processes by modulating gene expression at the transcriptional and posttranscriptional levels. Post-translational modification (PTM) also plays critical roles in regulating gene expression and protein function. To study the role of PTM-associated IncRNAs in the genesis of Populus euphratica Oliver heterophyll, we analyzed the four heteromorphic leaves of P. euphratica using miRNA-seq and RNA-seq. Then based on the function of IncRNA targets, the identified IncRNAs were enriched by GO analysis. Finally, according to ceRNA theory, the IncRNA-miRNA-mRNA networks were constructed in P. euphratica heterophyll genesis. It was found that 84 IncRNAs regulated PTM by antagonizing 51 miRNAs, and these RNAs could coregulate the genesis of P. euphratica heterophyll through mainly protein phosphorylation modification and ubiquitination. Our results can provide a comprehensive landscape of IncRNA regulatory roles in plant morphogenesis.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"1 1","pages":"352-356"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72773742","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 : 2021-11-01DOI: 10.1109/ITME53901.2021.00011
P. Zhao
With the development of science and technology and the development of human demand and investment demand, the scale of engineering construction is getting bigger and bigger. The ensuing problem is that the complexity and difficulty of the project has increased, and the quality requirements have also increased. Traditional management methods can no longer meet the needs of infrastructure management; with the rapid development of computer technology and information technology, it is inevitable to introduce both in project management. This paper focuses on the research of the project management information system based on the adaptive ant colony algorithm, combines the adaptive ant colony algorithm with the project management information system, optimizes the current project management information system, and then designs the system for verification. It is concluded from the experimental results that the algorithm proposed in this paper is effective.
{"title":"Engineering Management Information System Based on Adaptive Ant Colony Algorithm","authors":"P. Zhao","doi":"10.1109/ITME53901.2021.00011","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00011","url":null,"abstract":"With the development of science and technology and the development of human demand and investment demand, the scale of engineering construction is getting bigger and bigger. The ensuing problem is that the complexity and difficulty of the project has increased, and the quality requirements have also increased. Traditional management methods can no longer meet the needs of infrastructure management; with the rapid development of computer technology and information technology, it is inevitable to introduce both in project management. This paper focuses on the research of the project management information system based on the adaptive ant colony algorithm, combines the adaptive ant colony algorithm with the project management information system, optimizes the current project management information system, and then designs the system for verification. It is concluded from the experimental results that the algorithm proposed in this paper is effective.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"15 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81631576","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 : 2021-11-01DOI: 10.1109/ITME53901.2021.00096
Pei Zhao
In order to train engineering and application-oriented international students with international professional quality and high skill level and to equip such graduates to have the ability to obtain high-quality employment, this paper shows how Jinan Engineering Polytechnic forms a popularized education and training experience for international students with an individualized education and training program and running the project-based design through the whole practical teaching link by the analysis of information engineering students training problems. Practice has proved that innovation and optimization of education and training mode for highly skilled talents is the key measures to effectively improve the level of international talent training.
{"title":"Research on the Optimization of the Education and Training Model for International Students Majoring in Information Engineering in Higher Vocational Education","authors":"Pei Zhao","doi":"10.1109/ITME53901.2021.00096","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00096","url":null,"abstract":"In order to train engineering and application-oriented international students with international professional quality and high skill level and to equip such graduates to have the ability to obtain high-quality employment, this paper shows how Jinan Engineering Polytechnic forms a popularized education and training experience for international students with an individualized education and training program and running the project-based design through the whole practical teaching link by the analysis of information engineering students training problems. Practice has proved that innovation and optimization of education and training mode for highly skilled talents is the key measures to effectively improve the level of international talent training.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"29 1","pages":"450-454"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82029595","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 : 2021-11-01DOI: 10.1109/ITME53901.2021.00112
Li Zhao, Wenjing Qi, Yongchun Wu
The quality evaluation system is critical part in keeping the high quality and healthy development of graduate education. There still exists many vulnerabilities and shortcomings in current system, which often pose a strong influence on the efficiency of evaluation and the accuracy of evaluation results. To tackle this problem, we propose an index system for graduate education evaluation based on stakeholder theory, which expands the “three-elements” evaluation subjects that consists of government, society and university, to a “five-elements” evaluation subjects by adding mentor and student as subjects according to the stakeholder theoretical model; then an evaluation index system is constructed on the “five-elements” evaluation subjects. Our evaluation system makes up the vulnerabilities and deficiencies in the current evaluation index system, improves the scientificity and accuracy of evaluation in professional degree graduate education effectively.
{"title":"The Construction of the Index System for Quality Evaluation in Professional Graduate Education Based on Stakeholder Theory","authors":"Li Zhao, Wenjing Qi, Yongchun Wu","doi":"10.1109/ITME53901.2021.00112","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00112","url":null,"abstract":"The quality evaluation system is critical part in keeping the high quality and healthy development of graduate education. There still exists many vulnerabilities and shortcomings in current system, which often pose a strong influence on the efficiency of evaluation and the accuracy of evaluation results. To tackle this problem, we propose an index system for graduate education evaluation based on stakeholder theory, which expands the “three-elements” evaluation subjects that consists of government, society and university, to a “five-elements” evaluation subjects by adding mentor and student as subjects according to the stakeholder theoretical model; then an evaluation index system is constructed on the “five-elements” evaluation subjects. Our evaluation system makes up the vulnerabilities and deficiencies in the current evaluation index system, improves the scientificity and accuracy of evaluation in professional degree graduate education effectively.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"134 1","pages":"528-532"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77359722","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 : 2021-11-01DOI: 10.1109/ITME53901.2021.00108
Y. Qi, Fangkai Zhang
In recent years, China has been paying attention to the cultivation of international talents. This paper aims to cultivate international talents with international vision. Take the combination of information technology and international teaching as the path, formulate an international talent cultivating program in line with the needs of social development, and take the school of economics and economics of Shandong University of finance as the pilot object. The results show that the integration of international teaching and information technology has significantly improved the proportion of international courses and the scale of teachers.
{"title":"International teaching design and practice under the background of information technology -Taking the international course of Shandong University of Finance and economics as an example","authors":"Y. Qi, Fangkai Zhang","doi":"10.1109/ITME53901.2021.00108","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00108","url":null,"abstract":"In recent years, China has been paying attention to the cultivation of international talents. This paper aims to cultivate international talents with international vision. Take the combination of information technology and international teaching as the path, formulate an international talent cultivating program in line with the needs of social development, and take the school of economics and economics of Shandong University of finance as the pilot object. The results show that the integration of international teaching and information technology has significantly improved the proportion of international courses and the scale of teachers.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"137 1","pages":"509-513"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76743148","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 : 2021-11-01DOI: 10.1109/itme53901.2021.00008
{"title":"ITME 2021 Program Committee","authors":"","doi":"10.1109/itme53901.2021.00008","DOIUrl":"https://doi.org/10.1109/itme53901.2021.00008","url":null,"abstract":"","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"57 35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79827830","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 : 2021-11-01DOI: 10.1109/ITME53901.2021.00040
Liyuan Zhang, Yifei Huang, Weibin Chen, Wenzhong Guo, Genggeng Liu
Steiner minimal tree construction is a key step in the physical design of Very Large Scale Integration (VLSI). Further considering X-architecture with better wirelength optimization and allowing wires to pass through obstacles to a certain extent before signal distortion, a novel X-architecture Steiner Minimal Tree with Limited Routing Length inside Obstacle (XSMT-LRLO) problem is formed. Therefore, the XSMT-LRLO based on Discrete Particle Swarm Optimization algorithm (XSMT-LRLO-DPSO) is proposed. Firstly, in order to significantly reduce the times of evaluations, a preprocessing strategy based on a lookup table is proposed. Secondly, XSMT-LRLO-DPSO is effectively en-coded by adopting the edge-point pairs encoding method adapted to an evolutionary iterative process. Then, aiming at the XSMT-LRLO problem, which is a discrete problem, a discrete update strategy based on mutation operation and crossover operation is proposed. Finally, adjustment and refinement strategies are introduced to respectively improve the obstacles bypassing ability and wirelength optimization ability of the proposed algorithm. The experimental results show that the proposed algorithm makes full use of the routing resources within the obstacles, and effectively saves routing resources. Compared with similar algorithms, the proposed algorithm has the strongest wirelength optimization ability.
{"title":"X-architecture Steiner Tree Algorithm with Limited Routing Length inside Obstacle","authors":"Liyuan Zhang, Yifei Huang, Weibin Chen, Wenzhong Guo, Genggeng Liu","doi":"10.1109/ITME53901.2021.00040","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00040","url":null,"abstract":"Steiner minimal tree construction is a key step in the physical design of Very Large Scale Integration (VLSI). Further considering X-architecture with better wirelength optimization and allowing wires to pass through obstacles to a certain extent before signal distortion, a novel X-architecture Steiner Minimal Tree with Limited Routing Length inside Obstacle (XSMT-LRLO) problem is formed. Therefore, the XSMT-LRLO based on Discrete Particle Swarm Optimization algorithm (XSMT-LRLO-DPSO) is proposed. Firstly, in order to significantly reduce the times of evaluations, a preprocessing strategy based on a lookup table is proposed. Secondly, XSMT-LRLO-DPSO is effectively en-coded by adopting the edge-point pairs encoding method adapted to an evolutionary iterative process. Then, aiming at the XSMT-LRLO problem, which is a discrete problem, a discrete update strategy based on mutation operation and crossover operation is proposed. Finally, adjustment and refinement strategies are introduced to respectively improve the obstacles bypassing ability and wirelength optimization ability of the proposed algorithm. The experimental results show that the proposed algorithm makes full use of the routing resources within the obstacles, and effectively saves routing resources. Compared with similar algorithms, the proposed algorithm has the strongest wirelength optimization ability.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"161 1","pages":"152-156"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80141315","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 : 2021-11-01DOI: 10.1109/ITME53901.2021.00032
Yunfen Luo, Xingkai Li
Recent years have seen a lot of interest in link prediction. Essentially, it means designing a prediction algorithm that is capable of accurately describing a certain network mechanism in order to get more accurate predictions. In complex network research, it has important applications. The DeepWalk method randomly samples neighbor nodes, and it does not fully consider the node position itself, so insufficient information considered in node sequence sequence sampling When using DeepWalk for link prediction, the node's own influence characteristics are not considered. First of all,we change DeepWalk through biased random walk, learns the vector representation of nodes, and then fuses the influence between node pairs and the similarity between node pairs to raise the accuracy of link prediction. We have experimented the algorithm of this paper on real network data, and from the experimental results, we can see that the algorithm of this paper works better than other link prediction algorithms.
{"title":"A Link Prediction Algorithm Combining Node Influence and New Biased Random Walk","authors":"Yunfen Luo, Xingkai Li","doi":"10.1109/ITME53901.2021.00032","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00032","url":null,"abstract":"Recent years have seen a lot of interest in link prediction. Essentially, it means designing a prediction algorithm that is capable of accurately describing a certain network mechanism in order to get more accurate predictions. In complex network research, it has important applications. The DeepWalk method randomly samples neighbor nodes, and it does not fully consider the node position itself, so insufficient information considered in node sequence sequence sampling When using DeepWalk for link prediction, the node's own influence characteristics are not considered. First of all,we change DeepWalk through biased random walk, learns the vector representation of nodes, and then fuses the influence between node pairs and the similarity between node pairs to raise the accuracy of link prediction. We have experimented the algorithm of this paper on real network data, and from the experimental results, we can see that the algorithm of this paper works better than other link prediction algorithms.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"8 1","pages":"107-111"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86883488","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 : 2021-11-01DOI: 10.1109/ITME53901.2021.00111
Xingyu Tian, Shengnan Tang, Daoxun Xia
The in-depth understanding and application of teacher and student data by learning analytics technology provide a new development perspective for the education field, in which emotional data play a vital role in evaluating teaching quality and learning effects. Currently, sentiment analysis technology is developing rapidly, but its application in the educational field is lagging. Most of the research is based on sentiment analysis of published texts on social media or videos recorded by students, which may lead to problems such as incomplete feedback content and delayed feedback analysis. Based on the mini-Xception framework, this paper implements the real-time identification and analysis of student sentiment in classroom teaching. Through the feedback results, teachers can fully understand the degree of student engagement and provide reasonable suggestions for subsequent teaching progress. The experimental results show that this method has high recognition accuracy for the real-time detection of seven student sentiments, and the average accuracy is 76.71 %. Compared with after-class student feedback or real-time text sentiment analysis, it can better reflect the real time and high efficiency of information feedback. It provides a basis for teachers to control the teaching rhythm and evaluate the teaching effect and is an effective method for realizing personalized teaching.
{"title":"Application of Real-time Sentiment Analysis Based on Mini-Xception in Classroom Teaching","authors":"Xingyu Tian, Shengnan Tang, Daoxun Xia","doi":"10.1109/ITME53901.2021.00111","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00111","url":null,"abstract":"The in-depth understanding and application of teacher and student data by learning analytics technology provide a new development perspective for the education field, in which emotional data play a vital role in evaluating teaching quality and learning effects. Currently, sentiment analysis technology is developing rapidly, but its application in the educational field is lagging. Most of the research is based on sentiment analysis of published texts on social media or videos recorded by students, which may lead to problems such as incomplete feedback content and delayed feedback analysis. Based on the mini-Xception framework, this paper implements the real-time identification and analysis of student sentiment in classroom teaching. Through the feedback results, teachers can fully understand the degree of student engagement and provide reasonable suggestions for subsequent teaching progress. The experimental results show that this method has high recognition accuracy for the real-time detection of seven student sentiments, and the average accuracy is 76.71 %. Compared with after-class student feedback or real-time text sentiment analysis, it can better reflect the real time and high efficiency of information feedback. It provides a basis for teachers to control the teaching rhythm and evaluate the teaching effect and is an effective method for realizing personalized teaching.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"83 1","pages":"523-527"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82657566","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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