{"title":"神经网络与规则的比较评价方法","authors":"Punyapat Chanpet, K. Chomsuwan","doi":"10.1109/TALE.2016.7851833","DOIUrl":null,"url":null,"abstract":"This study aimed to design and develop to an E-portfolio assessment system on Project-based learning approach to teaching and learning oriented assessment. The researcher considered 60 pre-service senior teachers from two classes in university particularly on instruction media courses. The control group comprised 30 pre-service teachers who used E-portfolio system and analytic rubric assessment that was a coherent set of criteria for students' work. It included descriptions of levels of performance quality on the criteria. The experimental group comprised 30 pre-service teachers that served as who used E-portfolio system and neural network assessment. Neural Networks was a model of the work of human brain by using computer. It made computer as clever as the human learning, and trained to classify the data mining in E-portfolio. Experimental results indicate that the E-portfolio assessment system has no significant effect on pre-service teacher achievement, positive effect on self-learning. In addition, rubric assessment and neural network assessment of project-based learning achievements produced different results.","PeriodicalId":117659,"journal":{"name":"2016 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE)","volume":"59 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative assessment method between neural network & rubric\",\"authors\":\"Punyapat Chanpet, K. Chomsuwan\",\"doi\":\"10.1109/TALE.2016.7851833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aimed to design and develop to an E-portfolio assessment system on Project-based learning approach to teaching and learning oriented assessment. The researcher considered 60 pre-service senior teachers from two classes in university particularly on instruction media courses. The control group comprised 30 pre-service teachers who used E-portfolio system and analytic rubric assessment that was a coherent set of criteria for students' work. It included descriptions of levels of performance quality on the criteria. The experimental group comprised 30 pre-service teachers that served as who used E-portfolio system and neural network assessment. Neural Networks was a model of the work of human brain by using computer. It made computer as clever as the human learning, and trained to classify the data mining in E-portfolio. Experimental results indicate that the E-portfolio assessment system has no significant effect on pre-service teacher achievement, positive effect on self-learning. In addition, rubric assessment and neural network assessment of project-based learning achievements produced different results.\",\"PeriodicalId\":117659,\"journal\":{\"name\":\"2016 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE)\",\"volume\":\"59 5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TALE.2016.7851833\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TALE.2016.7851833","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative assessment method between neural network & rubric
This study aimed to design and develop to an E-portfolio assessment system on Project-based learning approach to teaching and learning oriented assessment. The researcher considered 60 pre-service senior teachers from two classes in university particularly on instruction media courses. The control group comprised 30 pre-service teachers who used E-portfolio system and analytic rubric assessment that was a coherent set of criteria for students' work. It included descriptions of levels of performance quality on the criteria. The experimental group comprised 30 pre-service teachers that served as who used E-portfolio system and neural network assessment. Neural Networks was a model of the work of human brain by using computer. It made computer as clever as the human learning, and trained to classify the data mining in E-portfolio. Experimental results indicate that the E-portfolio assessment system has no significant effect on pre-service teacher achievement, positive effect on self-learning. In addition, rubric assessment and neural network assessment of project-based learning achievements produced different results.