{"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}
引用次数: 0
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.