{"title":"对话属性告知参与课程讨论论坛的深度和质量","authors":"Elaine Farrow, Johanna D. Moore, D. Gašević","doi":"10.1145/3375462.3375481","DOIUrl":null,"url":null,"abstract":"This paper describes work in progress to answer the question of how we can identify and model the depth and quality of student participation in class discussion forums using the content of the discussion forum messages. We look at two widely-studied frameworks for assessing critical discourse and cognitive engagement: the ICAP and Community of Inquiry (CoI) frameworks. Our goal is to discover where they agree and where they offer complementary perspectives on learning. In this study, we train predictive classifiers for both frameworks on the same data set in order to discover which attributes are most predictive and how those correlate with the framework labels. We find that greater depth and quality of participation is associated with longer and more complex messages in both frameworks, and that the threaded reply structure matters more than temporal order. We find some important differences as well, particularly in the treatment of messages of affirmation.","PeriodicalId":355800,"journal":{"name":"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Dialogue attributes that inform depth and quality of participation in course discussion forums\",\"authors\":\"Elaine Farrow, Johanna D. Moore, D. Gašević\",\"doi\":\"10.1145/3375462.3375481\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes work in progress to answer the question of how we can identify and model the depth and quality of student participation in class discussion forums using the content of the discussion forum messages. We look at two widely-studied frameworks for assessing critical discourse and cognitive engagement: the ICAP and Community of Inquiry (CoI) frameworks. Our goal is to discover where they agree and where they offer complementary perspectives on learning. In this study, we train predictive classifiers for both frameworks on the same data set in order to discover which attributes are most predictive and how those correlate with the framework labels. We find that greater depth and quality of participation is associated with longer and more complex messages in both frameworks, and that the threaded reply structure matters more than temporal order. We find some important differences as well, particularly in the treatment of messages of affirmation.\",\"PeriodicalId\":355800,\"journal\":{\"name\":\"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3375462.3375481\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3375462.3375481","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dialogue attributes that inform depth and quality of participation in course discussion forums
This paper describes work in progress to answer the question of how we can identify and model the depth and quality of student participation in class discussion forums using the content of the discussion forum messages. We look at two widely-studied frameworks for assessing critical discourse and cognitive engagement: the ICAP and Community of Inquiry (CoI) frameworks. Our goal is to discover where they agree and where they offer complementary perspectives on learning. In this study, we train predictive classifiers for both frameworks on the same data set in order to discover which attributes are most predictive and how those correlate with the framework labels. We find that greater depth and quality of participation is associated with longer and more complex messages in both frameworks, and that the threaded reply structure matters more than temporal order. We find some important differences as well, particularly in the treatment of messages of affirmation.