{"title":"在大型工程课程中使用笔式计算的代表性素养和参与性学习","authors":"A. Johri, V. Lohani","doi":"10.1109/FIE.2008.4720401","DOIUrl":null,"url":null,"abstract":"Representations are central to engineering practice. In this paper we present a theoretical model of how technology enables learning through participation by facilitating creation, sharing, recording, and reflection of representations. Our study is focused on large lecture classes (150-300 students) of a freshman year engineering course Engineering Exploration. Large classes provide unique challenges to the use of representations as the use of gestures and facial expressions in communication is hindered due to the size of classes. We found that when used concurrently Tablets and DyKnow supported representational practice facilitating student expression and increasing engagement in lectures. The technology further supported awareness and feedback within lectures and allowed co-construction of shared representations among faculty and students leading to a feedback based learning environment. We argue that there is some evidence that pen-based computing can transform large lecture classes to make them more inclusive and participatory. This technology driven innovation can help us in developing effective formative assessment strategies to redesign learning environment, particularly in large classrooms, to support the conceptual understanding of students. We analyzed and present both qualitative and quantitative assessment data collected from freshman engineering students through in-class and end of semester course exit survey (N~500).","PeriodicalId":342595,"journal":{"name":"2008 38th Annual Frontiers in Education Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Representational literacy and participatory learning in large engineering classes using pen-based computing\",\"authors\":\"A. Johri, V. Lohani\",\"doi\":\"10.1109/FIE.2008.4720401\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Representations are central to engineering practice. In this paper we present a theoretical model of how technology enables learning through participation by facilitating creation, sharing, recording, and reflection of representations. Our study is focused on large lecture classes (150-300 students) of a freshman year engineering course Engineering Exploration. Large classes provide unique challenges to the use of representations as the use of gestures and facial expressions in communication is hindered due to the size of classes. We found that when used concurrently Tablets and DyKnow supported representational practice facilitating student expression and increasing engagement in lectures. The technology further supported awareness and feedback within lectures and allowed co-construction of shared representations among faculty and students leading to a feedback based learning environment. We argue that there is some evidence that pen-based computing can transform large lecture classes to make them more inclusive and participatory. This technology driven innovation can help us in developing effective formative assessment strategies to redesign learning environment, particularly in large classrooms, to support the conceptual understanding of students. We analyzed and present both qualitative and quantitative assessment data collected from freshman engineering students through in-class and end of semester course exit survey (N~500).\",\"PeriodicalId\":342595,\"journal\":{\"name\":\"2008 38th Annual Frontiers in Education Conference\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 38th Annual Frontiers in Education Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FIE.2008.4720401\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 38th Annual Frontiers in Education Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FIE.2008.4720401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Representational literacy and participatory learning in large engineering classes using pen-based computing
Representations are central to engineering practice. In this paper we present a theoretical model of how technology enables learning through participation by facilitating creation, sharing, recording, and reflection of representations. Our study is focused on large lecture classes (150-300 students) of a freshman year engineering course Engineering Exploration. Large classes provide unique challenges to the use of representations as the use of gestures and facial expressions in communication is hindered due to the size of classes. We found that when used concurrently Tablets and DyKnow supported representational practice facilitating student expression and increasing engagement in lectures. The technology further supported awareness and feedback within lectures and allowed co-construction of shared representations among faculty and students leading to a feedback based learning environment. We argue that there is some evidence that pen-based computing can transform large lecture classes to make them more inclusive and participatory. This technology driven innovation can help us in developing effective formative assessment strategies to redesign learning environment, particularly in large classrooms, to support the conceptual understanding of students. We analyzed and present both qualitative and quantitative assessment data collected from freshman engineering students through in-class and end of semester course exit survey (N~500).