{"title":"使用可复制的数据科学工具创建一个积极的学习环境","authors":"R. Burns","doi":"10.1145/3409311.3403400","DOIUrl":null,"url":null,"abstract":"After a decade of struggle to help students install and launch machine virtual machines in the cloud, the author migrated his computer science course to the Gigantum data science platform, which automates the delivery of complex software configurations. The goal was to make it easier for students to complete projects so that they could focus on programming rather than system administration. In the process, lectures were redesigned into an active learning experience in Jupyter notebooks in which students run and modify examples as they are presented and can reproduce exactly all work that they have done or has been demonstrated.","PeriodicalId":72732,"journal":{"name":"Current issues in emerging elearning","volume":"48 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Creating an Active Learning Environment using Reproducible Data Science Tools\",\"authors\":\"R. Burns\",\"doi\":\"10.1145/3409311.3403400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"After a decade of struggle to help students install and launch machine virtual machines in the cloud, the author migrated his computer science course to the Gigantum data science platform, which automates the delivery of complex software configurations. The goal was to make it easier for students to complete projects so that they could focus on programming rather than system administration. In the process, lectures were redesigned into an active learning experience in Jupyter notebooks in which students run and modify examples as they are presented and can reproduce exactly all work that they have done or has been demonstrated.\",\"PeriodicalId\":72732,\"journal\":{\"name\":\"Current issues in emerging elearning\",\"volume\":\"48 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current issues in emerging elearning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3409311.3403400\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current issues in emerging elearning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3409311.3403400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Creating an Active Learning Environment using Reproducible Data Science Tools
After a decade of struggle to help students install and launch machine virtual machines in the cloud, the author migrated his computer science course to the Gigantum data science platform, which automates the delivery of complex software configurations. The goal was to make it easier for students to complete projects so that they could focus on programming rather than system administration. In the process, lectures were redesigned into an active learning experience in Jupyter notebooks in which students run and modify examples as they are presented and can reproduce exactly all work that they have done or has been demonstrated.