{"title":"统计学入门课程中的双模式交付:设计与评估","authors":"Tommy Soesmanto, S. Bonner","doi":"10.1080/10691898.2019.1608874","DOIUrl":null,"url":null,"abstract":"Abstract In recent years, the Australian tertiary education sector embraced the gradual adaption of the dual mode system in course delivery in universities and higher degree education providers. In such systems, students have the option, as well as the flexibility, to undertake the same course in a face-to-face (F2F) environment and/or an online environment. This article presents an evaluation of the dual mode design of a first-year business statistics course delivered at the Griffith University. In this article, we discuss the various aspects of the dual mode design in the course, emphasizing the use of consistent teaching strategies for the F2F and online student cohorts. Moreover, we present a comparative analysis of learning satisfaction and academic performance of the two cohorts within the dual mode system. Using t-tests, nonparametric tests, and propensity score matching estimators we provide new insights into dual mode course design. Our results suggest no significant difference in student experiences and outcomes. Discussion and analysis presented in this article is useful as feedback for further improvement in teaching strategies in the delivery of dual mode courses.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":"27 1","pages":"90 - 98"},"PeriodicalIF":2.2000,"publicationDate":"2019-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2019.1608874","citationCount":"12","resultStr":"{\"title\":\"Dual Mode Delivery in an Introductory Statistics Course: Design and Evaluation\",\"authors\":\"Tommy Soesmanto, S. Bonner\",\"doi\":\"10.1080/10691898.2019.1608874\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract In recent years, the Australian tertiary education sector embraced the gradual adaption of the dual mode system in course delivery in universities and higher degree education providers. In such systems, students have the option, as well as the flexibility, to undertake the same course in a face-to-face (F2F) environment and/or an online environment. This article presents an evaluation of the dual mode design of a first-year business statistics course delivered at the Griffith University. In this article, we discuss the various aspects of the dual mode design in the course, emphasizing the use of consistent teaching strategies for the F2F and online student cohorts. Moreover, we present a comparative analysis of learning satisfaction and academic performance of the two cohorts within the dual mode system. Using t-tests, nonparametric tests, and propensity score matching estimators we provide new insights into dual mode course design. Our results suggest no significant difference in student experiences and outcomes. Discussion and analysis presented in this article is useful as feedback for further improvement in teaching strategies in the delivery of dual mode courses.\",\"PeriodicalId\":45775,\"journal\":{\"name\":\"Journal of Statistics Education\",\"volume\":\"27 1\",\"pages\":\"90 - 98\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2019-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/10691898.2019.1608874\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistics Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/10691898.2019.1608874\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistics Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10691898.2019.1608874","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
Dual Mode Delivery in an Introductory Statistics Course: Design and Evaluation
Abstract In recent years, the Australian tertiary education sector embraced the gradual adaption of the dual mode system in course delivery in universities and higher degree education providers. In such systems, students have the option, as well as the flexibility, to undertake the same course in a face-to-face (F2F) environment and/or an online environment. This article presents an evaluation of the dual mode design of a first-year business statistics course delivered at the Griffith University. In this article, we discuss the various aspects of the dual mode design in the course, emphasizing the use of consistent teaching strategies for the F2F and online student cohorts. Moreover, we present a comparative analysis of learning satisfaction and academic performance of the two cohorts within the dual mode system. Using t-tests, nonparametric tests, and propensity score matching estimators we provide new insights into dual mode course design. Our results suggest no significant difference in student experiences and outcomes. Discussion and analysis presented in this article is useful as feedback for further improvement in teaching strategies in the delivery of dual mode courses.
期刊介绍:
The "Datasets and Stories" department of the Journal of Statistics Education provides a forum for exchanging interesting datasets and discussing ways they can be used effectively in teaching statistics. This section of JSE is described fully in the article "Datasets and Stories: Introduction and Guidelines" by Robin H. Lock and Tim Arnold (1993). The Journal of Statistics Education maintains a Data Archive that contains the datasets described in "Datasets and Stories" articles, as well as additional datasets useful to statistics teachers. Lock and Arnold (1993) describe several criteria that will be considered before datasets are placed in the JSE Data Archive.