Pub Date : 2023-07-21DOI: 10.1080/26939169.2023.2240385
Allison Davidson
{"title":"A Review of the use of Investigative Projects in Statistics and Data Science Courses","authors":"Allison Davidson","doi":"10.1080/26939169.2023.2240385","DOIUrl":"https://doi.org/10.1080/26939169.2023.2240385","url":null,"abstract":"","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49243507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-20DOI: 10.1080/26939169.2023.2238018
Ciaran Evans, William Cipolli, Z. A. Draper, J. Binfet
Abstract Engaging and motivating students in undergraduate statistics courses can be enhanced by using topical peer-reviewed publications for analyses as part of course assignments. Given the popularity of on-campus therapy dog stress-reduction programs, this topic fosters buy-in from students whilst providing information regarding the importance of mental health and well-being as it impacts learning. This article describes how instructors can use a study on the benefits of human–dog interactions to teach students about study design, data collection and ethics, and hypothesis testing. The data and research questions are accessible to students without requiring detailed subject-area knowledge. Students can think carefully about how to collect and analyze data from a randomized controlled trial with two-sample hypothesis tests. Instructors can use these data for short in-class examples or longer assignments and assessments, and throughout this article, we suggest activities and discussion questions. Supplementary materials for this article are available online.
{"title":"Repurposing a peer-reviewed publication to engage students in statistics: An illustration of study design, data collection, and analysis","authors":"Ciaran Evans, William Cipolli, Z. A. Draper, J. Binfet","doi":"10.1080/26939169.2023.2238018","DOIUrl":"https://doi.org/10.1080/26939169.2023.2238018","url":null,"abstract":"Abstract Engaging and motivating students in undergraduate statistics courses can be enhanced by using topical peer-reviewed publications for analyses as part of course assignments. Given the popularity of on-campus therapy dog stress-reduction programs, this topic fosters buy-in from students whilst providing information regarding the importance of mental health and well-being as it impacts learning. This article describes how instructors can use a study on the benefits of human–dog interactions to teach students about study design, data collection and ethics, and hypothesis testing. The data and research questions are accessible to students without requiring detailed subject-area knowledge. Students can think carefully about how to collect and analyze data from a randomized controlled trial with two-sample hypothesis tests. Instructors can use these data for short in-class examples or longer assignments and assessments, and throughout this article, we suggest activities and discussion questions. Supplementary materials for this article are available online.","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42147291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-13DOI: 10.1080/26939169.2023.2234425
A. Underwood, Aidan Sichel, Emily C. Marshall
{"title":"Teaching Reproducible Methods in Economics at Liberal Arts Colleges: A Survey","authors":"A. Underwood, Aidan Sichel, Emily C. Marshall","doi":"10.1080/26939169.2023.2234425","DOIUrl":"https://doi.org/10.1080/26939169.2023.2234425","url":null,"abstract":"","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46456402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.1080/26939169.2023.2231065
Qing Wang, Xizhen Cai
{"title":"Active-Learning Class Activities and Shiny Applications for Teaching Support Vector Classifiers","authors":"Qing Wang, Xizhen Cai","doi":"10.1080/26939169.2023.2231065","DOIUrl":"https://doi.org/10.1080/26939169.2023.2231065","url":null,"abstract":"","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48216666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1080/26939169.2023.2224407
L. Kennedy‐Shaffer
{"title":"Teaching the Difficult Past of Statistics to Improve the Future","authors":"L. Kennedy‐Shaffer","doi":"10.1080/26939169.2023.2224407","DOIUrl":"https://doi.org/10.1080/26939169.2023.2224407","url":null,"abstract":"","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47403191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-04DOI: 10.1080/26939169.2023.2226026
N. Horton
The Journal of Statistics and Data Science Education (JSDSE) Jackie Dietz Best Paper Award was established in 2011 to honor Jackie’s contributions as the founding editor of the journal from 1993 to 2000. JSDSE (formerly the Journal of Statistics Education) was founded as an open-access journal with no author publication charges to help foster pedagogical discussions and to share best practices. More on Jackie’s many contributions to the journal and the profession can be found in Rossman and Dietz (2011) and Horton (2022). The Jackie Dietz award is presented annually to the best paper among all those appearing in JSDSE in the previous year. What makes a “best” paper? Table 1 displays the names, authors, and year of publication for the first 13 recipients. Looking back at the winners, it’s clear that the winning papers are asking important questions and exploring the big picture of data science and statistics education. The formal criteria for the award call for papers that:
统计与数据科学教育杂志(JSDSE)杰基·迪茨最佳论文奖于2011年设立，以表彰杰基在1993年至2000年期间作为该杂志的创始编辑所做的贡献。JSDSE(以前的Journal of Statistics Education)是一本开放获取的期刊，不收取作者出版费用，旨在促进教学讨论和分享最佳实践。更多关于Jackie对期刊和专业的贡献，可以在Rossman和Dietz(2011)和Horton(2022)中找到。Jackie Dietz奖每年颁发给上一年在JSDSE上发表的所有论文中的最佳论文。什么是“最好”的论文?表1显示了前13位收件人的姓名、作者和出版年份。回顾获奖者，很明显，获奖论文提出了重要的问题，并探索了数据科学和统计教育的大局。该奖项的正式标准要求论文:
{"title":"The Journal of Statistics and Data Science Education Jackie Dietz Best Paper Award","authors":"N. Horton","doi":"10.1080/26939169.2023.2226026","DOIUrl":"https://doi.org/10.1080/26939169.2023.2226026","url":null,"abstract":"The Journal of Statistics and Data Science Education (JSDSE) Jackie Dietz Best Paper Award was established in 2011 to honor Jackie’s contributions as the founding editor of the journal from 1993 to 2000. JSDSE (formerly the Journal of Statistics Education) was founded as an open-access journal with no author publication charges to help foster pedagogical discussions and to share best practices. More on Jackie’s many contributions to the journal and the profession can be found in Rossman and Dietz (2011) and Horton (2022). The Jackie Dietz award is presented annually to the best paper among all those appearing in JSDSE in the previous year. What makes a “best” paper? Table 1 displays the names, authors, and year of publication for the first 13 recipients. Looking back at the winners, it’s clear that the winning papers are asking important questions and exploring the big picture of data science and statistics education. The formal criteria for the award call for papers that:","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":"31 1","pages":"113 - 115"},"PeriodicalIF":1.7,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42328609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-04DOI: 10.1080/26939169.2023.2223609
Amanda R. Ellis, E. Slade
Abstract ChatGPT is one of many generative artificial intelligence (AI) tools that has emerged recently, creating controversy in the education community with concerns about its potential to be used for plagiarism and to undermine students’ ability to think independently. Recent publications have criticized the use of ChatGPT and other generative AI tools in the classroom, with little focus on the potential benefits. This article focuses on the potential of ChatGPT as an educational tool for statistics and data science. It encourages readers to consider the history of trepidation surrounding introducing new technology in the classroom, such as the calculator. We explore the possibility of leveraging ChatGPT’s capabilities in statistics and data science education, providing examples of how ChatGPT can aid in developing course materials and suggestions for how educators can prompt students to interact with ChatGPT responsibly. As educators, we can guide the use of generative AI tools in statistics and data science classrooms so that students and educators can leverage the benefits of this technology.
{"title":"A New Era of Learning: Considerations for ChatGPT as a Tool to Enhance Statistics and Data Science Education","authors":"Amanda R. Ellis, E. Slade","doi":"10.1080/26939169.2023.2223609","DOIUrl":"https://doi.org/10.1080/26939169.2023.2223609","url":null,"abstract":"Abstract ChatGPT is one of many generative artificial intelligence (AI) tools that has emerged recently, creating controversy in the education community with concerns about its potential to be used for plagiarism and to undermine students’ ability to think independently. Recent publications have criticized the use of ChatGPT and other generative AI tools in the classroom, with little focus on the potential benefits. This article focuses on the potential of ChatGPT as an educational tool for statistics and data science. It encourages readers to consider the history of trepidation surrounding introducing new technology in the classroom, such as the calculator. We explore the possibility of leveraging ChatGPT’s capabilities in statistics and data science education, providing examples of how ChatGPT can aid in developing course materials and suggestions for how educators can prompt students to interact with ChatGPT responsibly. As educators, we can guide the use of generative AI tools in statistics and data science classrooms so that students and educators can leverage the benefits of this technology.","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":"31 1","pages":"128 - 133"},"PeriodicalIF":1.7,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41848103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-02DOI: 10.1080/26939169.2023.2205907
Byran J. Smucker, Nathaniel T. Stevens, Jacqueline A. Asscher, P. Goos
Abstract The design and analysis of experiments (DOE) has historically been an important part of an education in statistics, and with the increasing complexity of modern production processes and the advent of large-scale online experiments, it continues to be highly relevant. In this article, we provide an extensive review of the literature on DOE pedagogy, and provide five perspectives on the subject: one from each of the authors as well as a composite profile derived from a survey of DOE instructors. Our work provides a snapshot of current DOE pedagogy that showcases both the similarities and variety in how the subject is taught, as well as a look ahead at how its instruction may evolve. Supplementary materials for this article are available online.
{"title":"Profiles in the Teaching of Experimental Design and Analysis","authors":"Byran J. Smucker, Nathaniel T. Stevens, Jacqueline A. Asscher, P. Goos","doi":"10.1080/26939169.2023.2205907","DOIUrl":"https://doi.org/10.1080/26939169.2023.2205907","url":null,"abstract":"Abstract The design and analysis of experiments (DOE) has historically been an important part of an education in statistics, and with the increasing complexity of modern production processes and the advent of large-scale online experiments, it continues to be highly relevant. In this article, we provide an extensive review of the literature on DOE pedagogy, and provide five perspectives on the subject: one from each of the authors as well as a composite profile derived from a survey of DOE instructors. Our work provides a snapshot of current DOE pedagogy that showcases both the similarities and variety in how the subject is taught, as well as a look ahead at how its instruction may evolve. Supplementary materials for this article are available online.","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45515451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-27DOI: 10.1080/26939169.2023.2208185
Margo Glantz, Jennifer Johnson, Marilyn Macy, Juan Nunez, Rachel Saidi, Camilo Velez Ramirez
Abstract Two-year colleges provide the opportunity for students of all ages to try new subjects, change careers, upskill, or begin exploring higher education, at affordable rates. Many might begin their exploration by taking a course at a local two-year college. Currently, not many of these institutions in the U.S. offer data science courses. This article introduces the perspective lens of students who have gone through the Montgomery College Data Science Certificate Program. We found that, contrary to many other educational fields at the College, data science students tend to come from diverse backgrounds and career paths. A common theme emerged that all students learned valuable skills and applications such as coding in various programming languages and approaches to machine learning. Other meaningful themes included an appreciation of course accessibility, especially catered toward busy professionals who might only be able to take evening courses. Students appreciated learning that data science and ethics are intertwined. Finally, it was evident that going through the data science program positively impacted the lives and careers of these students. The implications of the themes of these student experiences are discussed as they relate to data science education. Supplementary materials for this article are available online.
{"title":"Students' Experience and Perspective of a Data Science Program in a Two-Year College","authors":"Margo Glantz, Jennifer Johnson, Marilyn Macy, Juan Nunez, Rachel Saidi, Camilo Velez Ramirez","doi":"10.1080/26939169.2023.2208185","DOIUrl":"https://doi.org/10.1080/26939169.2023.2208185","url":null,"abstract":"Abstract Two-year colleges provide the opportunity for students of all ages to try new subjects, change careers, upskill, or begin exploring higher education, at affordable rates. Many might begin their exploration by taking a course at a local two-year college. Currently, not many of these institutions in the U.S. offer data science courses. This article introduces the perspective lens of students who have gone through the Montgomery College Data Science Certificate Program. We found that, contrary to many other educational fields at the College, data science students tend to come from diverse backgrounds and career paths. A common theme emerged that all students learned valuable skills and applications such as coding in various programming languages and approaches to machine learning. Other meaningful themes included an appreciation of course accessibility, especially catered toward busy professionals who might only be able to take evening courses. Students appreciated learning that data science and ethics are intertwined. Finally, it was evident that going through the data science program positively impacted the lives and careers of these students. The implications of the themes of these student experiences are discussed as they relate to data science education. Supplementary materials for this article are available online.","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48860161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1080/26939169.2023.2205905
J. Witmer
{"title":"What Should We Do Differently in STAT 101?","authors":"J. Witmer","doi":"10.1080/26939169.2023.2205905","DOIUrl":"https://doi.org/10.1080/26939169.2023.2205905","url":null,"abstract":"","PeriodicalId":34851,"journal":{"name":"Journal of Statistics and Data Science Education","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45186102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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