Pub Date : 2020-09-01DOI: 10.1080/10691898.2020.1845499
Alicia A. Johnson, Colin W. Rundel, Jingchen Hu, Kevin Ross, Allan Rossman
{"title":"Teaching an Undergraduate Course in Bayesian Statistics: A Panel Discussion","authors":"Alicia A. Johnson, Colin W. Rundel, Jingchen Hu, Kevin Ross, Allan Rossman","doi":"10.1080/10691898.2020.1845499","DOIUrl":"https://doi.org/10.1080/10691898.2020.1845499","url":null,"abstract":"","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1845499","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49166663","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 : 2020-09-01DOI: 10.1080/10691898.2020.1834475
Linda Farmus, R. Cribbie, M. Rotondi
Abstract The flipped classroom (FC) inverts the traditional classroom by having students participate in passive aspects of learning at home and active aspects of learning in class with the guide of an instructor. The introductory statistics course for nonmath majors may be especially suited to the FC model given its unique challenges as a required course for students with varying mathematical skills and background. For example, these students often have low interest and high statistics-related anxiety. Recent studies suggest the FC for introductory statistics courses leads to increased performance relative to a traditional lecture-based classroom (LC). This meta-analysis compared the academic performance of students in introductory statistics courses for nonmath majors who were taught in a FC versus those taught in a LC. Results indicate that students in the FC had statistically discernibly higher final performance outcomes compared to the LC delivery with an average difference of 6.9% in performance (Hedge’s g = 0.43), though there was evidence of moderation by the presence of weekly in-class quizzes. These findings suggest that implementing the FC within the introductory statistics classroom at the undergraduate level may improve learning achievement, but more research is needed to explore the role of regular class quizzes. Supplementary materials for this article are available online.
摘要翻转课堂(FC)是一种颠覆传统课堂的教学模式，学生在教师的指导下，在家中被动学习，在课堂上主动学习。非数学专业的统计学入门课程可能特别适合FC模型，因为它作为具有不同数学技能和背景的学生的必修课具有独特的挑战。例如，这些学生通常对统计数据兴趣不高，并且有高度的统计相关焦虑。最近的研究表明，相对于传统的基于讲座的课堂(LC)，入门统计学课程的FC可以提高学生的表现。本荟萃分析比较了在FC和LC授课的非数学专业学生在统计学入门课程上的学习成绩。结果表明，与LC交付的学生相比，FC的学生在统计上有明显更高的最终表现结果，平均表现差异为6.9% (Hedge 's g = 0.43)，尽管有证据表明每周课堂测验的存在是适度的。这些发现表明，在本科阶段的统计学入门课堂中实施FC可能会提高学习成绩，但需要更多的研究来探索常规课堂测验的作用。本文的补充材料可在网上获得。
{"title":"The Flipped Classroom in Introductory Statistics: Early Evidence From a Systematic Review and Meta-Analysis","authors":"Linda Farmus, R. Cribbie, M. Rotondi","doi":"10.1080/10691898.2020.1834475","DOIUrl":"https://doi.org/10.1080/10691898.2020.1834475","url":null,"abstract":"Abstract The flipped classroom (FC) inverts the traditional classroom by having students participate in passive aspects of learning at home and active aspects of learning in class with the guide of an instructor. The introductory statistics course for nonmath majors may be especially suited to the FC model given its unique challenges as a required course for students with varying mathematical skills and background. For example, these students often have low interest and high statistics-related anxiety. Recent studies suggest the FC for introductory statistics courses leads to increased performance relative to a traditional lecture-based classroom (LC). This meta-analysis compared the academic performance of students in introductory statistics courses for nonmath majors who were taught in a FC versus those taught in a LC. Results indicate that students in the FC had statistically discernibly higher final performance outcomes compared to the LC delivery with an average difference of 6.9% in performance (Hedge’s g = 0.43), though there was evidence of moderation by the presence of weekly in-class quizzes. These findings suggest that implementing the FC within the introductory statistics classroom at the undergraduate level may improve learning achievement, but more research is needed to explore the role of regular class quizzes. Supplementary materials for this article are available online.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1834475","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41584593","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 : 2020-09-01DOI: 10.1080/10691898.2020.1832006
M. Caballer-Tarazona, V. Coll-Serrano
Abstract In the first years of their economics degree programs, students will face many problems successfully dealing with a range of subjects with quantitative content. Specifically, in the field of statistics, difficulties to reach some basic academic achievements have been observed. Hence, a continuing challenge for statistics teachers is how to make this subject more appealing for students through the design and implementation of new teaching methodologies. The latter tend to follow two main approaches. On the one hand, it is useful for the learning process to propose practical activities that can connect theoretical concepts with real applications in the economic context. On the other hand, we should design multidisciplinary activities that link concepts from different subjects. With this goal in mind, in this article we propose a complete activity for first year students in business administration and economics degree programs, aimed to reinforce some basic statistical and economic concepts, while other basic transversal skills are also practiced, all within the subject of statistics.
{"title":"The Raising Factor, That Great Unknown. A Guided Activity for Undergraduate Students","authors":"M. Caballer-Tarazona, V. Coll-Serrano","doi":"10.1080/10691898.2020.1832006","DOIUrl":"https://doi.org/10.1080/10691898.2020.1832006","url":null,"abstract":"Abstract In the first years of their economics degree programs, students will face many problems successfully dealing with a range of subjects with quantitative content. Specifically, in the field of statistics, difficulties to reach some basic academic achievements have been observed. Hence, a continuing challenge for statistics teachers is how to make this subject more appealing for students through the design and implementation of new teaching methodologies. The latter tend to follow two main approaches. On the one hand, it is useful for the learning process to propose practical activities that can connect theoretical concepts with real applications in the economic context. On the other hand, we should design multidisciplinary activities that link concepts from different subjects. With this goal in mind, in this article we propose a complete activity for first year students in business administration and economics degree programs, aimed to reinforce some basic statistical and economic concepts, while other basic transversal skills are also practiced, all within the subject of statistics.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1832006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43773545","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 : 2020-09-01DOI: 10.1080/10691898.2020.1841590
Nicola Justice
Abstract Many statistics departments in institutions throughout the world hire graduate students to teach and assist with the teaching of undergraduate and graduate-level statistics courses. As many of these graduate student instructors and graduate teaching assistants (GTAs) have little or no previous experience teaching statistics, statistics departments are faced with the challenge of preparing their graduate students for teaching roles. Articles have been written sharing various departments’ strategies for GTA training and development programs, however, articles are often not supported by empirical research. This article provides a review of empirical research regarding graduate students’ preparation for teaching—first focusing on graduate students in statistics, specifically, and second offering what can be learned from studies of graduate students in other disciplines. We conclude with ten research-based recommendations for preparing graduate students to teach statistics, along with practical ideas for how to implement them.
{"title":"Preparing Graduate Students to Teach Statistics: A Review of Research and Ten Practical Recommendations","authors":"Nicola Justice","doi":"10.1080/10691898.2020.1841590","DOIUrl":"https://doi.org/10.1080/10691898.2020.1841590","url":null,"abstract":"Abstract Many statistics departments in institutions throughout the world hire graduate students to teach and assist with the teaching of undergraduate and graduate-level statistics courses. As many of these graduate student instructors and graduate teaching assistants (GTAs) have little or no previous experience teaching statistics, statistics departments are faced with the challenge of preparing their graduate students for teaching roles. Articles have been written sharing various departments’ strategies for GTA training and development programs, however, articles are often not supported by empirical research. This article provides a review of empirical research regarding graduate students’ preparation for teaching—first focusing on graduate students in statistics, specifically, and second offering what can be learned from studies of graduate students in other disciplines. We conclude with ten research-based recommendations for preparing graduate students to teach statistics, along with practical ideas for how to implement them.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1841590","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44840746","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 : 2020-08-19DOI: 10.1080/10691898.2020.1796399
Lynette Hudiburgh, D. Garbinsky
Abstract Although the use of tables, graphs, and figures to summarize information has long existed, the advent of the big data era and improved computing power has brought renewed attention to the field of data visualization. As such, it is crucial that introductory statistics courses train students to become critical authors and consumers of data visualizations. To that end, we have developed a semester-long, instructor-supported, group project that exposes students to this growing field. We have found this project to be an exciting and effective way to teach students the power of statistics and, more importantly, the critical role context plays when interpreting statistics. Among the many benefits of this project are hands-on learning, improved mathematical reasoning, and better collaboration and communication skills. In this article, we describe the project structure, project assessment, and techniques for facilitating effective group work.
{"title":"Data Visualization: Bringing Data to Life in an Introductory Statistics Course","authors":"Lynette Hudiburgh, D. Garbinsky","doi":"10.1080/10691898.2020.1796399","DOIUrl":"https://doi.org/10.1080/10691898.2020.1796399","url":null,"abstract":"Abstract Although the use of tables, graphs, and figures to summarize information has long existed, the advent of the big data era and improved computing power has brought renewed attention to the field of data visualization. As such, it is crucial that introductory statistics courses train students to become critical authors and consumers of data visualizations. To that end, we have developed a semester-long, instructor-supported, group project that exposes students to this growing field. We have found this project to be an exciting and effective way to teach students the power of statistics and, more importantly, the critical role context plays when interpreting statistics. Among the many benefits of this project are hands-on learning, improved mathematical reasoning, and better collaboration and communication skills. In this article, we describe the project structure, project assessment, and techniques for facilitating effective group work.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1796399","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44933459","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 : 2020-08-11DOI: 10.1080/10691898.2020.1806761
J. Albert
This article reviews the second edition of the Bayesian text “Rethinking Statistics” by Richard McElreath.
本文回顾了Richard McElreath的贝叶斯文本“重新思考统计学”的第二版。
{"title":"Review of Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Second Edition, by Richard McElreath, Chapman and Hall, 2020","authors":"J. Albert","doi":"10.1080/10691898.2020.1806761","DOIUrl":"https://doi.org/10.1080/10691898.2020.1806761","url":null,"abstract":"This article reviews the second edition of the Bayesian text “Rethinking Statistics” by Richard McElreath.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1806761","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44658368","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 : 2020-07-23DOI: 10.1080/10691898.2020.1799727
Xizhen Cai, Qing Wang
ABSTRACT To incorporate active learning and cooperative teamwork in statistics classroom, this article introduces a creative three-dimensional educational tool and an in-class activity designed for introducing the topic of agglomerative hierarchical clustering. The educational tool consists of a simple bulletin board and color pushpins (it can also be realized with a less expensive alternative) based on which students work collaboratively in small groups of 3–5 to complete the task of agglomerative hierarchical clustering: they start with n singleton clusters, each corresponding to a pushpin of a unique color on the board, and work step by step to merge all pushpins into one single cluster using the single linkage, complete linkage, or group average linkage criteria. We present a detailed lesson plan that accompanies the designed activity and also provide a real data example in the supplementary materials. Supplementary materials for this article are available online.
{"title":"Educational Tool and Active-Learning Class Activity for Teaching Agglomerative Hierarchical Clustering","authors":"Xizhen Cai, Qing Wang","doi":"10.1080/10691898.2020.1799727","DOIUrl":"https://doi.org/10.1080/10691898.2020.1799727","url":null,"abstract":"ABSTRACT To incorporate active learning and cooperative teamwork in statistics classroom, this article introduces a creative three-dimensional educational tool and an in-class activity designed for introducing the topic of agglomerative hierarchical clustering. The educational tool consists of a simple bulletin board and color pushpins (it can also be realized with a less expensive alternative) based on which students work collaboratively in small groups of 3–5 to complete the task of agglomerative hierarchical clustering: they start with n singleton clusters, each corresponding to a pushpin of a unique color on the board, and work step by step to merge all pushpins into one single cluster using the single linkage, complete linkage, or group average linkage criteria. We present a detailed lesson plan that accompanies the designed activity and also provide a real data example in the supplementary materials. Supplementary materials for this article are available online.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1799727","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49323448","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 : 2020-05-03DOI: 10.1080/10691898.2020.1795468
Allan Rossman, Prince Afriyie
{"title":"Interview With Prince Afriyie: From Ghana to America","authors":"Allan Rossman, Prince Afriyie","doi":"10.1080/10691898.2020.1795468","DOIUrl":"https://doi.org/10.1080/10691898.2020.1795468","url":null,"abstract":"","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1795468","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49231709","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 : 2020-05-03DOI: 10.1080/10691898.2020.1796069
J. Witmer
{"title":"Note From the Editor","authors":"J. Witmer","doi":"10.1080/10691898.2020.1796069","DOIUrl":"https://doi.org/10.1080/10691898.2020.1796069","url":null,"abstract":"","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1796069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47810637","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 : 2020-05-03DOI: 10.1080/10691898.2020.1773354
Henrique Alvarenga da Silva, A. Moura
Abstract Biostatistics is a critical skill to physicians in an evidence-based medicine era, but teaching basic statistical concepts is challenging. Students often experience anxiety caused by the complexity of statistics and might express negative attitudes toward the subject. We aimed to analyze the effect of an introductory biostatistics course using RStudio on attitude toward statistics and assess its acceptance among medical students. Forty-three 1st-year medical students were included. Pre- and post-course attitudes toward statistics were assessed using the Survey of Attitudes Toward Statistics (SATS-28) scale and technology acceptance was assessed by a Technology Acceptance Model scale at the end of the course. There was a statistically discernible (significant) gain in the scores of three of the four SATS dimensions: affection (p = 0.006, Cohen’s d = 0.442), cognitive competence (p < 0.001, Cohen’s d = 0.605), and difficulty (p = 0.008, Cohen’s d = 0.421). Acceptance of RStudio was moderate to high in 93% of the participants, without statistical differences between genders. RStudio can be useful in the teaching of statistics to medical students, being well accepted and positively associated with students’ attitude toward statistics. Supplementary files for this article are available online.
{"title":"Teaching Introductory Statistical Classes in Medical Schools Using RStudio and R Statistical Language: Evaluating Technology Acceptance and Change in Attitude Toward Statistics","authors":"Henrique Alvarenga da Silva, A. Moura","doi":"10.1080/10691898.2020.1773354","DOIUrl":"https://doi.org/10.1080/10691898.2020.1773354","url":null,"abstract":"Abstract Biostatistics is a critical skill to physicians in an evidence-based medicine era, but teaching basic statistical concepts is challenging. Students often experience anxiety caused by the complexity of statistics and might express negative attitudes toward the subject. We aimed to analyze the effect of an introductory biostatistics course using RStudio on attitude toward statistics and assess its acceptance among medical students. Forty-three 1st-year medical students were included. Pre- and post-course attitudes toward statistics were assessed using the Survey of Attitudes Toward Statistics (SATS-28) scale and technology acceptance was assessed by a Technology Acceptance Model scale at the end of the course. There was a statistically discernible (significant) gain in the scores of three of the four SATS dimensions: affection (p = 0.006, Cohen’s d = 0.442), cognitive competence (p < 0.001, Cohen’s d = 0.605), and difficulty (p = 0.008, Cohen’s d = 0.421). Acceptance of RStudio was moderate to high in 93% of the participants, without statistical differences between genders. RStudio can be useful in the teaching of statistics to medical students, being well accepted and positively associated with students’ attitude toward statistics. Supplementary files for this article are available online.","PeriodicalId":45775,"journal":{"name":"Journal of Statistics Education","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2020-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10691898.2020.1773354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49587472","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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