{"title":"C Oswald George prize announcement 2021","authors":"H. MacGillivray","doi":"10.1111/test.12295","DOIUrl":"https://doi.org/10.1111/test.12295","url":null,"abstract":"The article entitled “Interrogating a measurement conjecture to introduce the concept of statistical association in upper elementary education” by Mairéad Hourigan and Aisling Leavy has been awarded the C. Oswald George prize for 2021 This paper describes an investigation involving active collecting of personal data and exploring patterns in the data, to introduce students aged 11-12 years to their first experiences of thinking about association between continuous variables. The teaching exercise was also part of preservice training, with two teacher educators working alongside five preservice primary teachers to design and implement the statistical investigation to introduce statistical association, and support future development. The lesson was taught by two preservice teachers and small group work was facilitated by the other preservice teachers and the teacher educators. The investigation was into jump height and jump length, involving careful consideration of experiment, measurement and data collection conditions. The students were then asked to attempt graphical representation of their data, leading to discussion and questions of what is relationship and how to represent it. On then being shown a scatterplot for the first time, the students moved through questions of reading the data, reading between the data and reading beyond the data. Amongst other observations, it was noted that young students tend to case-oriented views to tackle new concepts but also “possess the potential to understand the concepts of statistical association as well as the communicative function of scatter plots”. The lesson provides authentic learning experiences for both students and preservice teachers, and combines excellent statistical pedagogy and good practice in teaching statistical thinking with sound grounding in the scholarly literature of educational research. The clear exposition of this combined but authentic approach provides interesting reading for all, at any level, who aim to teach statistics from an enquiryoriented student-based approach, as it provides valuable insight into students' reactions to first meeting of this key statistical concept, its graphical representation, attendant ideas of variation and estimation, with concomitant learning for preservice primary teachers. By concluding with thoughtful reflections and suggestions for improvement of this lesson for both students and teachers, the paper reinforces its demonstration of combining scholarly work, sound pedagogy, good practice in teaching statistics, and authentic understanding of what is important in statistics to produce an interesting and thought-provoking learning experience and paper. Congratulations to the authors for their excellent paper.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41411176","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}
{"title":"Thanks to all","authors":"H. MacGillivray","doi":"10.1111/test.12299","DOIUrl":"https://doi.org/10.1111/test.12299","url":null,"abstract":"Thank you to Teaching Statistics Trust members, editorial board members, reviewers, authors and readers of this unique and important journal. For everyone involved with teaching, whether at school, tertiary or in the workplace, the past two years have been challenging. I particularly extend deep gratitude to all our reviewers who put so much thought and effort into this very important professional work which often does not receive the appreciation from authorities that it should. The effects and influences of SARS-CoV-2 (Covid 19) on society and on teaching, as well as the increasing work to further learning in statistics and data science, have been reflected in the admirable efforts, initiatives and thinking of authors. I particularly wish to thank everyone involved in the special issue published in 2021, Teaching Data Science and Statistics: foundation and introductory. The success of the excellent work by authors and reviewers is evidenced by the many downloads and enquiries. My coeditors Jim Ridgway and Rob Gould were outstanding in all aspects of their work. It is not easy to develop and implement good practice in teaching statistics and data science, nor is it easy to write well and meet scholarly writing standards about it. But these efforts are some of the most important in education, particularly at foundation and introductory levels across all disciplines, and the challenges are also opportunities to further this work. Best wishes for 2022 and keep contributing to inspiring, teaching and writing about best practices in our International Journal for Statistics and Data Science Teaching.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46975525","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}
{"title":"Teaching Statistics Trust prize for 2021 special issue","authors":"H. MacGillivray","doi":"10.1111/test.12298","DOIUrl":"https://doi.org/10.1111/test.12298","url":null,"abstract":"Teaching Statistics are happy to announce that the Teaching Statistics Trust has awarded a prize for the best paper in the 2021 special issue, Teaching Data Science and Statistics: foundation and introductory, to Anna Fergusson and Chris Wild for their paper On traversing the data landscape: Introducing APIs to data-science students. Statistics and data science and their teaching are intrinsically linked. This is seen not only in the increasing inclusion of technology in teaching statistics, but also in the data and contexts considered, and the broadening of statistical issues, explorations, presentations, and discussions at introductory levels, whether school, undergraduate or postgraduate/workplace in other disciplines. The intent of the special issue is to provide impetus and inspiration to all readers and authors in furthering this progress, and to celebrate the new subtitle of the journal, in the increasing awareness of what data science is, and how statistics and data science work together in tackling real and complex datasets and problems involving complex data. Data science is much more than a new set of tools it opens doors to whole new ways of thinking about information, explanation, and action, and the special issue demonstrates what an extraordinarily rich field this is and just how much challenge and opportunity there are that could, and should, be considered by the statistical and data science community. Amongst the excellent papers illustrating a wide variety of approaches and offering some very rich examples for teaching in this emerging space, the special issue editors, after much debate, chose the winning paper because of the importance of harvesting the vast amounts of data now available combined with authentic student engagement in enquiry-based learning in a fun and universally appealing context. The pedagogic approach is an excellent demonstration of the long-time advocacy of leading statisticians and statistical educators of students learning of technical tools and statistical thinking via graduated needs arising in the tackling of a real data investigation that piques student curiosity and exploration. The proposal, using APIs, is unique and cutting edge, but is explained in an extremely clear way. It centers on the importance of the data gathering phase in data science (at least when it comes to data scraping), and mastery of this skill not only empowers students, but teaches them that the internet really is just organized data. However such approaches cannot succeed without careful scaffolding, preparation and deep understanding of student needs in learning about data. Students move from immersion in a search activity (for photos) to URL hacking and GUIdriven tools, to thinking of variables and then to API’s. Graphical explorations are then encouraged to at least partially discuss some of the questions that have arisen during a student’s personal journey in the investigation. The approach is simple, well written, directl","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42223476","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}
{"title":"16th Conference of The Mathematics Education for the Future Project: Building on the Past to Prepare for the Future, King's College, Cambridge University, UK, Aug 8‐13, 2022","authors":"","doi":"10.1111/test.12294","DOIUrl":"https://doi.org/10.1111/test.12294","url":null,"abstract":"","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42128766","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}
{"title":"Statistical meaningfulness, teaching craft and writing about teaching statistics and data science","authors":"H. MacGillivray","doi":"10.1111/test.12300","DOIUrl":"https://doi.org/10.1111/test.12300","url":null,"abstract":"In this issue we celebrate the awarding of three prizes for papers on good practice in teaching statistics and data science: the C Oswald George prize for best paper in Teaching Statistics issues 1 to 3 in 2021; the Peter Holmes prize for highlighting excellence in motivating practical classroom activity in these issues; and the Teaching Statistics Trust prize for best paper in the 2021 special issue on Teaching Data Science and Statistics. The announcements and citations for these three papers may be found in this issue. These papers significantly add to the demonstration of the work across the world in developing, implementing, sustaining and researching good practice in teaching statistics and data science, and this issue also includes editorial thanks and appreciation to all who contribute to the writing on such good practice authors, reviewers, the Teaching Statistics Trust and publisher Wiley. There is substantial need for, and considerable appreciation of, more writing of high standard on good practice in teaching statistics and data science. Full text downloads of papers in Teaching Statistics increased by approximately 30% from 2016 to 2020, but increased again by more than 33% in just the first 10 months of 2021 with the addition of the special issue. There is also need for a substantial cultural shift with greater acknowledgement and respect for the skills and expertise required for good teaching of statistics and data science in and across all disciplines, especially foundation and introductory, and for creditable and refereed writing on good practice in such teaching in its development, implementation, sustainment, evaluation and research. Hence there is need for understanding of both what constitutes good practice in teaching statistics and data science, and what constitutes good writing and researching such practice. Although there has been much discussion over the past three decades on the former, this discussion must be ongoing and constantly evolve to reflect the constantly evolving and dynamic nature of statistics and data science as they develop diverse capabilities (methodological, conceptual, and technological) to tackle increasingly complex and large problems in wideranging real contexts. Clearly the first requirement of the latter is that it must be about good practice in the teaching. However it should also satisfy criteria of scholarly writing but appropriate for the very large community of all those who teach statistics and data science. In the interests of reader convenience, I am now going to use the word “statistics” instead of “statistics and data science” to include everything to do with thought, endeavours and professional practice involving chance, variation and data, without attempting to describe any internal or external possible “boundaries”. There has been much emphasis over many decades that good statistics teaching must reflect the good practice of statistics, but the parallels between the two are far deepe","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48971998","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}
{"title":"Peter Holmes Prize Announcement 2021","authors":"H. MacGillivray","doi":"10.1111/test.12297","DOIUrl":"https://doi.org/10.1111/test.12297","url":null,"abstract":"The article entitled “Discovering experimental design: An interactive teaching exercise using Fisher’s tea-tasting experiment” by Thomas Fanshawe has been awarded the Peter Holmes prize for 2021. The aim of this prize is to highlight excellence in motivating practical classroom activity. This article describes using a classic experiment in an active learning, student discovery preliminary to experimental design in an introductory medical statistics module whose aim is for students to gain an understanding of statistics applied to biomedical science. It is written extremely clearly but succinctly, with pleasing historical context and details invaluable to anyone using a student discovery approach in a time-poor course in another discipline, especially professional disciplines with students demanding usefulness and engagement but also efficient use of time. The summary of student group designs, of small but important changes made based on student feedback, and practical tips for consistency in teaching approaches are as helpful as they are clear. The author’s comments such as “The diverging opinions that arose over design choices were a microcosm of discussions that arise when designing real-life experimental studies” are both interesting and useful. This concise but well-planned learning experience provided a useful foundation for a later class dedicated to medical study design, and opportunities to learn points relating to the connection between design and analysis. However the exercise is readily amenable to adaptation for students at different levels of education and ability. Overall, this article embodies the aim and spirit of the Peter Holmes prize in an excellent demonstration of a practical and fun classroom activity, embodying authentic student discovery practice within a design environment. Congratulations to the author for this excellent paper. 1 | HISTORY OF THE PRIZE","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49050454","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}
Kim L. Austerschmidt, Alexander Stappert, Hanna Heusel, Sarah Bebermeier
{"title":"Using a video presentation on variance and covariance in the teaching of statistics","authors":"Kim L. Austerschmidt, Alexander Stappert, Hanna Heusel, Sarah Bebermeier","doi":"10.1111/test.12292","DOIUrl":"https://doi.org/10.1111/test.12292","url":null,"abstract":"We outline the use and evaluation of a video presentation about variance and covariance developed to motivate students to process the topics and to enhance their skills. We outline the structure and the content of the video presentation and present data of an evaluation study. Students in different subjects who must pass statistics courses (N = 114) participated in an online survey with randomized controlled design and repeated measurement. Results indicate that students who watched the video presentation significantly improved on their skills, compared to a control group reading a textbook section about the same topics. The video presentation was judged as more satisfying and useful for learning than the text. We discuss application scenarios and further teaching implications. Ideally a longitudinal study should investigate effects of continuous learning with video presentations, changes in motivation, anxiety, and attitudes as well as effects for students of different subjects.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47878658","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}
{"title":"Take a chance on statistical edutainment","authors":"L. Lesser, D. Pearl","doi":"10.1111/test.12293","DOIUrl":"https://doi.org/10.1111/test.12293","url":null,"abstract":"Chances are that edutainment fun items can engage students in discussing and learning key concepts about probability.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43219085","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}
J. L. Hsu, Abram J. Jones, Jia-Huei Lin, You-Ren Chen
{"title":"Data visualization in introductory business statistics to strengthen students' practical skills","authors":"J. L. Hsu, Abram J. Jones, Jia-Huei Lin, You-Ren Chen","doi":"10.1111/test.12291","DOIUrl":"https://doi.org/10.1111/test.12291","url":null,"abstract":"The objective of this study is to present and discuss how data visualization can be incorporated into teaching approaches by business faculty in introductory business statistics to strengthen business students' practical skills. Data visualization lessens difficulties in learning statistics by providing opportunities to illustrate analytical findings in graphic form, which is essential for learners with different learning styles. Familiarizing students with Excel, Python, or other software in introductory business statistics is beneficial in helping them attain statistical literacy by analyzing real‐world data such as COVID‐19 statistics. Using such data equips students with knowledge of statistical implementation—a core skill in the business world.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46523514","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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