{"title":"Visualizing statistical edutainment: What you see is what you get","authors":"L. Lesser, Dennis K. Pearl","doi":"10.1111/test.12355","DOIUrl":"https://doi.org/10.1111/test.12355","url":null,"abstract":"Concepts of data visualization are explored using statistics educational fun items and illustrated by sharing results from the experiment we conducted on cartoon captions.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"131 - 142"},"PeriodicalIF":0.8,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45808309","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":"Authors' response to Michael Martin","authors":"Dennis K. Pearl, L. Lesser","doi":"10.1111/test.12354","DOIUrl":"https://doi.org/10.1111/test.12354","url":null,"abstract":"","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"146 - 147"},"PeriodicalIF":0.8,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49510854","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":"Media Covid misinformation due to confounding","authors":"Matthew Brenneman, R. L. Pierce","doi":"10.1111/test.12352","DOIUrl":"https://doi.org/10.1111/test.12352","url":null,"abstract":"We discuss a case study on how misinformation regarding Covid‐19 health outcomes can arise due to confounding. Data from the UK on mortality rates suggest that people who have some level of vaccination and contract the Delta variant of Covid are twice as likely to die than those who are unvaccinated. Age, however, a confounding variable, when accounted for, produces a more complicated picture. The mortality rates for the vaccinated are statistically lower than the unvaccinated for the older but not younger age group. We present several approaches for teaching confounding to help students better understand this underemphasized concept's cause, effects, and origins.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"158 - 166"},"PeriodicalIF":0.8,"publicationDate":"2023-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42289560","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":"Reducing statistics anxiety and academic procrastination among Israeli students: A pilot program","authors":"Mazi Kadosh, Meirav Hen, J. Ferrari","doi":"10.1111/test.12356","DOIUrl":"https://doi.org/10.1111/test.12356","url":null,"abstract":"Many college students consider statistical courses as frightening and demanding, yielding high anxiety and low competence, and correlating with maladaptive academic behaviors and low achievement. With undergraduate students, the present pre‐post study compared a supportive online teaching program utilizing mandatory statistical exercises (n = 37) with a no intervention, optional exercise statistics class (n = 32). We evaluated whether our statistics teaching intervention decreased test anxiety and academic procrastination and increased academic self‐efficacy and academic achievements. Results indicated a decrease in academic procrastination and test anxiety at course end for intervention group and an increase in test anxiety for control group. At the end of the course intervention group reported higher academic self‐efficacy and achievements. Teaching statistics using mandatory supportive activities might contribute to more positive psychological outcomes (eg, higher academic self‐efficacy and lower academic procrastination) and higher academic achievements.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"167 - 175"},"PeriodicalIF":0.8,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46566607","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":"Truth in edutainment: What you get is what you see","authors":"Michael A. Martin","doi":"10.1111/test.12353","DOIUrl":"https://doi.org/10.1111/test.12353","url":null,"abstract":"Discussion of “Visualizing statistical edutainment: What you see is what you get” by Lesser and Pearl.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"143 - 145"},"PeriodicalIF":0.8,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42934586","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":"What goes before the CART? Introducing classification trees with Arbor and CODAP","authors":"Tim Erickson, J. Engel","doi":"10.1111/test.12347","DOIUrl":"https://doi.org/10.1111/test.12347","url":null,"abstract":"This volume is largely about nontraditional data; this paper is about a nontraditional visualization: classification trees. Using trees with data will be new to many students, so rather than beginning with a computer algorithm that produces optimal trees, we suggest that students first construct their own trees, one node at a time, to explore how they work, and how well. This build‐it‐yourself process is more transparent than using algorithms such as CART; we believe it will help students not only understand the fundamentals of trees, but also better understand tree‐building algorithms when they do encounter them. And because classification is an important task in machine learning, a good foundation in trees can prepare students to better understand that emerging and important field. We also describe a free online tool—Arbor—that students can use to do this, and note some implications for instruction.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"S104 - S113"},"PeriodicalIF":0.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45198100","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":"The possibilities of exploring nontraditional datasets with young children","authors":"Lucía Zapata-Cardona","doi":"10.1111/test.12349","DOIUrl":"https://doi.org/10.1111/test.12349","url":null,"abstract":"Today's world is characterized by the extensive production of data in different scenarios that everyday citizens need to understand for their informed participation in society. With the increase in the availability of data in a society defined by the industrious production of data, the educational system needs to think of possibilities to bring young children closer to the world of data science. This paper presents a nontraditional data exploration experience with an 8‐year‐old participant helped by a data visualization tool. A task‐based interview was conducted while the participant explored a carbon dioxide emission dataset. This paper studied how the participant interrogates the data, draws inferences and exhibits dispositions. At the end, some reflections are presented when introducing the exploration of nontraditional data in teaching.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"S22 - S29"},"PeriodicalIF":0.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43640408","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":"M in CoMputational thinking: How long does it take to read a book?","authors":"Kym Fry, K. Makar, J. Hillman","doi":"10.1111/test.12348","DOIUrl":"https://doi.org/10.1111/test.12348","url":null,"abstract":"Even at the primary level, computational thinking (CT) can support young students to prepare for participating in futures that are immersed in data. In mathematics classrooms, there are few explanations of the ways CT can support students in formulating and solving complex problems. This paper presents an example of a primary classroom investigation (8‐9 year olds) over seven lessons of the problem “How long does it take to read a book?” The aim is to illustrate ways a statistical investigation can provide context for CT and demonstrate how the two complement each other to solve problems involving mathematics. The findings highlight opportunities and challenges that students face across the elements of CT—decomposition, abstraction, pattern recognition and modelling, and generalization and algorithmic thinking, including recommendations for teaching.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"S30 - S39"},"PeriodicalIF":0.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42538853","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":"Reflections on gaze data in statistics education","authors":"L.B.M.M. Boels","doi":"10.1111/test.12340","DOIUrl":"https://doi.org/10.1111/test.12340","url":null,"abstract":"Gaze data are still uncommon in statistics education despite their promise. Gaze data provide teachers and researchers with a new window into complex cognitive processes. This article discusses how gaze data can inform and be used by teachers both for their own teaching practice and with students. With our own eye‐tracking research as an example, background information on eye‐tracking and possible applications of eye‐tracking in statistics education is provided. Teachers indicated that our eye‐tracking research created awareness of the difficulties students have when interpreting histograms. Gaze data showed details of students' strategies that neither teachers nor students were aware of. With this discussion paper, we hope to contribute to the future usage and implementation of gaze data in statistics education by teachers, researchers, educational and textbook designers, and students.","PeriodicalId":43739,"journal":{"name":"Teaching Statistics","volume":"45 1","pages":"S40 - S51"},"PeriodicalIF":0.8,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45337642","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}