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Proceedings of the IASE 2021 Satellite Conference最新文献

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Reimagining online statistical education for accelerated teaching and learning; a perspective from West Africa 重新构想在线统计教育，促进教学和学习;来自西非的视角
Proceedings of the IASE 2021 Satellite Conference Pub Date : 1900-01-01 DOI: 10.52041/iase.cvino
Owiredu Emmanuel Odame, A. Adebanji
{"title":"Reimagining online statistical education for accelerated teaching and learning; a perspective from West Africa","authors":"Owiredu Emmanuel Odame, A. Adebanji","doi":"10.52041/iase.cvino","DOIUrl":"https://doi.org/10.52041/iase.cvino","url":null,"abstract":"Electronic learning (e-learning) swiftly became the essential mode of teaching during the COVID-19 pandemic. Higher Education Institutions had to immediately migrate all in-person classes online. This posed some learning challenges to a lot of students especially those residing in more remote locations with inadequate online learning devices and poor internet facilities This study documents the online learning experiences of some undergraduate Statistics and Actuarial Science students from Kwame Nkrumah University of Science and Technology, Ghana, during COVID-19 lockdown. The responses revealed that majority (42.2%) of the students’ preferred in-person learning, some preferred online (18.6%), and hybrid method (39%). Internet access was through MTN (60%), Vodafone (24%) and Airteltigo (14%). Multinomial logistic regression analysis was employed to identify determining factors for student preferred mode of teaching and results showed internet service provider, place of residence, gender and program of study as significant.","PeriodicalId":189852,"journal":{"name":"Proceedings of the IASE 2021 Satellite Conference","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114782976","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}
引用次数: 0
Enhancing data literacy at an early stage: Primary school pupils’ precursor ideas of covariation 早期提高数据素养:小学生协变的先兆概念
Proceedings of the IASE 2021 Satellite Conference Pub Date : 1900-01-01 DOI: 10.52041/iase.kjrrp
Martin Andre, Daniel Frischemeier, C. Schneider
{"title":"Enhancing data literacy at an early stage: Primary school pupils’ precursor ideas of covariation","authors":"Martin Andre, Daniel Frischemeier, C. Schneider","doi":"10.52041/iase.kjrrp","DOIUrl":"https://doi.org/10.52041/iase.kjrrp","url":null,"abstract":"Covariational reasoning can already be enhanced in primary school. Anyway, given that pupils do not know conventional notations like coordinate systems in the first grades, addressing ideas of covariation is a challenging task. In our study, we show that 1st graders’ (6-7 years) ideas of covariation already exist in a precursor way and can be addressed by specific tasks based on data from Gapminder’s photo database Dollar Street. Using a design-based research approach, we developed and implemented semi-digital learning trajectories to enhance pupils’ data literacy at a very early stage. Interactions between young learners are observed to gain insights (a) into their covariational thinking when working on these specific tasks and (b) for iteratively re-designing the learning trajectories. Our observations define an early starting point for learning processes of covariational reasoning and the learning trajectories give opportunities to address issues of sustainable development.","PeriodicalId":189852,"journal":{"name":"Proceedings of the IASE 2021 Satellite Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129938780","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}
引用次数: 1
Just Simulate It! Introducing Computing Through Simulation Studies in a Second Statistics Course 只是模拟它!在第二统计学课程中介绍通过模拟研究计算
Proceedings of the IASE 2021 Satellite Conference Pub Date : 1900-01-01 DOI: 10.52041/iase.kwmvx
Aimee Schwab-McCoy
{"title":"Just Simulate It! Introducing Computing Through Simulation Studies in a Second Statistics Course","authors":"Aimee Schwab-McCoy","doi":"10.52041/iase.kwmvx","DOIUrl":"https://doi.org/10.52041/iase.kwmvx","url":null,"abstract":"Introductory data science courses provide students with a computational foundation beyond traditional introductory courses. Even in the intro stats course, many students are using R to support their coursework rather than applet or “point-and-click” software systems. Introducing computation earlier in the statistics and data science curriculum enables students to work deeper and sooner with real data sets. Changes in early statistics and data science education have a ripple effect across the curriculum. As the introductory courses are modernized, the later courses must change too. The class described in this paper is a second-semester statistical modeling course with a modern, post-data science flair. Regression models are introduced separately (multiple regression, Poisson regression, logistic regression) before being generalized as the generalized linear model (GLM). In this class, learners studied the patterns and behaviors of these models through targeted labs leaning heavily on simulated data. This course emphasizes the development of statistical intuition through hands-on learning experiences, rather than a set of rules for each situation.","PeriodicalId":189852,"journal":{"name":"Proceedings of the IASE 2021 Satellite Conference","volume":"426 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131719110","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}
引用次数: 0
Data science for youth in the time of COVID 新冠肺炎时代的青年数据科学
Proceedings of the IASE 2021 Satellite Conference Pub Date : 1900-01-01 DOI: 10.52041/iase.hmtse
J. Mokros, Jacob Sagrans, P. Noyce
{"title":"Data science for youth in the time of COVID","authors":"J. Mokros, Jacob Sagrans, P. Noyce","doi":"10.52041/iase.hmtse","DOIUrl":"https://doi.org/10.52041/iase.hmtse","url":null,"abstract":"Through the “COVID-Inspired Data Science through Epidemiology Education” project, 400 underserved middle-school youth across the United States are engaging in a 20-hour out-of-school data club centered on a novel. The narrative is integrated with hands-on data activities and modeling (e.g., creating graphs of infections over time in CODAP; modeling disease transmission rates in NetLogo). Youth learn to: 1) Use data tools to track the spread of a variety of infectious diseases; 2) Ask and address their own questions of data; and 3) Use data to communicate to local audiences about epidemiological patterns and challenges. The project breaks new ground in integrating data science with epidemiology education for 11–14-year-old youth.","PeriodicalId":189852,"journal":{"name":"Proceedings of the IASE 2021 Satellite Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134082690","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}
引用次数: 1
Combining Social Betterment and Inclusive Teaching Via Discussion Boards in Basic and Intermediate Statistics 从基础统计与中级统计的讨论区看社会改善与包容性教学的结合
Proceedings of the IASE 2021 Satellite Conference Pub Date : 1900-01-01 DOI: 10.52041/iase.aqnfz
Ngoc Phan, Crystal Luce, Courtney Donovan
{"title":"Combining Social Betterment and Inclusive Teaching Via Discussion Boards in Basic and Intermediate Statistics","authors":"Ngoc Phan, Crystal Luce, Courtney Donovan","doi":"10.52041/iase.aqnfz","DOIUrl":"https://doi.org/10.52041/iase.aqnfz","url":null,"abstract":"To use Statistics and Data Science courses to address social injustice, our methods of teaching must aid in deconstructing oppressive ideologies. To truly facilitate transformative learning, we must start by examining how our pedagogies reinforce dominant narratives and silence marginalized perspectives. This requires intentional reflexive methods to create inclusive spaces where individuals critically engage with the material. Mark, Henry, & Julnes (2000) define Social Betterment as “the reduction or prevention of social problems, the improvement of social conditions, and the alleviation of human suffering.” Inclusive Teaching is a pedagogy that focuses on the needs of all students to support course engagement and includes a range of approaches geared towards creating a space that decenters whiteness in statistics education. We combine these into a framework that encourage transformative discourse in introductory and intermediate statistics courses through application discussions alongside content learning.","PeriodicalId":189852,"journal":{"name":"Proceedings of the IASE 2021 Satellite Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132883103","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}
引用次数: 0
Statistical education and official statistics - training future data scientists 统计教育和官方统计——培养未来的数据科学家
Proceedings of the IASE 2021 Satellite Conference Pub Date : 1900-01-01 DOI: 10.52041/iase.lciru
M. Puloka, S. Budgett, M. Pfannkuch
{"title":"Statistical education and official statistics - training future data scientists","authors":"M. Puloka, S. Budgett, M. Pfannkuch","doi":"10.52041/iase.lciru","DOIUrl":"https://doi.org/10.52041/iase.lciru","url":null,"abstract":"EMOS (The European Master in Official Statistics) was set up to strengthen the collaboration within academia and producers of official statistics and help develop professionals able to work with European official data at different levels in the fast-changing production system of the 21st century. In this paper we address the need for training in Official Statistics, particularly in current times, where new skill sets and competencies are necessary. In particular, the needs for new data sources currently used by national statistical systems require the development of new methodologies. For that purpose, we do a matching between National Statistical Offices (NSO) needs and the offer from universities.","PeriodicalId":189852,"journal":{"name":"Proceedings of the IASE 2021 Satellite Conference","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115739928","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}
引用次数: 0
An analysis of media items about the Coronavirus pandemic: New insights for statistical literacy 关于冠状病毒大流行的媒体报道分析:统计素养的新见解
Proceedings of the IASE 2021 Satellite Conference Pub Date : 1900-01-01 DOI: 10.52041/iase.htbhr
I. Gal, V. Geiger
{"title":"An analysis of media items about the Coronavirus pandemic: New insights for statistical literacy","authors":"I. Gal, V. Geiger","doi":"10.52041/iase.htbhr","DOIUrl":"https://doi.org/10.52041/iase.htbhr","url":null,"abstract":"Despite repeated calls for development of statistical literacy among citizens, in fact there is a dearth of recent systematic empirical research on the actual mathematical and statistical demands of mainstream media. Hence, this study aimed to develop a typology of the content of mathematical and statistical products and demands in the COVID-19 pandemic media, given the criticality of such information to citizens and societies alike. We conducted content-analysis of a purposive sample of over 300 media items from digital news sources based in four countries with different profiles. The analysis generated nine categories of new or enhanced types of knowledge and skill demands evident in the media items analyzed, such as regarding models and causality, data quality and strength of evidence, comparative thinking, literacy and language, official data sources, critical interpretation, and more. We discuss implications for current conceptual models and for instructional efforts focused on statistical literacy.","PeriodicalId":189852,"journal":{"name":"Proceedings of the IASE 2021 Satellite Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121878822","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}
引用次数: 0
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