{"title":"INTRODUCING HIGH SCHOOL STATISTICS TEACHERS TO PREDICTIVE MODELLING BY EXPLORING DYNAMIC MOVIE RATINGS DATA: A FOCUS ON TASK DESIGN","authors":"Anna-Marie Fergusson, M. Pfannkuch","doi":"10.52041/serj.v21i2.49","DOIUrl":null,"url":null,"abstract":"With the advent of data science, recommendations for teaching statistical modelling include adopting a greater focus on prediction. However, there has been minimal research about the design of tasks for teaching predictive modelling from a data science. Therefore, a design-based research approach was used to develop a new web-based task that explored: accessing and using dynamic movie ratings data from an API; developing a model to generate prediction intervals; and modifying and running provided R code in the browser. The task was implemented within a face-to-face teaching experiment involving six high school statistics teachers. Analysis of the teacher responses to the task identified four key task design features that appeared to stimulate development of statistical and computational ideas related to predictive modelling and APIs.","PeriodicalId":38581,"journal":{"name":"Statistics Education Research Journal","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics Education Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52041/serj.v21i2.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 3
Abstract
With the advent of data science, recommendations for teaching statistical modelling include adopting a greater focus on prediction. However, there has been minimal research about the design of tasks for teaching predictive modelling from a data science. Therefore, a design-based research approach was used to develop a new web-based task that explored: accessing and using dynamic movie ratings data from an API; developing a model to generate prediction intervals; and modifying and running provided R code in the browser. The task was implemented within a face-to-face teaching experiment involving six high school statistics teachers. Analysis of the teacher responses to the task identified four key task design features that appeared to stimulate development of statistical and computational ideas related to predictive modelling and APIs.
期刊介绍：
SERJ is a peer-reviewed electronic journal of the International Association for Statistical Education (IASE) and the International Statistical Institute (ISI). SERJ is published twice a year and is free. SERJ aims to advance research-based knowledge that can help to improve the teaching, learning, and understanding of statistics or probability at all educational levels and in both formal (classroom-based) and informal (out-of-classroom) contexts. Such research may examine, for example, cognitive, motivational, attitudinal, curricular, teaching-related, technology-related, organizational, or societal factors and processes that are related to the development and understanding of stochastic knowledge. In addition, research may focus on how people use or apply statistical and probabilistic information and ideas, broadly viewed. The Journal encourages the submission of quality papers related to the above goals, such as reports of original research (both quantitative and qualitative), integrative and critical reviews of research literature, analyses of research-based theoretical and methodological models, and other types of papers described in full in the Guidelines for Authors. All papers are reviewed internally by an Associate Editor or Editor, and are blind-reviewed by at least two external referees. Contributions in English are recommended. Contributions in French and Spanish will also be considered. A submitted paper must not have been published before or be under consideration for publication elsewhere.
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