{"title":"“I LOVE MATH ONLY IF IT'S CODING”: A CASE STUDY OF STUDENT EXPERIENCES IN AN INTRODUCTION TO DATA SCIENCE COURSE","authors":"Erica Heinzman","doi":"10.52041/serj.v21i2.43","DOIUrl":null,"url":null,"abstract":"Many important voices--including The National Council for Teachers of Mathematics (NCTM), the Dana Center’s Launch Years initiative, and others--advocate for expanding the traditional course offerings in high school mathematics and statistics to include courses such as the Introduction to Data Science (IDS). To date, the research on the IDS course has primarily focused on pedagogy, professional learning for teachers, and the curriculum. This mixed-methods case study expands our understanding by analyzing the perspective of IDS students at a California public high school. Self-determination theory provides a useful frame for interpreting how these students experience the IDS course. The theory focuses on conditions for students to engage in meaningful learning: competence (self-efficacy), autonomy (agency), and relatedness (a sense of belonging). The findings from this case study suggest the IDS students feel confident, empowered, and part of a vibrant community, unlike previous mathematics and statistics courses they may have completed; and use specific language to describe their joy in problem-solving and the accessibility of the course. These findings have implications for the development and refinement of any high school data science course, including IDS.","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":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics Education Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52041/serj.v21i2.43","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: 2
Abstract
Many important voices--including The National Council for Teachers of Mathematics (NCTM), the Dana Center’s Launch Years initiative, and others--advocate for expanding the traditional course offerings in high school mathematics and statistics to include courses such as the Introduction to Data Science (IDS). To date, the research on the IDS course has primarily focused on pedagogy, professional learning for teachers, and the curriculum. This mixed-methods case study expands our understanding by analyzing the perspective of IDS students at a California public high school. Self-determination theory provides a useful frame for interpreting how these students experience the IDS course. The theory focuses on conditions for students to engage in meaningful learning: competence (self-efficacy), autonomy (agency), and relatedness (a sense of belonging). The findings from this case study suggest the IDS students feel confident, empowered, and part of a vibrant community, unlike previous mathematics and statistics courses they may have completed; and use specific language to describe their joy in problem-solving and the accessibility of the course. These findings have implications for the development and refinement of any high school data science course, including IDS.
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.