“I LOVE MATH ONLY IF IT'S CODING”: A CASE STUDY OF STUDENT EXPERIENCES IN AN INTRODUCTION TO DATA SCIENCE COURSE

Q3 Social Sciences
Erica Heinzman
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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.
“只有当数学是编码的时候,我才喜欢它”:数据科学导论课程中学生体验的个案研究
许多重要的声音——包括全国数学教师委员会(NCTM)、达纳中心的启动年倡议等——都主张扩大高中数学和统计学的传统课程,将数据科学导论(IDS)等课程包括在内。迄今为止,对IDS课程的研究主要集中在教育学、教师专业学习和课程方面。这个混合方法的案例研究通过分析加州公立高中IDS学生的观点来扩展我们的理解。自决理论为解释这些学生如何体验IDS课程提供了一个有用的框架。该理论关注学生进行有意义学习的条件:能力(自我效能)、自主性(能动性)和关联性(归属感)。这个案例研究的结果表明,IDS的学生感到自信、有力量,是一个充满活力的社区的一部分,这与他们以前可能完成的数学和统计学课程不同;并用特定的语言描述他们解决问题的乐趣和课程的可及性。这些发现对包括IDS在内的任何高中数据科学课程的开发和完善都有启示。
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来源期刊
Statistics Education Research Journal
Statistics Education Research Journal Social Sciences-Education
CiteScore
1.30
自引率
0.00%
发文量
46
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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