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Data Science : = A Gateway to Belonging in Stem and Other Quantitative Fields.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data Science :/
其他題名:	A Gateway to Belonging in Stem and Other Quantitative Fields.
作者:	Lamar, Tanya Mae.
面頁冊數:	1 online resource (229 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-04, Section: A.
Contained By:	Dissertations Abstracts International85-04A.
標題:	Mathematics education. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30615130click for full text (PQDT)
ISBN:	9798380470339

Data Science : = A Gateway to Belonging in Stem and Other Quantitative Fields.
Lamar, Tanya Mae.

Data Science :A Gateway to Belonging in Stem and Other Quantitative Fields. - 1 online resource (229 pages)

Source: Dissertations Abstracts International, Volume: 85-04, Section: A.

Thesis (Ph.D.)--Stanford University, 2023.

Includes bibliographical references

The divide between those who do and those who do not excel in mathematics is patterned in problematic ways. Women and people of color are typically underrepresented in Science, Technology, Engineering, and Math (STEM) and other quantitative fields (ex. Finance) where mathematics plays gatekeeper. However, mathematics is not a subject these groups of people are somehow less capable of learning (Chesnut et al., 2018). Instead, this imbalance points to issues within the education system where only a narrow group of students' needs are being met, constituting a history of institutionalized sexism, racism and classism. The current U.S. math education system seems to value a narrow and antiquated set of skills which necessarily result in only a small group of students succeeding at the highest levels. Students spend their time learning to reproduce a list of methods and procedures that have been in place since the 1800's even though this type of work can be done more quickly and accurately by an average smart phone (Education Association, 1894; Wolfram, 2020).Meanwhile the real world is bursting with data, and students rarely learn how to make sense of it or wield its power. The ability to analyze and make sense of complex data is a skill that can help solve problems on a global scale including issues faced by the environment, world health, the economy, and more. Further, students are tasked with making sense of data on a regular basis as technology has become a part of daily life. While technology has automated many jobs, only humans can think critically about contextual factors and circumstances to inform interpretations of mathematical models and data analyses. This type of creative mathematical thinking is what students need to be learning in the 21stcentury and the implementation of this change constitutes the focus of this dissertation study.The field of data science education is at an especially critical point in its expansion as secondary schools are beginning to offer formal mathematics courses on the topic. Researchers posit that the real world and authentic nature of the content will invite a wide range of student interests, and a widening of opportunities to find belonging in mathematics (LaMar & Boaler, 2021). However, being that the field of data science education research is still in its infancy, very little is known about how students experience data science learning.This mixed-methods dissertation study focuses on how an experience in a high school data science course led students to shift their feelings of belonging in STEM and other quantitative fields. Participants in this study came from Willow High School, located in a suburb of the San Francisco Bay Area and include all consented students enrolled in Ms. Weber's 12th grade Data Science course as well as Ms. Weber herself. The data that informs this study consists of 25 days of classroom observation, pre- and post- course student surveys, a series of interviews with Ms. Weber as well as a series of interviews with the enrolled students conducted at the beginning, middle, and end of the school year. The student participants include all 20 enrolled students with documented consent to participate, with an in-depth look at the data associated with 12 focal students.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798380470339Subjects--Topical Terms:

641129
Mathematics education.
Index Terms--Genre/Form:

542853
Electronic books.

Data Science : = A Gateway to Belonging in Stem and Other Quantitative Fields.
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