國立虎尾科技大學 |

Essays on Statistics and Data Science Education.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Essays on Statistics and Data Science Education./
作者:	Klugman, Emma Mary.
面頁冊數:	1 online resource (146 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
Contained By:	Dissertations Abstracts International85-12B.
標題:	Science education. -
電子資源:	click for full text (PQDT)
ISBN:	9798382777528

Essays on Statistics and Data Science Education.
Klugman, Emma Mary.

Essays on Statistics and Data Science Education. - 1 online resource (146 pages)

Source: Dissertations Abstracts International, Volume: 85-12, Section: B.

Thesis (Ph.D.)--Harvard University, 2024.

Includes bibliographical references

Statistics & data science are growing, rapidly evolving, and increasingly important for an informed citizenry in a data-saturated world. In this dissertation, I address two central questions: (1) who is taking statistics? and (2) what are statistics courses teaching?I estimate that 920,000 US students take statistics in high school each year, but this population has not yet been well studied. Using a rich set of survey responses describing 15,727 students' demographics, career interests and values, STEM identity, grades, and test scores, my first study compares four groups of high-school course-takers: those who take statistics, calculus, both, and neither. I then employ latent profile analysis to shed light on who these students are, showing that students with different profiles take statistics at surprisingly similar rates: statistics is as an important part of the academic pathway for a wide range of students and serves a demographically diverse population.In my second study, I build upon tools from natural language processing and psychometric measurement to develop a human-in-the-loop methodology for measuring latent constructs in large text corpora, and present a framework for doing so. I construct a lexicon-based instrument to measure the extent to which syllabi from college statistics and data science courses align with a vision for modernizing instruction set forth in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) project and across 145 journal articles spanning almost a century. In so doing, I illustrate an approach that researchers can take in bringing measurement questions to text data, a method that I believe strikes a useful balance between interpretability, communicability, validity, and scalability.My final study applies these instruments to 32,483 syllabi from US statistics and data science courses taught between 2010 and 2018. I find a modest overall increase in modern approaches over this decade. Finally, I explore differences between institution types using multilevel models, finding that private and four-year institutions, as well as those with higher admissions rates and Pell-recipient populations, have more modern syllabi, though two-year institutions and schools serving fewer Pell recipients seem to be gaining ground.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382777528Subjects--Topical Terms:

1151737
Science education.
Subjects--Index Terms:

Data scienceIndex Terms--Genre/Form:

554714
Electronic books.

Essays on Statistics and Data Science Education.
LDR:03698ntm a22004217 4500 001 1146549
005 20240812064642.5
006 m o d
007 cr bn ---uuuuu
008 250605s2024 xx obm 000 0 eng d
020 $a 9798382777528
035 $a (MiAaPQ)AAI31293727
035 $a AAI31293727
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Klugman, Emma Mary. $3 1471953
245 1 0 $a Essays on Statistics and Data Science Education.
264 0 $c 2024
300 $a 1 online resource (146 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
500 $a Advisor: Ho, Andrew.
502 $a Thesis (Ph.D.)--Harvard University, 2024.
504 $a Includes bibliographical references
520 $a Statistics & data science are growing, rapidly evolving, and increasingly important for an informed citizenry in a data-saturated world. In this dissertation, I address two central questions: (1) who is taking statistics? and (2) what are statistics courses teaching?I estimate that 920,000 US students take statistics in high school each year, but this population has not yet been well studied. Using a rich set of survey responses describing 15,727 students' demographics, career interests and values, STEM identity, grades, and test scores, my first study compares four groups of high-school course-takers: those who take statistics, calculus, both, and neither. I then employ latent profile analysis to shed light on who these students are, showing that students with different profiles take statistics at surprisingly similar rates: statistics is as an important part of the academic pathway for a wide range of students and serves a demographically diverse population.In my second study, I build upon tools from natural language processing and psychometric measurement to develop a human-in-the-loop methodology for measuring latent constructs in large text corpora, and present a framework for doing so. I construct a lexicon-based instrument to measure the extent to which syllabi from college statistics and data science courses align with a vision for modernizing instruction set forth in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) project and across 145 journal articles spanning almost a century. In so doing, I illustrate an approach that researchers can take in bringing measurement questions to text data, a method that I believe strikes a useful balance between interpretability, communicability, validity, and scalability.My final study applies these instruments to 32,483 syllabi from US statistics and data science courses taught between 2010 and 2018. I find a modest overall increase in modern approaches over this decade. Finally, I explore differences between institution types using multilevel models, finding that private and four-year institutions, as well as those with higher admissions rates and Pell-recipient populations, have more modern syllabi, though two-year institutions and schools serving fewer Pell recipients seem to be gaining ground.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Science education. $3 1151737
650 4 $a Educational tests & measurements. $3 1180442
650 4 $a Statistics. $3 556824
650 4 $a Education. $3 555912
653 $a Data science
653 $a Data science education
653 $a Measurement
653 $a Psychometrics
653 $a Statistics education
653 $a Text analysis
655 7 $a Electronic books. $2 local $3 554714
690 $a 0515
690 $a 0463
690 $a 0288
690 $a 0714
710 2 $a Harvard University. $b Education. $3 1372568
710 2 $a ProQuest Information and Learning Co. $3 1178819
773 0 $t Dissertations Abstracts International $g 85-12B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31293727 $z click for full text (PQDT)