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Friend or Foe? The Role of Machine Learning in Education Policy Research.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Friend or Foe? The Role of Machine Learning in Education Policy Research./
Author:	Weissman, Amanda.
Description:	1 online resource (248 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-04, Section: B.
Contained By:	Dissertations Abstracts International84-04B.
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29730363click for full text (PQDT)
ISBN:	9798845460394

Friend or Foe? The Role of Machine Learning in Education Policy Research.
Weissman, Amanda.

Friend or Foe? The Role of Machine Learning in Education Policy Research. - 1 online resource (248 pages)

Source: Dissertations Abstracts International, Volume: 84-04, Section: B.

Thesis (Ph.D.)--University of Michigan, 2022.

Includes bibliographical references

Machine learning, while common in other disciplines, has slowly started to become used more education research. My project seeks to answer the call from researchers for guidance about the nature of machine learning and illustration in how to use machine learning. First, I address the nature of machine learning and provide examples of its capabilities in education policy research. Second, I examine what value machine learning adds over traditional regression in predicting vulnerable student populations for early intervention. Third, I probe how machine learning can aid in identifying students at risk for dropping out of high school. My project will be one of the few projects in the field of education to espouse the potential benefits of machine learning and interrogate its value added to traditional quantitative research methods.

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

Mode of access: World Wide Web

ISBN: 9798845460394Subjects--Topical Terms:

517247
Statistics.
Subjects--Index Terms:

Machine learningIndex Terms--Genre/Form:

542853
Electronic books.

Friend or Foe? The Role of Machine Learning in Education Policy Research.
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502 $a Thesis (Ph.D.)--University of Michigan, 2022.
504 $a Includes bibliographical references
520 $a Machine learning, while common in other disciplines, has slowly started to become used more education research. My project seeks to answer the call from researchers for guidance about the nature of machine learning and illustration in how to use machine learning. First, I address the nature of machine learning and provide examples of its capabilities in education policy research. Second, I examine what value machine learning adds over traditional regression in predicting vulnerable student populations for early intervention. Third, I probe how machine learning can aid in identifying students at risk for dropping out of high school. My project will be one of the few projects in the field of education to espouse the potential benefits of machine learning and interrogate its value added to traditional quantitative research methods.
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538 $a Mode of access: World Wide Web
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650 4 $a Education policy. $3 2191387
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650 4 $a Secondary education. $3 2122779
650 4 $a Education. $3 516579
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653 $a Education policy research
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