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Undergraduate Student Motivation in ...
~
Pachlhofer, Keith A.
Undergraduate Student Motivation in Modularized Developmental Mathematics Courses.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Undergraduate Student Motivation in Modularized Developmental Mathematics Courses./
作者:
Pachlhofer, Keith A.
面頁冊數:
1 online resource (154 pages)
附註:
Source: Dissertation Abstracts International, Volume: 78-12(E), Section: A.
Contained By:
Dissertation Abstracts International78-12A(E).
標題:
Education. -
電子資源:
click for full text (PQDT)
ISBN:
9780355078558
Undergraduate Student Motivation in Modularized Developmental Mathematics Courses.
Pachlhofer, Keith A.
Undergraduate Student Motivation in Modularized Developmental Mathematics Courses.
- 1 online resource (154 pages)
Source: Dissertation Abstracts International, Volume: 78-12(E), Section: A.
Thesis (Ed.D.)
Includes bibliographical references
This study used the Motivated Strategies for Learning Questionnaire in modularized courses at three institutions across the nation (N = 189), and multiple regression was completed to investigate five categories of student motivation that predicted academic success and course completion. The overall multiple regression analysis was significant and two variables, Task Value and Self-Efficacy, were significant in predicting student progress in the course. Also, open-ended items were collected to help determine the students' evaluation of what helps them to succeed and this was then compared to the findings from the multiple regression analysis.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355078558Subjects--Topical Terms:
555912
Education.
Index Terms--Genre/Form:
554714
Electronic books.
Undergraduate Student Motivation in Modularized Developmental Mathematics Courses.
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This study used the Motivated Strategies for Learning Questionnaire in modularized courses at three institutions across the nation (N = 189), and multiple regression was completed to investigate five categories of student motivation that predicted academic success and course completion. The overall multiple regression analysis was significant and two variables, Task Value and Self-Efficacy, were significant in predicting student progress in the course. Also, open-ended items were collected to help determine the students' evaluation of what helps them to succeed and this was then compared to the findings from the multiple regression analysis.
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click for full text (PQDT)
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