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Technology, Knowledge and Learning
Published in: Technology, Knowledge and Learning 3/2023

19-07-2021 | Original research

Female Students in Quantitative Courses: An Exploration of their Motivational Sources, Learning Strategies, Learning Behaviors, and Course Achievement

Authors: Chitra S. Dabas, Pauline S. Muljana, Tian Luo

Published in: Technology, Knowledge and Learning | Issue 3/2023

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Abstract

This study investigates factors that stimulate better academic performance for female students in learning quantitative topics, such as those involving mathematical-related tasks. We explore the differences in self-regulated learning (e.g., sources of motivation and execution of learning strategies), learning behaviors, and learning achievement of female students in quantitative courses. A combination of primary survey data and secondary data from the course-specific Learning Management System (LMS) is used in this study to identify differences between the four grade groups (e.g., students earning final grades A, B, C, and D & F). Findings reveal that the higher-grade groups have stronger metacognitive self-regulation, elaboration, time and study environment management, and effort regulation skills than the lower-grade groups. The higher-grade groups also have stronger self-efficacy, lower test anxiety, more LMS activities, and earlier assignment and quiz submissions. The lower-grade group students consistently submit assignments at the last minute and show fewer LMS activities overall. Our findings have important implications for instructors, academic administrators, and scholars in promoting female students’ self-regulated learning in quantitative courses.
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Metadata
Title
Female Students in Quantitative Courses: An Exploration of their Motivational Sources, Learning Strategies, Learning Behaviors, and Course Achievement
Authors
Chitra S. Dabas
Pauline S. Muljana
Tian Luo
Publication date
19-07-2021
Publisher
Springer Netherlands
Published in
Technology, Knowledge and Learning / Issue 3/2023
Print ISSN: 2211-1662
Electronic ISSN: 2211-1670
DOI
https://doi.org/10.1007/s10758-021-09552-z

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