IEICE TRANSACTIONS on Information
Measuring Motivational Pattern on Second Language Learning and its Relationships to Academic Performance: A Case Study of Blended Learning Course
Summary :
Learning analytics (LA) has emerged as a technique for educational quality improvement in many learning contexts, including blended learning (BL) courses. Numerous studies show that students' academic performance is significantly impacted by their ability to engage in self-regulated learning (SRL). In this study, learning behaviors indicating SRL and motivation are elucidated during a BL course on second language learning. Online trace data of a mobile language learning application (m-learning app) is used as a part of BL implementation. The observed motivation were of two categories: high-level motivation (study in time, study again, and early learning) and low-level motivation (cramming and catch up). As a result, students who perform well tend to engage in high-level motivation. While low performance students tend to engage in clow-level motivation. Those findings are supported by regression models showing that study in time followed by early learning significantly influences the academic performance of BL courses, both in the spring and fall semesters. Using limited resource of m-learning app log data, this BL study could explain the overall BL performance.
- Publication
- IEICE TRANSACTIONS on Information Vol.E106-D No.11 pp.1842-1853
- Publication Date
- 2023/11/01
- Publicized
- 2023/08/01
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2023EDP7052
- Type of Manuscript
- PAPER
- Category
- Educational Technology
Authors
Zahra AZIZAH
Tohoku University
Tomoya OHYAMA
Tohoku University
Xiumin ZHAO
Tohoku University
Yuichi OHKAWA
Tohoku University
Takashi MITSUISHI
Tohoku University
Keyword
Latest Issue
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Zahra AZIZAH, Tomoya OHYAMA, Xiumin ZHAO, Yuichi OHKAWA, Takashi MITSUISHI, "Measuring Motivational Pattern on Second Language Learning and its Relationships to Academic Performance: A Case Study of Blended Learning Course" in IEICE TRANSACTIONS on Information,
vol. E106-D, no. 11, pp. 1842-1853, November 2023, doi: 10.1587/transinf.2023EDP7052.
Abstract: Learning analytics (LA) has emerged as a technique for educational quality improvement in many learning contexts, including blended learning (BL) courses. Numerous studies show that students' academic performance is significantly impacted by their ability to engage in self-regulated learning (SRL). In this study, learning behaviors indicating SRL and motivation are elucidated during a BL course on second language learning. Online trace data of a mobile language learning application (m-learning app) is used as a part of BL implementation. The observed motivation were of two categories: high-level motivation (study in time, study again, and early learning) and low-level motivation (cramming and catch up). As a result, students who perform well tend to engage in high-level motivation. While low performance students tend to engage in clow-level motivation. Those findings are supported by regression models showing that study in time followed by early learning significantly influences the academic performance of BL courses, both in the spring and fall semesters. Using limited resource of m-learning app log data, this BL study could explain the overall BL performance.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2023EDP7052/_p
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@ARTICLE{e106-d_11_1842,
author={Zahra AZIZAH, Tomoya OHYAMA, Xiumin ZHAO, Yuichi OHKAWA, Takashi MITSUISHI, },
journal={IEICE TRANSACTIONS on Information},
title={Measuring Motivational Pattern on Second Language Learning and its Relationships to Academic Performance: A Case Study of Blended Learning Course},
year={2023},
volume={E106-D},
number={11},
pages={1842-1853},
abstract={Learning analytics (LA) has emerged as a technique for educational quality improvement in many learning contexts, including blended learning (BL) courses. Numerous studies show that students' academic performance is significantly impacted by their ability to engage in self-regulated learning (SRL). In this study, learning behaviors indicating SRL and motivation are elucidated during a BL course on second language learning. Online trace data of a mobile language learning application (m-learning app) is used as a part of BL implementation. The observed motivation were of two categories: high-level motivation (study in time, study again, and early learning) and low-level motivation (cramming and catch up). As a result, students who perform well tend to engage in high-level motivation. While low performance students tend to engage in clow-level motivation. Those findings are supported by regression models showing that study in time followed by early learning significantly influences the academic performance of BL courses, both in the spring and fall semesters. Using limited resource of m-learning app log data, this BL study could explain the overall BL performance.},
keywords={},
doi={10.1587/transinf.2023EDP7052},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - Measuring Motivational Pattern on Second Language Learning and its Relationships to Academic Performance: A Case Study of Blended Learning Course
T2 - IEICE TRANSACTIONS on Information
SP - 1842
EP - 1853
AU - Zahra AZIZAH
AU - Tomoya OHYAMA
AU - Xiumin ZHAO
AU - Yuichi OHKAWA
AU - Takashi MITSUISHI
PY - 2023
DO - 10.1587/transinf.2023EDP7052
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E106-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2023
AB - Learning analytics (LA) has emerged as a technique for educational quality improvement in many learning contexts, including blended learning (BL) courses. Numerous studies show that students' academic performance is significantly impacted by their ability to engage in self-regulated learning (SRL). In this study, learning behaviors indicating SRL and motivation are elucidated during a BL course on second language learning. Online trace data of a mobile language learning application (m-learning app) is used as a part of BL implementation. The observed motivation were of two categories: high-level motivation (study in time, study again, and early learning) and low-level motivation (cramming and catch up). As a result, students who perform well tend to engage in high-level motivation. While low performance students tend to engage in clow-level motivation. Those findings are supported by regression models showing that study in time followed by early learning significantly influences the academic performance of BL courses, both in the spring and fall semesters. Using limited resource of m-learning app log data, this BL study could explain the overall BL performance.
ER -
English
