Measuring Motivational Pattern on Second Language Learning and its Relationships to Academic Performance: A Case Study of Blended Learning Course

Zahra AZIZAH; Tomoya OHYAMA; Xiumin ZHAO; Yuichi OHKAWA; Takashi MITSUISHI

doi:10.1587/transinf.2023EDP7052

Measuring Motivational Pattern on Second Language Learning and its Relationships to Academic Performance: A Case Study of Blended Learning Course

Zahra AZIZAH, Tomoya OHYAMA, Xiumin ZHAO, Yuichi OHKAWA, Takashi MITSUISHI

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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

learning analytics, data mining, blended learning, self-regulated learning, motivation

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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},}

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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 -