Metacognition, motivation, self-efficacy belief, and English learning achievement in online learning: Longitudinal mediation modeling approach

ABSTRACT

The Purpose

Despite a large number of studies in online learning, limited studies have focused on language learners’ metacognition, motivation, and self-efficacy beliefs in the online learning setting. This study attempts to fill this gap by evaluating how the three factors impact learners’ English learning achievement in online learning environments.

Design

Surveys were administered two times. Data analyses were based on longitudinal mediation analysis. The participants were 590 undergraduate students in China.

Findings

The results showed a positive and significant correlation among the four variables. Overall, self-efficacy beliefs predicted English learning achievement. The findings support the joint mediating role of metacognition and motivation on the effects of self-efficacy beliefs on English learning achievement.

Value

The findings support the need to strengthen learners’ metacognition, motivation, and self-efficacy beliefs for online English learning.

KEYWORDS:

• Metacognition
• motivation
• self-efficacy belief
• English learning achievement
• longitudinal mediation

Acknowledgement

Thanks for the participants’ efforts in taking part in this study during the COVID-19 period. Special thanks go to Professor Chuang Wang, who provided comments for this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Statements on open data, ethics

The current research data are available from the authors upon request.

The participants in this study gave their informed consent prior to its initiation. The research received approval from the institutional ethics committee approval.

Additional information

Notes on contributors

Mark Feng Teng

Mark Feng Teng is Associate Professor of Applied Linguistics at Beijing Normal University. His research interests mainly focus on L2 vocabulary acquisition, and metacognition in L2 writing. He has published extensively in these areas, including monographs and edited books, numerous international journal papers, and book chapters. He received the 2017 Hong Kong Association for Applied Linguistics (HAAL) Best Paper Award. He was named in the recent edition of the Stanford University list of World Top 2% scientists in applied linguistic research. He serves as co-editor for OTI section, TESL-EJ. His email address is [email protected]

Zi Yang

Zi Yang is an Assistant Professor at the Institute of Education, Xiamen University. Her email address is [email protected]