A multilevel regression analysis of computer-mediated communication in synchronous and asynchronous contexts and digital reading achievement in Japanese students

ABSTRACT

In the digital era, traditional communication has undergone a drastic transformation into computer-mediated communication (CMC), which can be classified into synchronous CMC (SCMC) and asynchronous CMC (ASCMC). This study compared the effects of extracurricular CMC among students about schoolwork on students' digital reading achievement between SCMC and ASCMC, with the categorization of students into three levels, i.e., top, medium, and low achievers. Data from 6,109 samples representing 183 schools in Japan were retrieved from the dataset of Programme for International Student Assessment (PISA) 2018. Due to the hierarchical nature of the data, multilevel regression analysis was adopted to identify the variance of studentand school-level. The results revealed a significant positive effect of SCMC on the digital reading performance of students, while ASCMC had a negative impact. Furthermore, among the three categories of achievers, medium achievers were the group most sensitive to both SCMC and ASCMC at any frequency, while top achievers were not significantly influenced by SCMC and ASCMC at any frequency, and low achievers were influenced by SCMC and ASCMC only at several frequencies. These findings indicate that it is more advisable for students to use SCMC, and treatment should be customized to students of different levels.

KEYWORDS:

• Computer-meditated communication
• digital reading
• educational policy
• online interactive learning
• PISA reading

Disclosure statement

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

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by The National Social Science Fund of China, China [Grant number 21BYY024].

Notes on contributors

Hangyan Yu

Hangyan Yu is a Master’s level student at the Department of Linguistics, School of International Studies, Zhejiang University, Hangzhou 310058, China. Her research interests lie in second language acquisition, computer-assisted English language learning, and educational data mining. E-mail: [email protected].

Jie Hu

Jie Hu, Ph.D., is a professor and the Deputy Dean at the Department of Linguistics, School of International Studies, Zhejiang University, Hangzhou 310058, China. She has been focusing on English language education for more than 10 years after her Ph.D. graduation from the University of Warwick, U.K. Her research interests include ICT-based English language education, second language acquisition, educational data mining and learning analysis. E-mail: [email protected].