Digital Flow: Insights from English Teacher Educators
Year: 2025
Type: article
Abstract: Since Csikszentmihalyi's seminal work in 1975, the concept of flow has been extensively explored within the field of psychology. However, its application within foreign language teaching, particularly in the realm of digital language instruction, remains relatively under-researched. To address this gap, this study examined the flow experience of 58 teacher educators tasked with teaching English reading skills in a virtual environment (Learning Management System - LMS) during the Covid19 pandemic. This study employed a comprehensive flow model encompassing antecedents, experience, and consequences to: 1) examine the relationships between flow antecedents, flow experience, and flow consequences; and 2) investigate potential differences among teacher educators based on gender, academic degree, and teaching experience. Quantitative data analysis including correlation, One-way ANOVA, Independent-samples t-test, complemented by face-to-face interviews, uncovered noteworthy insights: Firstly, moderate to low correlations were found between the three stages of flow experienced by teacher educators in the computer-mediated environment. Secondly, male teacher educators displayed a moderately higher level of flow antecedents and flow experience compared to their female counterparts within the virtual setting. Nevertheless, the educators' academic degree and teaching experience exhibited a significant impact on the consequences of flow. These findings highlight the importance of improving teacher educators' technological proficiency within training programs by incorporating specific flow stimuli, such as clear tasks, appropriate task difficulty, relevant content, and the development of technology skills.
Authors: Mojtaba Maghsoudi, Ali Mansouri Nejad
Institution: Farhangian University
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6945976100
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