Efl Instructors’ Digital Technology Perceptions, Motivation, and Job Satisfaction Levels in Emergency Remote Education
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Date
2023-07-25Author
Demirkol Orak, Suheyla
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The present study investigated EFL instructors’ digital technology integration, motivation,
perception and job satisfaction levels regarding SAMR Model in the Emergency Remote
Education (ERE) process caused from Covid-19 pandemic. The study was employed at
20 universities in Türkiye, and 162 female and 81 male EFL instructors participated in the
quantitative study, and 14 of them participated in the qualitative part via convenience
sampling method. A mixed-method explanatory research design was employed.
Quantitative data was collected via online questionnaires, and qualitative data was
collected via semi-structured interviews, reflection journals, and open-ended resposes.
Descriptive Statistics, Pearson Correlation Analysis, Hierarchical Multiple Regression,
Anova, and Content analysis methods were utilised. The results discovered that EFL
instructors’ digital technology integration levels circulated around the Substitution and
Modification levels, and instructors were neither motivated nor satisfied with teaching
online during the ERE. It was revealed that there was not a significant relationship
between instructors’ digital technology integration levels and their motivation and job
satisfaction levels. Multiple Hierarchical Regression results showed that instructors’
gender, background education, and online teaching experiences have a siginificant
relationship with their digital technology integration levels, age and seniority do not have.
The findings pointed that instructors’ digital technology integration practices were
rendered mainly because of passive students and insufficient infrastructure. To ensure a
sustainable education, educational bodies are recommended to strengthen infrastructure,
and develop regular Professional Development Units to meet the addressed gap of the
instructors’ insufficient background education and online teaching experiences with the
upgraded methods.