Pedagogical Ramifications of Fourth Industrial Revolution Technology on General English Classes from Korean Students Perspective
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The purpose of this study is to investigate Korean university students’ perceptions of how the fourth industrial revolution (4IR) technology (e.g., Artificial Intelligence, Big Data, and Augmented Reality/ Virtual Reality) will contribute to current and future general English (GE) education at Korean universities in the era of 4IR. Data were collected from 177 university students who were taking GE classes at a Korean university at the time this study was conducted, and a survey questionnaire which includes multiple choice, Likert scale, and open-ended questions, was used as the main data collection method. Data were analyzed by following descriptive statistics and the general qualitative data analysis method. The findings of this study show that students perceive that some, but not all problems that current GE classes have could be fixed by the 4IR technology. In addition, they believe that the development of 4IR technology will drive a change of the future GE education, but some aspects of current GE classes (e.g., their mandatory status at university and learning in an offline context) and the roles of human agents (e.g., students’ ownership of their English learning and human teachers’ different roles to AI teachers’) should be valued in the future GE classes. Educational Implications of the findings and limitations of the study are also discussed.
Abstract
The purpose of this study is to investigate Korean university students’ perceptions of how the fourth industrial revolution (4IR) technology (e.g., Artificial Intelligence, Big Data, and Augmented Reality/ Virtual Reality) will contribute to current and future general English (GE) education at Korean universities in the era of 4IR. Data were collected from 177 university students who were taking GE classes at a Korean university at the time this study was conducted, and a survey questionnaire which includes multiple choice, Likert scale, and open-ended questions, was used as the main data collection method. Data were analyzed by following descriptive statistics and the general qualitative data analysis method. The findings of this study show that students perceive that some, but not all problems that current GE classes have could be fixed by the 4IR technology. In addition, they believe that the development of 4IR technology will drive a change of the future GE education, but some aspects of current GE classes (e.g., their mandatory status at university and learning in an offline context) and the roles of human agents (e.g., students’ ownership of their English learning and human teachers’ different roles to AI teachers’) should be valued in the future GE classes. Educational Implications of the findings and limitations of the study are also discussed.
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