As the COVID-19 pandemic struck the world in 2020, schools and institutions were forced to provide online education as an emergency measure. This study examined college students’ prediction on how the pandemic will change college education in general and their perceptions of emergency online language education in the first and second semesters of the year 2020. At the end of the first and second semesters in 2020, this study surveyed students who took emergency online college English classes at a Korean university and compared the results between the two semesters. Results showed that the majority of students predicted a major transition in college education due to COVID-19 and expected online education to continue even after the pandemic. More importantly, the students showed a positive change of attitude toward online language learning over the year. In addition, the efficiency of online language learning has improved significantly, presumably due to psychological and pedagogical factors. It is hoped that this study will offer a better understanding of the students’ perceptions of the emergency online education of 2020 and provide practical implications to improve the quality of online language education.

Since artificial neural networks were applied to machine translation (MT) programs such as Google Translate and Papago, their quality of translation has improved dramatically. It leads to the consideration of MT as a pedagogical tool for teaching and learning English. In this regard, this study observed and analyzed eight Korean EFL young adults’ English writing processes using Google Translate and Papago in real-time. To explore when and how they exploited MT in completing a narrative essay, a qualitative method using screen recordings of writing sessions and retrospective interviews was implemented. The findings revealed three most representative instances among many others that the participants utilized MT to resolve difficulties in English. Moreover, those instances are closely related to self-judgment the writers constantly made. Self-judgment is an inevitable process for the writers to incorporate MT output in their writing. In the process of self-judgment, English abilities and knowledge the writers possess might play significant roles to accept appropriate MT outputs. The results of the present study also indicate that the participants, albeit a small number, preferred Papago over Google Translate based on their assumptions in accuracy and usefulness. Finally, some implications and limitations drawn from these results were also discussed.

The present study investigated the effects of a synchronous video (Zoom) class and audio-recording practice on students' speaking performance. It also examined students' perceptions of a Zoom speaking class and voice recording practice in the synchronous online learning environment. Sixty-four Korean students first answered questionnaires to investigate their backgrounds and perspectives on online Zoom learning and then took a pre- mock TOEIC speaking test. After participating in online Zoom classes for ten weeks, they completed the same multiple questionnaires and the same mock speaking test. Additionally, they answered the open-ended questions about the advantages and disadvantages of a Zoom speaking class and voice recording practice. The data were analyzed statistically, and qualitative responses were categorized into themes based on the students' responses. The results showed that the students improved significantly in speaking performances in the post-test compared to the pre-test. In addition, the students' perceptions showed positive aspects towards synchronous English courses. The participants considered synchronous Zoom learning with self-recorded practice to be helpful and an effective way to improve their speaking skills. The technical issues, however, should be considered in any future learning environment.

With the development of Artificial Intelligence (AI) and its sharp growth in demand, AI chatbot has spread to other fields, including the field of language education on AI-based smart learning. This empirical study aims to review the learning effects of Korean education using AI chatbots in smart learning. In addition, the perceived learning effects of Korean as second language (KSL) learners were examined. Additionally, as the learning style of the learners could influence the learning effect, this study also compared the differences in perceived learning effect according to the students’ learning style (visual, auditory, and hands-on). The participants of this study used a Korean language education chatbot application and answered a survey on the learning effect, namely the earning content, learning flow, learning anxiety, learning efficacy, and learning satisfaction. The results showed that KSL learners considered Korean language education through chatbots was as effective as existing Korean language education. The chatbot also received positive evaluation in terms of decreasing learning anxiety and increasing learning efficacy. Furthermore, the study revealed that among the different learning styles, visual learners showed a significant reduction in learning anxiety.

The main goal of this study is to verify factors influencing English teachers’ switch intention to augmented reality(AR) based on Push-Pull-Mooring(PPM) theory. To this end, the study proposes three variables (content uniformity, functional simplicity, learning inefficiency) in the push effect and three variables (interactivity, learning practicality, experiential learning) in the pull effect, which have a positive impact on English teachers’ switch intention to AR. For the mooring effect, this study proposes English teachers’ innovation as a moderating factor within the relationships between variables in push-pull and switch intention. For three months, a total of 49 responses from English teachers at various organizations, including elementary schools, private English institutions, and libraries with English programs were analyzed using SmartPLS 3.0 to test the proposed hypotheses. The results provide a clear understanding of the reasons that English teachers intend to switch to AR. The contributions and implications of the study are discussed concerning the future approach to AR use in English learning and teaching.

The study aims to examine of factors affecting the relationship between Korean university students' learning flow and learning outcomes, and the correlations among these factors under the real-time online learning conditions. The participants, 49 college students from a university in Busan, were asked to complete a questionnaire regarding their perception of the given factors. The collected data was then analyzed by using correlation analysis and regression analysis. The results were as follows: first, significant correlations were discovered among learners' participation in non-face-to-face online real-time classes, self-directed learning, communication between learners, sharing of information, learning flow, and digital tool use. On the other hand, no correlation was reported between self-directed learning and communication specifically. Second, regarding factors affecting learning flow and learning performance, the relationship between digital tool use and communication was found to be statistically significant, while that between self-directed learning and sharing information was not. The results of this study cannot be definitive due to its limitations, but it might still show the relationships among factors involved in online real-time classes. A further look at the design and operation of online classes conducted by different instructors might reveal a truer picture of what is going on under these conditions.