Earticle

본 연구는 챗봇의 활용이 한국 대학생의 영어 어휘 학습에 미치는 영향을 조사한 것으로, 챗봇과의 채팅을 통해 실험 참가자의 영어 어휘 능력이 실제 상승하는지 여부와 영어 어휘 학습에 대한 인식이 어떻게 변하는지 알아보는 데 그 목적이 있다. 47명의 국내 대학생을 실험그룹과 통제그룹으로 나누어 총 8주 동안 실험을 진행하였고, 챗봇 활용의 효과 를 파악하기 위해 실험 시작 전과 종료 후 사전 사후 어휘 평가를 실시하였으며, 사전 사후 설문조사를 통해 챗봇을 활용한 어휘 학습에 대한 참가자의 인식 변화를 조사하였다. 본 연구의 주요 결과 및 시사점은 다음과 같다. 사전 사후 어휘 평가 결과, 참가자의 어휘 능력은 실험 전에 비해 실험 종료 후 상승한 것으로 나타났고, 사전 사후 설문 결과, 챗봇의 활용은 참가자의 영어 어휘 학습에 대한 태도를 긍정적으로 변화시키는 데 중요한 역할을 하는 것으로 파악되었다. 테크놀로지의 발달과 함께 최근 영어 교육에 있어 챗봇의 활용이 증가하는데 비해 그에 대한 실증적 연구가 부족하다는 점을 고려해 볼 때, 본 연구가 갖는 시사점이 크다고 할 수 있다.

The current study investigates whether artificially intelligent chatbots influence Korean EFL students' vocabulary learning. For eight weeks, 47 college students in Korea participated in this study. They were divided into two groups: one experimental group and one control group. Participants in the experimental group engaged in chat with a chatbot during the eight-week experimental period. Before and after the experiment, pre- and post-tests were administered to see if their English vocabulary improved. Pre- and post- surveys were also performed to understand how the participants perceived chatbot-assisted vocabulary learning. Results show that the experimental group improved their vocabulary skills as a result of engaging in chat with the chatbot. Also, their perceptions of vocabulary learning positively changed, increasing their motivation, interest, and confidence in English. Given that there have been few empirical studies to investigate the effects of chatbots on vocabulary development, the present study can provide insights on the effectiveness of chatbots.

본 연구는 챗봇의 활용이 국내 대학생의 영어 듣기 및 읽기 학습에 미치는 영향을 조사한 것으로, 실험 참가자의 영어 듣기 및 읽기 능력이 챗봇과의 채팅을 통해 실제로 상승하는지에 대한 여부를 알아보는 데 그 목적이 있다. 본 연구를 위해 총 46명의 참가자를 실험그룹과 통제그룹으로 나누어 16주 동안 실험을 진행하였으며, 실험 시작 전과 실험 종료 후 사전 사후 평가를 실시하여 챗봇 활용의 효과를 파악하였다. 본 연구의 주요 결과 및 시사점은 다음과 같다. 사전 사후 평가 결과 실험그룹과 통제그룹 모두에서 영어 듣기 및 읽기 능력이 유의미하게 상승한 것으로 나타났다. 특히 영어 듣기 능력과 관련하여 실험그룹이 통제그룹보다 사후 평가에서 더 많은 상승폭을 보임으로써 듣기 능력 향상에 대한 챗봇 활용의 효과를 증명하였다. 본 연구는 4차 산업혁명 시대에 따라 영어 학습을 위한 챗봇 활용에 대한 시사점을 제시하는데 그 의의를 갖는다고 볼 수 있다.

In an effort to investigate the effects of chatbots on English listening and reading skills, 46 college students participated in the current study. Participants consisted of first-year students who enrolled in an English class at a university in South Korea. They were randomly divided into two groups: one experimental group (n=24) and one control group (n=22). During 16 weeks, the experimental group engaged in chats with a chatbot, named Elbot, while the control group did not. There were pre- and post-tests to confirm the effects of the chatbot usage. Major findings are as follows: First, participants in both groups significantly improved listening and reading skills. On the post-listening test, however, the experimental group showed more improvements. Their listening proficiency level improved from intermediate to advanced level after engaging in chat with the chatbot. Limitations and implications for theory and practice are discussed at the end.

2023년 챗GPT가 소개되면서, 교육현장에 많은 관심이 쏠리고 있다. 현재 자연어 처리 챗봇을 활용한 다양한 교육프로그램이 연구되고 있다. 본 연구는 수도권 초등학생 6학년 110명을 대상으로 약 3개월간 자연어 처리 챗봇 을 교과 수업에 적용하였다. 이를 통해 사전, 사후 분석으로 자연어 처리 챗봇을 활용한 교육프로그램이 학생들의 AI 기술에 대한 긍정적인 수용성을 높일 수 있는지 검증하고자 하였다. 통계적 검증방법으로는 대응표본 t 검정, 독립표본 t 검정 및 선형회귀 분석을 각각 실시하였다. 그 결과, 자연어 처리 챗봇을 활용한 교육프로그램이 학생 들의 AI 기술에 대한 긍정적 수용성을 높이고, 부정적인 인식은 감소시키는 데 효과적임을 밝혀낼 수 있었다. 다 가오는 2022 개정 교육과정 도입시기를 대비하여, 전 교과 학습에서 AI 기술을 적용하는 방안을 적극적으로 연구 할 필요성이 제기된다.

Recently, ChatGPT is receiving a lot of attention in the education industry. Many educational programs are being researched and developed that utilize natural language processing chatbots. This study was conducted with 110 sixth-grade elementary school students as participants. The purpose of this study was to verify whether an educational program utilizing a natural language processing chatbot could increase students' positive perception of AI technology. Statistical validation was conducted by paired-sample t-test, independent-sample t-test, and linear regression analysis. As a result, it was found that the educational program utilizing a natural language processing chatbot increased students' positive perception of AI technology and had a positive effect in reducing negative perceptions. There is a need to research various teaching methods that utilize AI technology.

As Artificial Intelligence (AI) becomes increasingly prevalent in everyday life, concerns about AI ethics and privacy are growing. One such concern is the unauthorized use of AI chatbots through a practice known as "jailbreaking." Jailbreaking refers to the act of bypassing software restrictions on chatbots, enabling users to use them in unauthorized ways. Our study aims to explore the motivations behind jailbreaking and its implications for ethical governance in the context of AI. We will employ a mixed-method approach, combining topic modeling and regression analysis to extract and analyze data from online forums related to jailbreaking. Our study has both academic and practical implications. The academic implications of this study include enhancing our understanding of the ethical and privacy implications of jailbreaking. The practical implications include informing organizations and policymakers of potential vulnerabilities in their AI chatbot systems and proactively preventing possible jailbreaking to protect user privacy and maintain ethical standards.

The rapid advancement of artificial intelligence (AI) is driving innovation across the field of information services, and academic libraries are increasingly adopting AI chatbots. The Web Services Team at the University of Oklahoma Libraries initially developed an in-house chatbot leveraging natural language processing based on question and answer data collected from interactions between librarians and users. They later transitioned the system to Ivy.ai. Through a semi-structured interview, this study presents an analysis of the development and implementation of the libraries' AI chatbot focusing on the adoption process, challenges, and internal organizational dynamics. The findings indicate that successful chatbot implementation requires not only technological development but also efforts to alleviate organizational concerns about change and to cultivate a collaborative culture. These results offer practical implications for libraries and institutions considering the adoption of AI chatbots and contribute to the theoretical foundation for understanding organizational acceptance of evolving AI technologies.

Purpose: Artificial intelligence (AI) has had a profound impact on humanity; in particular, chatbots have been designed for interactivity and applied to many aspects of daily life. Chatbots are also regarded as an innovative modality in nursing education. This study aimed to identify nursing students' awareness of using chatbots and factors influencing their usage intention. Methods: This study, which employed a descriptive design using a self-reported questionnaire, was conducted at three university nursing schools located in Seoul, South Korea. The participants were 289 junior and senior nursing students. Data were collected using self-reported questionnaires, both online via a Naver Form and offline. Results: The total mean score of awareness of using chatbots was 3.49±0.61 points out of 5. The mean scores of the four dimensions of awareness of using chatbots were 3.37±0.60 for perceived value, 3.66±0.73 for perceived usefulness, 3.83±0.73 for perceived ease of use, and 3.36±0.87 for intention to use. Significant differences were observed in awareness of using chatbots according to satisfaction with nursing (p<.001), effectiveness of using various methods for nursing education (p<.001), and interest in chatbots (p<.001). The correlations among the four dimensions ranged from .52 to .80. In a hierarchical regression analysis, perceived value (β=.45) accounted for 60.2% of variance in intention to use. Conclusion: The results suggest that chatbots have the potential to be used in nursing education. Further research is needed to clarify the effectiveness of using chatbots in nursing education.

The purpose of this study is to investigate the possibility of using chatbots as a school library educational tool. In order to achieve the purpose of the study, 116 librarian teachers first investigated the types and contents of education conducted in the school library setting and the perception of chatbots there. In addition, 15 librarians (five elementary, five middle, and five high school) were asked to complete a structured questionnaire after using Google's Bard, Microsoft's Bing, and OpenAI's Nova to find out if it is possible to use chatbots in school library education. As a result, user and reading education chatbots were found to be common in school libraries, and 99% of librarians knew about them in some detail. However, the average chatbot performance by area was 2.9 out of 5 (2.6 points being the lowest). Nevertheless, chatbots are being developed utilizing deep learning methodologies and have excellent performance, and are very effective for content-based library education through problem-solving activities.

Artificial intelligence (AI)-powered chatbots are rapidly supplanting human-derived scholarly work in the fast-paced digital age. This necessitates a re-evaluation of our traditional research and publication ethics, which is the focus of this article. We explore the ethical issues that arise when AI chatbots are employed in research and publication. We critically examine the attribution of academic work, strategies for preventing plagiarism, the trustworthiness of AI-generated content, and the integration of empathy into these systems. Current approaches to ethical education, in our opinion, fall short of appropriately addressing these problems. We propose comprehensive initiatives to tackle these emerging ethical concerns. This review also examines the limitations of current chatbot detectors, underscoring the necessity for more sophisticated technology to safeguard academic integrity. The incorporation of AI and chatbots into the research environment is set to transform the way we approach scholarly inquiries. However, our study emphasizes the importance of employing these tools ethically within research and academia. As we move forward, it is of the utmost importance to concentrate on creating robust, flexible strategies and establishing comprehensive regulations that effectively align these potential technological developments with stringent ethical standards. We believe that this is an essential measure to ensure that the advancement of AI chatbots significantly augments the value of scholarly research activities, including publications, rather than introducing potential ethical quandaries.

Purpose: This study aimed to identify students' awareness of the use of a chatbot (A-uC), a type of artificial intelligence technology, for violence prevention among elementary school students. Methods: The participants comprised 215 students in the fourth to sixth grades in Chuncheon, South Korea, and data were collected via a self-reported questionnaire. Results: The mean A-uC score was 3.43±0.83 out of 5 points. The mean scores for the 4 sub-dimensions of the A-uC tool were 3.48±0.80 for perceived value, 3.44±0.98 for perceived usefulness, 3.63±0.92 for perceived ease of use, and 3.15±1.07 for intention to use. Significant differences were observed in A-uC scores (F=59.26, p<.001) according to the need for the use of chatbots in violence prevention education. The relationships between intention to use and the other A-uC sub-dimensions showed significant correlations with perceived value (r=.85, p<.001), perceived usefulness (r=.76, p<.001), and perceived ease of use (r=.64, p<.001). Conclusion: The results of this study suggest that chatbots can be used in violence prevention education for elementary school students.

This study examines how information presentation strategies―specifically online review provision and price framing―affect user experience and reuse intention in an LLM-based hotel recommender chatbot. To investigate this, we developed a hybrid chatbot integrating a large language model (LLM), Text-to-SQL, and Retrieval-Augmented Generation (RAG), and conducted a 2 × 2 between-subjects experiment based on real user interactions. Data were collected from 160 participants who interacted with the chatbot and subsequently completed a survey. The results indicate that both online review provision and downward price framing significantly enhance perceived recommender chatbot quality, which subsequently increases user satisfaction and reuse intention, whereas their interaction effect is not significant. In addition, exploratory factor analysis revealed that the multidimensional structure of chatbot quality converged into a single higher-order factor. Mediation analysis further showed that the effects of information presentation strategies on behavioral outcomes were mediated by perceived chatbot quality and satisfaction. These findings suggest that, in conversational recommender environments, information presentation strategies influence user behavior primarily through holistic quality evaluations rather than through direct effects on satisfaction.

This study focused on analyzing how different interactions (face-to-face chatting and chatting with AI chatbots) may affect speaking skills. In order to examine whether using AI chatbots can be beneficial for improving speaking task performances, 110 participants were divided into three groups: a face-toface chatting, AI text-chatting, and AI voice-chatting group. They were assigned three speaking tasks that involved describing a picture, responding to questions, and expressing an opinion, which they did both before and after the experiments. Based on the analysis of quantitative data, the findings of the study indicated that both AI groups improved their speaking performance after the experiment while there were mixed results from the face-to-face interactions. It was found that the participants in the face-to-face group improved significantly better in responding to questions and expressing an opinion while no significant differences were revealed in the describing a picture task. With respect to the effects of using AI chatbots, there were no significant differences in the two speaking tasks (describe a picture and respond to questions) between the three groups. However, the comparative analysis of the three different interaction modes suggested that the AI voice-chatting pairs outperformed in terms of their speaking performance task (expressing an opinion) compared with the face-to-face and AI textchatting groups. Regarding students’ perspectives, descriptive statistics and selected student interviews were reported. Based on the findings of the current study, pedagogical implications and directions for future research are also suggested.

The objective of this study is to provide a deeper understanding of the factors that lead to the development and adoption of AI-based chatbots. We analyze the structural relationship between the organizational (externalities), systematic (fit), and the consumer-related (psychological) factors and their role in the adoption of AI-based chatbots. Founded on the theories of task-technology fit and network externalities, we present a conceptual model overlooking common perception-based theories (e.g., Technology Acceptance Model). We collected 380 responses from Indian banking consumers to test the model using the PLS-SEM method. Interestingly, the findings present a positive impact of all factors on consumers’ intention to adopt AI-based chatbots. However, the interplays between these factors provide a mixed perspective for literature. Apart from employing a combination of factors that have been used to study technology adoption, our study explores the importance of externalities and their relationship with fit factors, a unique outlook often overlooked by prior research. Moreover, we offer a clear understanding of latent variables such as trust, and the intricacies of their interplays in a novel context. Thereby, the study offers implications for literature and practice, followed by future research directions.

본 연구는 인공지능 챗봇을 활용한 채팅 활동이 국내 대학생의 영어 문법 능력 향상에 미치는 영향을 조사한 것으로, 챗봇과의 채팅을 통해 실험 참가자의 영어 문법 능력이 실제로 상승하는지에 대한 여부를 알아보는 데 그 목적 이 있다. 총 16주 동안 70명의 참가자가 챗봇 그룹과 인간 그룹으로 나뉘어 본 연구에 참여하였고, 참여인원은 각각 36명, 34명이었다. 챗봇 그룹은 수업시간에 배운 내용을 주제로 챗봇과의 채팅에 참여하였고, 인간 그룹은 같은 반 학생들끼리 짝지어 채팅을 진행하였다. 채팅 활동의 효과를 파악하기 위하여 본 연구 시작 전과 종료 후, 사전 사후 영어 문법 시험을 실시하였고, 그룹 간 비교를 위하여 독립표본 t검증을 실시하였다. 주요 결과 및 시사점은 다음과 같다. 사전 사후 평가 분석 결과, 두 그룹 모두에서 영어 문법 능력이 유의미하게 상승한 것으로 나타나 채팅 활동의 효과를 증명하였다. 문법 능력 상승에 대한 그룹 간 차이 역시 통계적으로 유의미한 것으로 밝혀져 국내 영어 교육에 있어서 챗봇의 긍정적인 역할을 확인하였다. 본 연구는 영어 문법 능력 향상을 위한 인공지능 챗봇 활용에 대한 시사점 을 제시하는데 그 의의를 갖는다.

The purpose of this study is to explore the effects of the use of artificial intelligence chatbots on improving Korean college students' English grammar skills. 70 undergraduate students participated in the present study. They were taking a General English class offered by a university in Korea. There were two groups in this study. Participants in the chatbot group consisted of 36 students while those in the human group were 34. Over 16 weeks, the chatbot group engaged in ten chat sessions with a chatbot while the human group had a chat with a human chat partner. Both pre- and post-tests were performed to examine changes in the participants' grammar skills over time. To compare the improvement between the two groups, an independent t-test was then run. Main findings are as follows: First, participants in both groups significantly improved their English grammar skills, indicating the beneficial effects of engaging in chat. Also, there was a statistically significant difference in the improvement between the chatbot and human groups, indicating the superior effects of the chatbot use. This study confirmed the improved grammar skills by the participants in the chatbot group, comparison with those in the human group. Based on these findings, suggestions for the future chatbot study are discussed.

Service organizations increasingly adopt data-based intelligent engines called chatbots in support of the interaction between customers and the companies. Two different types of chatbots have been suggested and introduced by companies leading the adoption of this emerging technology: rule-based chatbots and natural language processing-based chatbots. While the differences between these two types of technologies look relatively clear, the organizational and practical impacts of the differences have not been systematically explored. This study performed an experiment to compare the use of the two different types of chatbots used in practice by two comparable organizations. These two types of actual chatbots were used by Korean on-line shopping malls with similar business models (mobile shopping), length of history, size and reputation. The comparison was made based on such dimensions as usability, searchability, reliability and attractiveness. Contraty to conventional expectation that the superiority in technology will produce superior usability, the results show mixed superiority. The discussion on the reasons is presented.

The purpose of this study is to explore the current state of interactive AI chatbot development, focusing on ICT based new technology trends, and suggest ways of applying this chatbot technology to develop English education chatbots. First, this study explains the major principles of AI-based interactive chatbot development in recent years. Second, it also presents the basic structure of the AI-based chatbot system and its application of intelligent learning processes in English language education. In addition, with the development of future technologies, interactive AI chatbots can be expected to be used in many fields such as personal assistant service, interactive commerce, and the entertainment industry. Especially, the chatbot system is expected to enhance learners’ foreign language competence and motivation in language education settings.

GPT-3.5를 대표로 하여 초거대 언어모델이 개발되고 있으며, 이는 다양한 분야에서 인공지능 활용 기술의 빠른 발전을 촉진하고 있다. 교육 분야에서도 인공지능을 활용하거나, 인공지능과 교육을 융합하여 적용하려는 노력이 지속되고 있다. 초등학교 교실에서는 기초심리 상담에 대한 요구가 증가하고 있지만, 담임교사가 상담에만 전념할 수 없다는 문제가 있다. 본 연구는 이러한 문제를 해결하기 위해 교사를 도와 기초상담을 할 수 있는 챗봇을 개발 하였다. LLM의 학습모델인 RLHF를 적용하여, '학급질문사전 만들기'를 통해 학생들이 생각하는 인공지능 챗봇에 게 하고 싶은 질문을 수집하고, 프롬프트에 적용하여 제로샷으로 1차 챗봇앱을 개발하고, 학생들이 직접 사용하게 하여, 학생의 질문과 인공지능의 답변을 기록하여 담임교사의 심층상담을 위한 기초자료로 제공하였다. 챗봇을 사용한 학생들에게 설문조사를 실시하여, 그 결과를 프롬프트에 적용하고, 기초 상담자료를 퓨샷으로 2차 챗봇앱을 고도화하였다.

Large language models like GPT-3.5 are being developed, accelerating rapid advancements in various fields of artificial intelligence applications. Efforts to integrate AI into education are also ongoing. Elementary school classrooms are experiencing an increasing demand for basic psychological counseling, but it is challenging for teachers to fully focus on counseling. To address this issue, this study developed a chatbot to assist teachers in basic counseling. Utilizing RLHF, a learning model of LLM, we created a 'Classroom Question Dictionary' by collecting questions that students would like to ask the AI chatbot. We then applied these questions to the prompt to develop a zero-shot first-phase chatbot application. Students used the chatbot, and their questions and the AI's responses were recorded to serve as foundational data for teachers' in-depth counseling. A survey was conducted among the students who used the chatbot, and the results were applied to the prompt to further refine the basic counseling data for the second-phase chatbot application

최근 발생한 COVID-19의 확산은 언택트 또는 디지택트라는 새로운 생활양식을 초래하고 있으며 이로 인해 교육과 관련된 분야에서는 에듀테크와 관련된 다양한 논의가 진행되고 있는데 그 키워드 중 하나가 챗봇이다. 현재 한국의 다문화 정책은 다문화 학생을 지원하는 측면에서는 좋은 점수를 받고 있으나 모든 학생을 위한 다문화 교육 지원은 다소 미미하다는 지적을 받고 있는데 이에 이 연구에서는 다문화 교육에서의 챗봇 활용 가능성을 탐색하였다. 연구를 위해 단비.ai 챗봇 플랫폼을 활용해 챗봇용 다문화 교육 프로그램을 개발하였다. 이때 학생의 참여도와 연구 확장성을 높이기 위해 API key값을 활용하여 카카오톡 메신저와 연동하였으며 총 4차시로 이루어진 다문화 교육용 챗봇 프로그램을 개발하였다. 통제집단 26명과 실험 집단 28명으로 이루어진 연구 대상에게 챗봇 프로그램을 적용하였으며 그 결과, 다문화 인식과 수업 만족도 모두 통제 집단보다 실험 집단에서 유의한 상승이 나타났다. 익숙하지 않은 온라인 환경에서의 수업이 자칫 학생의 수업 만족도를 낮추는 요인이 될 수 있다는 점을 고려할 때 이러한 결과는 챗봇이 새로운 에듀테크의 대안이 될 수 있을 뿐만 아니라 학생들의 다문화 역량 함양을 위한 수업 콘텐츠로서의 가능성을 확인한 결과라 할 수 있다.

Technologies such as artificial intelligence and big data are causing a paradigm shift in the industrial field, and the recent spread of COVID-19 has brought about a new lifestyle called untouch or digital. For this reason, various discussions related to edutech are in progress in the field related to education, and one of the keywords is chatbot. Currently, Korea's multicultural policy is receiving good marks in terms of supporting multicultural students, but it is being criticized for the lack of support for multicultural education for all students. Based on the above discussion, this study explored the possibility of using chatbots in multicultural education. For research, we developed a multicultural education program for chatbots using the Danbi.ai chatbot platform. At this time, in order to increase student participation and research scalability, the API key value was used to link with KakaoTalk messenger and the chatbot program was applied to 28 people in the experimental group over 4 periods. As a result, both multicultural awareness and class satisfaction were significantly increased in the experimental group than in the control group and this can be said as a result showing that multicultural education using chatbots is effective.

최근 발생한 COVID-19의 확산은 언택트 또는 디지택트라는 새로운 생활양식을 초래하고 있으며 이로 인해 교육과 관련된 분야에서는 에듀테크와 관련된 다양한 논의가 진행되고 있는데 그 키워드 중 하나가 챗봇이다. 현재 한국의 다문화 정책은 다문화 학생을 지원하는 측면에서는 좋은 점수를 받고 있으나 모든 학생을 위한 다문화 교육 지원은 다소 미미하다는 지적을 받고 있는데 이에 이 연구에서는 다문화 교육에서의 챗봇 활용 가능성을 탐색하였다. 연구를 위해 단비.ai 챗봇 플랫폼을 활용해 챗봇용 다문화 교육 프로그램을 개발하였다. 이때 학생의 참여도와 연구 확장성을 높이기 위해 API key값을 활용하여 카카오톡 메신저와 연동하였으며 총 4차시로 이루어진 다문화 교육용 챗봇 프로그램을 개발하였다. 통제집단 26명과 실험 집단 28명으로 이루어진 연구 대상에게 챗봇 프로그램을 적용하였으며 그 결과, 다문화 인식과 수업 만족도 모두 통제 집단보다 실험 집단에서 유의한 상승이 나타났다. 익숙하지 않은 온라인 환경에서의 수업이 자칫 학생의 수업 만족도를 낮추는 요인이 될 수 있다는 점을 고려할 때 이러한 결과는 챗봇이 새로운 에듀테크의 대안이 될 수 있을 뿐만 아니라 학생들의 다문화 역량 함양을 위한 수업 콘텐츠로서의 가능성을 확인한 결과라 할 수 있다.

Technologies such as artificial intelligence and big data are causing a paradigm shift in the industrial field, and the recent spread of COVID-19 has brought about a new lifestyle called untouch or digital. For this reason, various discussions related to edutech are in progress in the field related to education, and one of the keywords is chatbot. Currently, Korea's multicultural policy is receiving good marks in terms of supporting multicultural students, but it is being criticized for the lack of support for multicultural education for all students. Based on the above discussion, this study explored the possibility of using chatbots in multicultural education. For research, we developed a multicultural education program for chatbots using the Danbi.ai chatbot platform. At this time, in order to increase student participation and research scalability, the API key value was used to link with KakaoTalk messenger and the chatbot program was applied to 28 people in the experimental group over 4 periods. As a result, both multicultural awareness and class satisfaction were significantly increased in the experimental group than in the control group and this can be said as a result showing that multicultural education using chatbots is effective.

With the rapid advancement of artificially intelligent (AI) technology, its applications are expanding across various sectors of society. The field of English education is no exception, witnessing a swift integration of AI tools. In this context, this study empirically examined teachers’ (n = 107) and learners’ (n = 147) perceptions of the complementary roles of AI chatbots and human instructors in English education. Using both one-sample and independent-sample t-tests, this study revealed that teachers rated the usefulness of chatbots significantly higher than students, although both groups recognized their value for grammar, vocabulary, and pronunciation support. Teachers also perceived chatbot limitations more strongly, stressing their insufficiency in emotional support and motivation. Both groups rated human teachers’ roles very highly, with teachers showing stronger awareness of pedagogical and affective functions. While learners acknowledged teachers’ indispensability, they also recognized the supportive role of AI. Finally, both groups expressed positive attitudes toward a collaborative instructional model, viewing AI and human instructors not as substitutes but as complementary partners in language learning.