• Cross-Cultural Studies
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• v.48
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• pp.223-252
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• 2017

This study explores effects of two types of chatbots - voice-based and text-based - on Korean EFL learners' speaking competence and learner perception. Participants were 80 freshmen students taking an English-speaking class at a university in Korea. They were divided into two experimental groups at random. During the sixteen-week experimental period, participants engaged in 10 chat sessions with the two different types of chatbots. To take a close examination of effects on the improvement of speaking competence, they took the TOEIC speaking test as pre- and post-tests. Structured questionnaire-based surveys were conducted before and after treatment to determine if there are changes in perception. Findings reveal two chatbots effectively contribute to improvement of speaking competence among EFL learners. Particularly, the voice-based chatbot was as effective as the text-based chatbot. An analysis of survey results indicates perception of chatbot-assisted language learning changed positively over time. In particular, most participants preferred voice-based chatbot over text-based chatbot. This study provides insight on the use of chatbots in EFL learning, suggesting that EFL teachers should integrate chatbot technology in their classrooms.

• The Journal of the Korea Contents Association
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• v.19 no.4
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• pp.12-29
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• 2019

The purpose of this study is to develop the scenario for implementation of the rule-based counseling chatbot and to verify its usefulness. For this purpose, counseling scenario for exploring problems triggering depression and establishing early counseling relationships was built and user evaluations for the rule-base counseling chatbot were conducted on 10 counseling psychologists. As a result, clear counseling structuring, appropriate use of selective and narrative responses, and active listening were identified as important components of counseling chatbot. To the next step, the usefulness of counseling chatbot developed in the previous step was examined with 78 college students. As a result, active listening was found to be an important factor in improving user satisfaction and positive mood change. In addition, through qualitative analysis of user evaluation, the unique advantages of counseling chatbot were identified and the limitations of counseling chatbot that should be overcome were identified. Based on the results of the study, the implications of the study and suggestions for future research were discussed.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.255-269
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• 2022

In this study, it was necessary to examine consumer acceptance attitudes from an in-depth and multifaceted perspective at a time when the need for chatbot services in various industrial fields is increasing and being activated in earnest. Accordingly, this study conducted a structural equation model to examine not only the structural relationship between ease, usefulness, and playfulness among the main functions of chatbot services and their acceptance attitudes, but also whether there is a mediating effect of service value in the relationship. As a result of the main study of this study, it was identified that the relationship between the ease, usefulness, and playfulness factors, which are the main functional sub-factors of the chatbot service, and their acceptance attitude and service value had a statistically static influence relationship. Based on these research results, the main research conclusions suggest that when companies in various fields provide chatbot services in the future, it is necessary to clearly determine the influencing factors that can affect the chatbot service acceptance attitude and provide these services. Through this, it is expected that the AI chatbot service will strengthen communication with consumers and establish itself as a customized and personalized counseling service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.158-160
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• 2022

Many office workers spend a lot of time performing repetitive office tasks in inefficient ways. We developed a user-friendly chatbot system based on Kakaotalk to automate repetitive tasks and used the chatbot in the real workplace. In the process of operating the chatbot, if several people use the chatbot at the same time, the server was down or could not respond. To address these issues, we performed code migration of programs used by chatbot back-end servers and tried several ways to improve server performance such as database redesign and load balancing. To determine how much each method affects performance improvement, we measured total request per second and average latency. After that, we proposed ways to improve the problems of using the chatbot in the work environment.

• Journal of the Korean earth science society
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• v.44 no.6
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• pp.675-692
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• 2023

This study used a Chatbot, a generative artificial intelligence (AI), to analyze the interaction between the Chatbot and students when exploring critical minerals from an epistemological aspect. The results, issues to be kept in mind in the teaching and learning process using AI were discussed in terms of the role of the teacher, the goals of education, and the characteristics of knowledge. For this study, we conducted a three-session science education program using a Chatbot for 19 high school students and analyzed the reports written by the students. As a result, in terms of form, the students' questions included search-type questions and non-search-type questions, and in terms of content, in addition to various questions asking about the characteristics of the target, there were also questions requiring a judgment by combining various data. In general, students had a questioning strategy that distinguished what they should aim for and what they should avoid. The Chatbot's answer had a certain form and consisted of three parts: an introduction, a body, and a conclusion. In particular, the conclusion included commentary or opinions with opinions on the content, and in this, value judgments and the nature of science were revealed. The interaction between the Chatbot and the student was clearly evident in the process in which the student organized questions in response to the Chatbot's answers. Depending on whether they were based on the answer, independent or derived questions appeared, and depending on the direction of comprehensiveness and specificity, superordinate, subordinate, or parallel questions appeared. Students also responded to the chatbot's answers with questions that included critical thinking skills. Based on these results, we discovered that there are inherent limitations between Chatbots and students, unlike general classes where teachers and students interact. In other words, there is 'limited interaction' and the teacher's role to complement this was discussed, and the goals of learning using AI and the characteristics of the knowledge they provide were also discussed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.167-177
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• 2022

Unlike previous studies on AI chatbot preference that focused mostly on satisfaction, this study considered both satisfaction and dissatisfaction. This study established that (1) AI chatbot preference is driven by attractive, must-be, and one-dimensional qualities, (2) AI chatbot need to develop service strategies by taking into account users' satisfaction and dissatisfaction in accordance with preference drivers, and (3) users view interaction as a requisite and thus, if they are not satisfied with services of a AI chatbot, they don't tend to appeal their opinion and leave the service with AI chatbot. This study emphasizes that a AI chatbot that desires to be a dominant market player must provide differentiated services according to the preference drivers and must continuously encourage user participation in order to improve service quality.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.26-47
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• 2022

Chatbots were an important research subject in the past. A chatbot is a computer program or an artificial intelligence program that participates in a conversation via auditory or textual methods. As the research on chatbots progressed, some important issues regarding them changed over time. Therefore, it is necessary to review the technology with a focus on recent advancements and core research technologies. In this paper, we introduce five different chatbot technologies: natural language processing, pattern matching, semantic web, data mining, and context-aware computer. We also introduce the latest technology for the chatbot researchers to recognize the present situation and channelize it in the right direction.

• Journal of Information Technology Applications and Management
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• v.30 no.4
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• pp.11-28
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• 2023

This paper proposes a method of integrating ChatGPT with traditional chatbot systems to enhance conversational artificial intelligence(AI) and create more efficient conversational systems. Traditional chatbot systems are primarily based on classification models and are limited to intent classification and simple response generation. In contrast, ChatGPT is a state-of-the-art AI technology for natural language generation, which can generate more natural and fluent conversations. In this paper, we analyze the business service areas that can be integrated with ChatGPT and traditional chatbots, and present methods for conducting conversational scenarios through case studies of service types. Additionally, we suggest ways to integrate ChatGPT with traditional chatbot systems for intent recognition, conversation flow control, and response generation. We provide a practical implementation example of how to integrate ChatGPT with traditional chatbots, making it easier to understand and build integration methods and actively utilize ChatGPT with existing chatbots.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.2
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• pp.254-268
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• 2024

Human agents are increasingly being replaced by chatbots. However, like humans, chatbots can also make mistakes in service delivery by failing to provide accurate answers to customer questions while research on service recovery has been highly focused on human employees. Recognizing the necessity of research on effective chatbot service recovery strategies, this study investigated the relationships among service recovery messages (courteous apology vs. humorous apology), perceived sincerity, recovery satisfaction, and continuous usage intention. An online experiment was conducted with the participants randomly assigned to one of two experimental conditions (courteous apology vs. humorous apology). After using the chatbot developed for this study, the participants completed a questionnaire. The analysis results revealed that, in comparison to the humorous apology, the courteous apology had a higher positive predictive effect on perceived sincerity, Furthermore, perceived sincerity and recovery satisfaction sequentially mediated the relationship between the chatbot's courteous apology and continuous usage intention. In conclusion, this study demonstrates that the courteous apology was a more effective approach as a chatbot service recovery strategy. This study offers insights into crafting recovery service messages for chatbots.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.