• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.35-40
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• 2019

The purpose of this study was to investigate the effects of learners' academic achievement and learner interaction through project - based learning. In the case of interaction, we focused on the field of learning, that is, the learner's communication style in various technical environments. The subjects of this study were 80 learners who took a 3-hour elective English language learning course at a university in Korea. This study is to investigate the effect of learner interaction through KakaoTalk and LMS (Learning Management System). As a result of the study, it was found that there was a significant difference between learner interaction by project - based learning and communication type and kakao talk utilization group and LMS (Learning Management System) group. 1) The results of the kakao talk utilization group were significant in both the learner interaction and the learner's academic achievement according to the project - based learning and communication type. For current digital native learners, Kakao Talk is the result of the fact that it is the optimal environment for problem solving, communication, and uploading and sharing of educational activities.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.719-721
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• 2022

본 논문은 비전공자의 프로그래밍 수업에서 발생하는 오류들을 수집하고 오류 유형을 분석하여 초보 프로그래머의 오류 문제 해결을 쉽게 접근할 수 있도록 하고 교수자가 하는 피드백을 인공지능을 통해 자동화하는 시스템을 개발하는 기초 연구가 되는 것을 목표로 하였다. 결과로는 분석한 오류 유형에는 컴파일 타임에러가 가장 많이 발생하였고 그중에서도 구문에러(syntax error), 그중 missing 에러가 가장 많이 나타났다. 비전공자 학습자는 에러메시지를 이해하는 것을 가장 어려워하였고, 교수자의 피드백을 가장 절실하게 필요로 하였다. 좋은 오류 메시지는 초보자 프로그래머를 위한 프로그램 사용성에 큰 차이를 만들 수 있어 오류 메시지 내용을 단순화시킬 필요가 있으며, 학습자와 교수자의 상호작용을 효율적으로 이루어지게 할 필요가 있고, 인공지능을 통한 피드백을 자동화할 필요가 있음을 제언하였다. 향후 과제로는 오류 유형 중 자주 발생하는 구문에러부터 해결할 수 있는 인공지능을 이용한 자동 피드백 프로그램을 만들어 학습자와 실시간 상호작용하여 온라인에서 프로그래밍 수업이 가능한 학습시스템을 구현하고자 한다.

• Journal of The Korean Association For Science Education
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• v.32 no.4
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• pp.671-685
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• 2012

In this study, we developed an analogical experimental design strategy emphasizing understanding and checking stages and applied it to four groups consisting of 7th grade science-gifted students. We classified the patterns of experimental design processes and analyzed the verbal interactions among the science-gifted students at the levels of turn and interaction unit. The analyses of the results reveled that three groups were relevant to reinitiated motion and the other to backward-divergent motion. In the analyses of turn and interaction unit, the frequencies of the statements related to the task were high, especially 'making suggestion' and 'elaborated symmetrical interaction'. The analyses for each stage of strategy indicated that the frequencies of 'explain', 'question', and 'cumulative interaction' at understanding stage were high. At designing stage, the frequencies of 'making suggestion', 'cumulative interaction', and 'disputative interaction' were found to be high. At checking stage, 'making suggestion', 'receiving opinion', and 'disputative interaction' were high. In the comparison of the patterns, the qualitative differences among interaction unit were found at all the stages, whereas there were differences only between designing and checking stages in the turn cases. Educational implications of these findings are discussed.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.21-41
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• 2024

This study explores the relationship between users' attachment styles and their interactions with ChatGPT (Chat Generative Pre-trained Transformer), an advanced language model developed by OpenAI. As artificial intelligence (AI) becomes increasingly integrated into everyday life, it is essential to understand how individuals with different attachment styles engage with AI chatbots in order to build a better user experience that meets specific user needs and interacts with users in the most ideal way. Grounded in attachment theory from psychology, we are exploring the influence of attachment style on users' interaction with ChatGPT, bridging a significant gap in understanding human-AI interaction. Contrary to expectations, attachment styles did not have a significant impact on ChatGPT usage or reasons for engagement. Regardless of their attachment styles, hesitated to fully trust ChatGPT with critical information, emphasizing the need to address trust issues in AI systems. Additionally, this study uncovers complex patterns of attachment styles, demonstrating their influence on interaction patterns between users and ChatGPT. By focusing on the distinctive dynamics between users and ChatGPT, our aim is to uncover how attachment styles influence these interactions, guiding the development of AI chatbots for personalized user experiences. The introduction of the Perceived Partner Responsiveness Scale serves as a valuable tool to evaluate users' perceptions of ChatGPT's role, shedding light on the anthropomorphism of AI. This study contributes to the wider discussion on human-AI relationships, emphasizing the significance of incorporating emotional intelligence into AI systems for a user-centered future.

• Korean Journal of Childcare and Education
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• v.9 no.1
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• pp.101-128
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• 2013

This study investigated the interactions between infants of differing natures and teachers in a nursery, and to find the right way to foster the relationship. This study was carried out for 13 weeks, in a class consisting of eight children between one and two years old and with two teachers. The sources of data collection included observations, interviews with teachers, taking videos and voice recording. The results were as follows. (1) Infants with different natures show different reactions in the same situation and it affects the interaction between them and the teachers. (2) The types of interactions among infants with different natures are distinct and the interaction is influenced by factors other than just their nature. A constant interaction between infants and teachers based on the natures of infants and situational reacting strategies toward infants tremendously influence infants' development.

• Journal of The Korean Association For Science Education
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• v.26 no.1
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• pp.16-24
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• 2006

The purpose of this study was to compare student-student verbal interaction from two type's experiments; problem-solving and task-solving. For this study, five 3rd grade middle school students were selected and their verbal interactions recorded via voice and video; and later transcribed. The student-student verbal interactions were classified as questions, explanations, thoughts, or metacognition fields, which were separated into deep versus surface learning approaches. For the problem-solving experiment, findings revealed that the number of verbal interactions is more than doubled and in particular, the number of verbal interactions using deep-approach is more than quadrupled from the point of problem-recognition to problem-solution. As for the task-solving experiment, findings showed that verbal interactions remained evenly distributed throughout the entire experiment. Finally, it was also discovered that students relied upon a more deep learning approach during the problem-solving experiment than the task-solving experiment.

• Science of Emotion and Sensibility
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• v.10 no.2
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• pp.155-168
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• 2007

Social and psychological experiences in human-agent interactions are becoming more important than the task-oriented efficiency, as the influence of computer agents increases and human-agent interaction develops similarly with interpersonal interaction. Many previous studies aimed to increase social presence in human-agent interaction, in order to derive users' positive psychological experiences, by applying the factors of interpersonal communication to verbal and non-verbal communication of the agents. This study examined the effects of the exchanges of mutual self-disclosure, one of the most important communication acts in interpersonal communication, between users and interface agents. Users' attachment styles towards the perception of social presence, the evaluations toward the agents, user experiences, and the intentions for future interaction were also studied. The mediating role of social presence in dependent variables was, also, examined in this research. The results showed that exchanging self-disclosures with an agent increased the perceptions of social experience, friendly evaluations toward the agent, positive user experience, and the intentions for future interaction. Participants' attachment styles, also, affected the perceptions of the dependent variables. The effects of the exchanges of self-disclosure and participants' attachment styles were mediated by perceived social presence toward the agent. The findings of this study imply that the social and communicational aspects need to be considered in design of the agents seriously. The results also suggest that there may be differences in the psychological effects of agents on users according to the users' personality.

• Korean Journal of Childcare and Education
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• v.9 no.5
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• pp.321-334
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• 2013

The purpose of this study was to examine the relationship of father's verbal control modes, children's self efficacy, social competence and interactive peer play. The subjects were pairs of 195 three, four and five year-old-children and their fathers. Data were analyzed with mean, standard deviation, and bivariate correlation. Results indicated that father's verbal control modes were significantly correlated with children's self efficacy, social competence and interactive peer play. Father's person-oriented control verbal mode was positively related to children's self-recognition, self-emotion, social competence, leadership and interactive peer play while imperative control verbal mode was negatively related to children's instability, interrupted play behavior, and disturbed play behavior.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.131-141
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• 2017

This paper analyzed class satisfaction and perceived learning achievement to the interaction type on e-learning in university. To achieve the study's objective, one course with and another course without learner-instructor interactions were selected. A total of184 student-respondents completed the questionnaire. Accordingly, more learner-content and learning-system interactions were noted in the course with learner-instructor interactions. Moreover, a correlation was observed between interaction, class satisfaction, and learning achievement. Learner-instructor interactions indicated the highest effect on both educational satisfaction and perceived learning achievement, followed by learner-system interactions on class satisfaction, and by learner-instructor interactions on learning achievement. Recommendations were then formulated based on the foregoing findings. First, workshops or training focusing on content development and on how to present the course should be provided to the instructors. Second, learner-instructor interactions should be activated in the course through various means. In this study, although learner-learner interactions was not given focus, future studied should delve into how learner-learner interaction should be activated and considered.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.19-29
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• 2020

As the AI speaker market is growing rapidly in recent years, the competition for the preoccupation of children who are the main users and the future prospective customers of the related companies is very intense. However, there is a lack of empirical research on how children interact with AI speakers. Therefore, this research examines the interactions between children and AI speakers, primarily through field studies, to extract what functions they use and what features they have. For this purpose, 799 conversations were collected and analyzed using the log data of the AI speaker recorded in real time. As a result, children were more likely to use children's songs, fairy tales, emotional conversations, and personification compared to adults. In addition, content analysis by specific types resulted in success/failure cases of interaction between children and AI speakers and proposed improvements by failure type. This study is meaningful in that it identifies children's AI speaker preferences, content, and major conversation patterns, and provides guidelines for developing services that meet children's eye level.