• Journal of Practical Engineering Education
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• v.16 no.5_spc
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• pp.643-651
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• 2024

This study aims to design and implement an AI mock interview system for Computer Science (CS) interview preparation using LLM (Large Language Model) based ChatGPT. The system utilizes AI's natural language processing and speech recognition capabilities to analyze and provide real-time feedback on interview responses, helping users improve their weaknesses during the preparation process. According to a survey, 90% of users reported that the real-time feedback function provided substantial assistance in their interview preparation. Key features include GPT prompt generation and Speech-to-Text functionality, which converts voice data into text. The system received positive evaluations for its response time and feedback accuracy. Future research will explore expanding the range of question types and applying the system to various industries.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.753-762
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• 2020

With an increasing interest in integrating artificial intelligence (AI) into interview processes, the Republic of Korea (ROK) army is trying to lead and analyze AI-powered interview platform. This study is to analyze the AI interview data using a unified non-crossing multiple quantile tree (UNQRT) model. Compared to the UNQRT, the existing models, such as quantile regression and quantile regression tree model (QRT), are inadequate for the analysis of AI interview data. Specially, the linearity assumption of the quantile regression is overly strong for the aforementioned application. While the QRT model seems to be applicable by relaxing the linearity assumption, it suffers from crossing problems among estimated quantile functions and leads to an uninterpretable model. The UNQRT circumvents the crossing problem of quantile functions by simultaneously estimating multiple quantile functions with a non-crossing constraint and is robust from extreme quantiles. Furthermore, the single tree construction from the UNQRT leads to an interpretable model compared to the QRT model. In this study, by using the UNQRT, we explored the relationship between the results of the Army AI interview system and the existing personnel data to derive meaningful results.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.75-80
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• 2021

Do happy applicants achieve more? Although it is well established that happiness predicts desirable work-related outcomes, previous findings were primarily obtained in social settings. In this study, we extended the scope of the "happiness premium" effect to the artificial intelligence (AI) context. Specifically, we examined whether an applicant's happiness signal captured using an AI system effectively predicts his/her objective performance. Data from 3,609 job applicants showed that verbally expressed happiness (frequency of positive words) during an AI interview predicts cognitive task scores, and this tendency was more pronounced among women than men. However, facially expressed happiness (frequency of smiling) recorded using AI could not predict the performance. Thus, when AI is involved in a hiring process, verbal rather than the facial cues of happiness provide a more valid marker for applicants' hiring chances.

• East Asian mathematical journal
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• v.39 no.2
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• pp.93-117
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• 2023

The aim of this study is to explore the pre-service math teachers' characteristics of education to develop their AI literacy and SW competency, and to derive some implications. We conducted a 14-hours AI and SW education program for pre-service teachers with theory and practice, and an analysis on class observation data, video frames of classes and interview, Python programming assignments and papers. The results of this case study for 3 pre-service teachers are as follows. First, two students understood artificial neural network and deep learning system accurately, furthermore, all students conducted a couple of explorations related with performance improvement of deep learning system with interest. Second, coding and exploration activities using Python improved students' computational thinking as well as SW competency, which help them give convergence education in the future. Third, they responded positively to the necessity of AI literacy and SW competency development, and to applying coding to math class. Lastly, it's necessary to endeavor to give a coding education to the student's eye level according to his or her prerequisite and to ease the burden of student's studying AI technology.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.3-14
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• 2020

The purpose of this paper is to analyze the factors effecting users' satisfaction on game AI for early AI diffusion. For this purpose, we interviewed 20 users who had experiences playing Blade&Soul, made by NCsoft. Interview data had been analyzed through the Semantic Network Analysis program to identify key subject words and their relations. As a result, the paper has found keywords such as patterns, contents, variety, system, and getting new users as factors effecting users satisfaction on game AI.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.231-247
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• 2020

As artificial intelligence (AI) has emerged as a promising future technology among the fourth industrial revolution, we are trying to apply artificial intelligence technology across all area of society, including libraries. This study investigated the effects, issues, and implications of artificial intelligence on university library services. As a research method, in-depth interviews were conducted with IT experts of university libraries in North America, and conclusions and discussion were drawn from interview results and related documents. Research results revealed that university libraries in North America were trying to build an infrastructure that facilitates information access and retrieval based on artificial intelligence systems and to provide new services in collaboration with AI research institutes in universities. This study raised issues regarding the expansion of the role of libraries and librarians, privacy, and data quality. It was also discussed that the need for re-education of university librarians to become software engineers who play a role in disseminating knowledge. In addition, this study suggested the investment for the establishment of the information system and an artificial intelligence research center in the library. The study discussed limitations of research due to changes in the research environment and suggestions for future research.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.39-59
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• 2022

We analyze the perceptions and requirements of early childhood teachers for artificial intelligence(AI) education to develop an AI education program for 5-year-olds. As for the research methodology, we conducted a survey and an in-depth interview to extract the AI educational elements centering on the analysis stage, the first stage of the ADDIE model. The research result is that first, it is necessary to design a curriculum that combines the contents of early childhood education and AI education to be naturally accepted as AI education for 5-year-olds. Second, an evaluation tool for AI education that can showcase the teacher's reflection should be developed systematically. Third, it is necessary to support a play-centered AI education support and environment for early childhood teachers. Lastly, it is essential to establish a system that can be continuously operated in the field of early childhood education in consideration of AI education in the non-curricular curriculum. It is expected that in the future, a play-oriented AI education program for 5-year-olds will be developed to spread awareness of AI education for infants and present an AI education approach for each age and stage of learners.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.777-786
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• 2023

Generative AI systems are expected to be more widely utilized. However, relatively little attention has been paid to understanding how users perceive and accept generative AI results. To identify strategies for increasing the future use of generative AI and prepare for potential issues, we organized design workshop for the general user group and the designer group. They created artwork utilizing Novel AI and semi-structured interview was followed to evaluate their attitudes toward generative AI and its copyright. Results indicate that the general public views generative AI positively, while the design-related group views it quite negatively. The participants expressed concerns as to the misuse the system, specifically related to copyright issues. People who are likely to utilize generative AI outcomes have insisted more strongly that copyrights should be their own. Those working in the design field highly evaluated the possibility of using generative AI in their work. Copyright perceptions were not significantly influenced by users' satisfaction or their level of involvement in the creation process. We discuss design implications for interfaces using generative AI based on the findings.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.17-36
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• 2022

The purpose of this study is to diagnose problems in the regulation and management of Restricted Development Zone and to prepare a construction plan to convert it to a data-based monitoring system. Unlike other land-use zones, the Restricted Development Zone is a exceptional zone that prohibits all development activities other than the minimum maintenance and must be strictly controlled and managed by the local government. However, the current Restricted Development Zone management is distributed according to the conditions of each local government, and it is not possible to monitor changes in the entire Restricted Development Zone as shown in the survey results. In particular, in this study, by introducing an AI-based monitoring system, MOLIT sends the results of detecting changes across the country at regular time points(monthly and quarterly) to the local governments based on the same regulation standards, and the local governments can be trusted while inputting the regulation results into the system. To propose this methodology, first, a survey and interview were conducted with local government officials and experts. Second, we analyzed cases in which AI analysis was applied to local governments and proposed a plan to improve the efficiency of regulation work according to the introduction of the monitoring system. Third, a plan was prepared to establish a monitoring system based on the advancement of the management information system. This monitoring system can be expanded and applied to land that needs periodic regulation and management in the future, and this study tried to propose a methodology and policy for this.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.167-176
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• 2019

The purposes of this study are first to identify the core competences of design leadership and second to propose the characteristic and effective leadership capabilities required in the design field. To propose the capabilities of reliable and meaningful core competency of design leadership, we identified core competencies through a group of experts from the top group of design leaders (Design executives, head of the design institute) rather than using a survey study based on unspecified designers. In addition, the unique interview method, AI (Appreciated Inquiry) was also used to share the actual experiences and philosophies of the interviewers, regardless of the core competencies. This study revealed that the core competences of design leadership were different from those of conventional general leadership and MOT (Management of Technology) leadership capabilities. Besides, it provided opportunities for leaders in other fields to understand and collaborate on characteristics of the design field, while demonstrating the necessity and justification of unique leadership traits in the field of design.