• Journal of Information Technology Services
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• v.20 no.4
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• pp.129-140
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• 2021

Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.831-838
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• 2022

Machine Learning is a process of using computer algorithms to extract information from raw data to solve complex problems in a data-rich environment. It has been used in the construction industry by both academics and practitioners for multiple applications to improve the construction process. The Construction Industry Institute, a leading construction research organization has twenty-five years of experience in benchmarking capital projects in the industry. The organization is at an advantage to develop useful machine learning applications because it possesses enormous real construction data. Its benchmarking programs have been actively used by owner and contractor companies today to assess their capital projects' performance. A credible benchmarking program requires statistically valid data without subjective interference in the program administration. In developing the next-generation benchmarking program, the Data Warehouse, the organization aims to use machine learning algorithms to minimize human effort and to enable rapid data ingestion from diverse sources with data validity and reliability. This research effort uses a focus group comprised of practitioners from the construction industry and data scientists from a variety of disciplines. The group collaborated to identify the machine learning requirements and potential applications in the program. Technical and domain experts worked to select appropriate algorithms to support the business objectives. This paper presents initial steps in a chain of what is expected to be numerous learning algorithms to support high-performance computing, a fully automated performance benchmarking system.

• The Research Journal of the Costume Culture
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• v.17 no.1
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• pp.177-188
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• 2009

SCM as the important marketing strategy enhance the firm's efficiency and compatibility in global market environment such as global outsourcing. Firms adopted SCM realized the need to evaluate precisely the performance of SCM. In spite of importance of SCM, there was not much intention and research to measure SCM performance in textile fashion industry. Therefore, the purpose of this case study was to measure performance of supply chain management in textile fashion business using BSC(Balanced Score Card) to measure not only financial perspective but also non-financial perspectives such as customer perspective, internal business perspectives, financial perspective, and innovation & learning perspective. The questionnaire developed by the reviews of the literature was adopted for this study. The results of this study showed that SCM performance was enhanced from the point of customer perspective(cost, quality, time, service), financial perspective(cash cycle time, inventory turn over, inventory obsolescence, return on asset, return on investment, capacity utilization), and innovation & learning perspective(cost for human resource management, service for human resources). But there was same performance level regarding internal business perspective(lead time, cost for manufacturing process, product quality control, productive flexibility for time, quantity, and variety). Therefore, we should keep close relationship and two way communication among supply chain members to promote better SCM performance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.27-37
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• 2023

The purpose of this study was to analyze the effect of the online extracurricular program operated by the university. The program contents applied in the study included learning strategies such as time management, goal setting, note taking, and memorization methods. The program used in the study was operated in an online environment, and the content was developed between 27 and 29 minutes. The developed contents can be taken using the learning management system. The variables selected to analyze the effects of this program were learning strategies and learning flow, and satisfaction was also included to examine the responses of program participants. The results of the study are as follows. First, learning strategies and learning flow showed statistically significant differences. This result is because the content was composed of meaningful sub-topics by selecting the elements necessary for learning activities. Second, as a result of program satisfaction analysis, it was confirmed that the average for all questions was high. Among them, the average of the item that the theme and contents of the program were useful was the highest. Third, open responses were analyzed by classifying them into cognitive and affective domains. In the cognitive domain, meanings such as knowledge, understanding, and application were presented as keywords, and in the affective domain, a number of keywords for motivation and attitude change were presented. This study is significant in that it provided practical programs necessary for university freshmen and analyzed their effects.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.249-260
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• 1997

The manufacturing environment is rife with nonlinear processes. In this context, an intelligent production controller should be able to predict the dynamic behavior of various subsystems as they react to transient environmental conditions, the varying internal condition of the manufacturing plant, and the changing demands of the production schedule. This level of adaptive capability may be achieved through a coherent methodology for a learning coordinator to predict nonlinear and stochastic processes. The system is to serve as a real time, online supervisor for routine activities as well as exceptional conditions such as damage, failure, or other anomalies. The complexity inherent in a learning coordinator can be managed by a modular architecture incorporating case based reasoning. In the interest of concreteness, the concepts are presented through a case study involving a knowledge based robotic system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.101-110
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• 2011

The change of digital convergence service environment converted the subject of design into user -centric one instead of developer-centric one, and changed the existing design environment focused on product development into the new user -centric design environment. Accordingly, GUI considering user's usability come to take big shares in those contents being used for multimedia equipments. However, as the present educational contents provide complex interface due to its design produced based on the existing e-learning system, they have many problems in that they don't consider user's usability. Thus this paper aimed to analyze actual examples through GUI elements of educational contents being used for multimedia equipments and attempt to suggest some directions for development. additionally, consider the various characteristics of digital convergence environment and educational contents, and try to set up strategic directions possible to utilize user'-centric interface elements more usefully and properly at the time to produce designs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.107-115
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• 2024

With the advent of the 4th Industrial Revolution, changes in the market environment and employment environment are accelerating due to smart technological innovation, and securing professional manpower and developing human resources for domestic small and medium-sized enterprises is becoming very important. Recently, most of the domestic small and medium-sized enterprises are experiencing hiring difficulties, and the development and training of human resources to overcome this is still lacking in systemization, despite much support from the government. This reflects the reality that it is not easy to invest training costs and time to adapt new employees to small and medium-sized businesses. Based on these problems, the work-study parallel project was introduced to cultivate practical talent in small and medium-sized businesses. Work-study parallel training is carried out in the form of mentoring between corporate field teachers and learning workers in actual workplaces, and even if the training is the same, there are differences depending on the learner's attitude, learning motivation, and training achievement. Ego state is a theory that can identify personality types and has the advantage of being able to understand and acknowledge oneself and others and intentionally improve positive factors to induce optimized interpersonal relationships. Accordingly, the purpose of this study is to analyze the attitudes of learning workers, who are the actual subjects for improving the performance of work-study parallel projects and establishing a stable settlement within the company, based on their ego status. Through this study, we aim to understand the impact of the personality type of learning workers on training performance and to suggest ways to improve training performance through work-study parallelism.

• Journal of Korea Multimedia Society
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• v.22 no.8
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• pp.823-831
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• 2019

In recent years, there has been developed systems such as a surveillance system and access control using a face recognition function instead of a password or an RFID chip, thereby reducing the risk of falsification. Moreover, deep learning technology has been applied to real-time face recognition technology in video, so it makes possible the development of access control system that improves the accuracy of recognition and efficiency of management. In this paper, we propose a real-time access management system based on face recognition using ResNet. The system is based on web server, which make it possible to manage the access by recognizing the person of the image through the camera and access information stored in the database. It can be accessed by a user application to receive various information. The implemented system identifies a person in real time and allows access control by accurately distinguishing whether they are members or not, and the test results can recognize in 0.2 seconds. The accuracy of recognition rate is up to about 97% depending on the experiment environment. With this system, access can be managed quickly and effectively, even many people rush to it.

• International Journal of Contents
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• v.6 no.1
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• pp.12-19
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• 2010

In this paper, attendance in distance learning courses of a cyber university has been surveyed in an effort to verify the effectiveness of distance learning. Based on survey data from 4,749 distance learning participants, major attending place, major reasons for attending online class, fidelity to online classes, attending time per week, perceived educational effectiveness, perceived and relative seriousness of problems, and other variables have been evaluated. The results indicate that perceptional seriousness of the investigated problems is not statistically important. The findings indicate that, among operational problems, self willingness and cheating are the most remarkable. In contrast, the relative seriousness of traditionally recognized problems such as H/W availability and network speed among environmental problems is least remarkable. An analysis of demographic differences such as sex, employment, and school year in terms of seriousness of problems is also performed. The results reveal the existence of statistically significant differences according to sex, employment, and school year with regard to almost all elements of environment, actual current conditions, and seriousness of problems, with the exception of some elements such as attending place and perceived fidelity.

• Journal of Industrial Convergence
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• v.19 no.3
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• pp.27-34
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• 2021

In the era of the 4th industrial revolution, the age of artificial intelligence, the development of ICT technology is having various effects on the online and offline educational environment. The universal access of online education changes the educational paradigm and converts it to a learner-centered service. At the time when a new educational environment is required to change, interest in flip learning is increasing. Even adult learner's online learning needs is also shown very high. The purpose of this study was to investigate how repetitive learning activities through flip learning for middle-aged online learners of K-Cyber University has a relationship and structural relationship between the effects of learning immersion and learning interest on learning satisfaction. Through this study, there is significance in research to suggest direction for learning satisfaction based on flip learning. For further studies, if a model of analysis of various factors that can be measured is specified and applied, it can be used as a research background that can maximize learning satisfaction based on flip learning.