• Knowledge Management Research
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• v.25 no.2
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• pp.19-47
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• 2024

Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.157-167
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• 2022

This study was conducted to confirm the relationship between the proactive accounts receivable management of SMEs on credit sales decision making and business performance, and to derive effective accounts receivable management plan and systematic credit sales decision making plan. Based on 455 copies of data collected through a survey targeting SMEs, it was confirmed through factor analysis, reliability analysis, confirmatory factor analysis, and model fit verification, and the research hypothesis was verified with a structural equation model. As a result of the verification, credit rating had a positive effect on financial performance, sales performance and credit sales decision, while credit control had a positive effect on financial performance, while negative effect on sales performance and credit sales decision. In the mediating effect hypothesis test, credit sales decision had a positive effect between credit rating and business performance and a negative effect between credit control and business performance. The study suggests that if small and medium-sized enterprises improve their business performance through effective accounts receivable management, they can create a synergistic effect in enhancing the business performance of companies if they simultaneously improve their proactive accounts receivable management and credit sales decision ability. Future research is required to study the impact of factors such as segmentation of research subjects and credit transaction motives and accounts receivables management.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.1-12
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• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• Journal of the Korea Convergence Society
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• v.8 no.6
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• pp.121-130
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• 2017

The purposed of this study was to identify the factors that affect Confidence in Performance Patient Safety Management targeted nursing students. The study subjects were 228 nursing students. The nursing students experienced patientl safety accidents in the fall (50.0%), needle puncture (18.5%), Patient identification error (12.0%), injection medication error (7.5%) and oral medication errors (4.3%). In the logistic regression analysis, Attitude of Patient Safety Management(t=6.09, p<.001), Clinical Decision Making(t=3.97, p<.001) and gender(t=2.56, p=.011) were significant factors related to Confidence of Performance Patient Safety Management. Based on the results of this study, we propose to develop a convergence education program that considers patient safety management attitude, clinical decision making ability, and gender in order to improve confidence of performance patient safety management of nursing students.

• Journal of Gifted/Talented Education
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• v.21 no.3
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• pp.703-718
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• 2011

Team-Based Learning can play an important role in gifted education, because that improve decision making, coordination and problem-solving ability through shapely team activity. So, when a program that founded on Team-Based Learning applied to gifted students, investigated the improved effects of creative problem solving ability. Developed programs consisted of total 10 times and were conducted the lesson for 13student (male 3, female 10) of 4, 5th grade gifted students class in S elementary school, Sancheong-gun. The improved effects of creative problem solving ability were selected as the self-checking tool of creative problem-solving ability. Due to a small number of students, nonparametric test has done with the results of before and after, it showed significantly improvements in significance level of 5%. In particular, there was a significant improvement in the field of divergent thinking, critical logical thinking. Therefore, the programs based on Team-Based Learning are effective for enhance creative problem solving ability of gifted students, they will be used widely in the classroom to require creative problem solving ability or the acquisition of knowledge of gifted students.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.21 no.2
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• pp.63-71
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• 2015

Background: The purpose of the study, using the ICF Tool in the process of rehabilitation of artificial joint replacement surgery of the hip joint, goal setting and understanding of the problem, through the process of creating intervention strategies, useful clinical practical course for rehabilitation I try to present the data. Methods: Fracture was the left total hip replacement (THR) surgery due to women of 76 years old. I proceed in order screening, evaluation, diagnosis, prognosis, treatment planning and intervention, re-screening. Needs of the patient was walking short distances for using the toilet. In order to improve was carried out arbitration, after you have created a list of issues that limit the ability to walk short distances. Results: It was revealed improved results in self-paced walk test (SPWT) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was used to examine whether the goals. In addition, MMT VAS, DGI, and TUG is a detailed goal was improved. Conclusions: It can be shown objectively the results of interventions performed for the purpose of solving the problem which is grasped through clinical Practical course for short-range walking ability enhance patient THR. I considered practical clinical course using the ICF Tool would be useful.

• Safety and Health at Work
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• v.6 no.4
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• pp.305-311
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• 2015

Background: The purpose of this study was to examine the relationship nursing personal and workplace system factors (work disability) and work ability index scores in Ontario, Canada. Methods: A total of 111 registered nurses were randomly selected from the total number of registered nurses on staff in the labor, delivery, recovery, and postpartum areas of four northeastern Ontario hospitals. Using a stratified random design approach, 51 participants were randomly selected in four northeastern Ontario cities. Results: A total of 51 (45.9% response rate) online questionnaires were returned and another 60 (54.1% response rate) were completed using the paper format. The obstetric workforce in northeastern Ontario was predominately female (94.6%) with a mean age of 41.9 (standard deviation = 10.2). In the personal systems model, three variables: marital status (p = 0.025), respondent ethnicity (p = 0.026), and mean number of patients per shift (p = 0.049) were significantly contributed to the variance in work ability scores. In the workplace system model, job and career satisfaction (p = 0.026) had a positive influence on work ability scores, while work absenteeism (p = 0.023) demonstrated an inverse relationship with work ability scores. In the combined model, all the predictors were significantly related to work ability scores. Conclusion: Work ability is closely related to job and career satisfaction, and perceived control at work among obstetric nursing. In order to improve work ability, nurses need to work in environments that support them and allow them to be engaged in the decision-making processes.

• Journal of Korean Library and Information Science Society
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• v.39 no.3
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• pp.53-71
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• 2008

This study attempts to analyse factors that influence the level of career decision for prospective librarians. To this end, an empirical study was conducted on the students from the department of Library & Information Science at universities located in Seoul, Gyeong Gi and Chung Cheong Areas. Exogenous variables included curriculum, career-related departmental activities, and librarian-related institutional factors. The result of analysis using the Structural Equation Model reveals that career-related departmental activities are preceding factors which affect the level of career decision and that personality types function as a modulator. This suggests that, in order to raise the career decision level, prospective librarians need to participate in career-related departmental activities, which make it easier to share information regarding career and thus enhance the level of career. Such career-related departmental activities include participating in job-oriented circles and career-consulting programs, communicating with seniors, and operating and joining career programs. Further organizational and institutional development is required : better curriculum, improved practical ability and qualifications as librarians. This study also discusses its limits and areas for future research.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.151-158
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• 2018

The purpose of this study is to develop a system for predicting students' collaborative problem solving ability based on the ICT factors of PISA 2015 that affect collaborative problem solving ability. The PISA 2015 computer-based collaborative problem-solving capability evaluation included 5,581 students in Korea. As a research method, correlation analysis was used to select meaningful variables. And the collaborative problem solving ability prediction model was created by using the deep learning method. As a result of the model generation, we were able to predict collaborative problem solving ability with about 95% accuracy for the test data set. Based on this model, a collaborative problem solving ability prediction system was designed and implemented. This research is expected to provide a new perspective on applying big data and artificial intelligence in decision making for ICT input and use in education.

• The Mathematical Education
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• v.60 no.2
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• pp.133-157
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• 2021

Ill-structured problems have drawn attention in that they can enhance problem-solving skills, which are essential in future societies. The purpose of this study is to analyze and evaluate students' spatial reasoning(Intrinsic-Static, Intrinsic-Dynamic, Extrinsic-Static, and Extrinsic-Dynamic reasoning) and problem solving abilities(understanding problems and exploring strategies, executing plans and reflecting, collaborative problem-solving, mathematical modeling) that appear in ill-structured problem-solving. To solve the research questions, two ill-structured problems based on the geometry domain were created and 11 lessons were given. The results are as follows. First, spatial reasoning ability of sixth-graders was mainly distributed at the mid-upper level. Students solved the extrinsic reasoning activities more easily than the intrinsic reasoning activities. Also, more analytical and higher level of spatial reasoning are shown when students applied functions of other mathematical domains, such as computation and measurement. This shows that geometric learning with high connectivity is valuable. Second, the 'problem-solving ability' was mainly distributed at the median level. A number of errors were found in the strategy exploration and the reflection processes. Also, students exchanged there opinion well, but the decision making was not. There were differences in participation and quality of interaction depending on the face-to-face and web-based environment. Furthermore, mathematical modeling element was generally performed successfully.