• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.155-162
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• 2017

This paper suggests efficient learning improvement method of computer use instruction based on flipped learning. Traditional computer use classes were difficult to practice and collaborative with sufficient lectures. However, we used KOCW (Korea Open Courseware) as a footsteps in the class using the flipped learning method and learned in advance before entering the classroom. In the classroom, we conducted collaborative hands on class based on mutual discussion. After the instruction, we measured learning motivation and satisfaction by gender, grade, and major using the motivation test tool. The results showed that degree of attention awareness, perception of class relevance and perception of learning satisfaction were analyzed as 'very satisfied' and 'satisfied' more than 90%.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.583-590
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• 2019

The purpose of this study is to develop an educational program for learning deep learning concepts for elementary school students. The model of education program was developed the deep-learning teaching method based on CT element-oriented teaching and learning model. The subject of the developed program is the artificial intelligence image recognition CNN algorithm, and we have developed 9 educational programs. We applied the program over two weeks to sixth graders. Expert validity analysis showed that the minimum CVR value was more than .56. The fitness level of learner level and the level of teacher guidance were less than .80, and the fitness of learning environment and media above .96 was high. The students' satisfaction analysis showed that students gave a positive evaluation of the average of 4.0 or higher on the understanding, benefit, interest, and learning materials of artificial intelligence learning.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.76-95
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• 2023

As information and communications technology-based "smart hospitals" and "digital healthcare" have become a hot topic in the healthcare field, hospital mobile apps are gaining attention; but, the utilization rate is low due to lack of publicity, unstable systems, and late updates. In this situation, systematic research is needed to increase the utilization rate of hospital mobile apps, but related research has been rare. Therefore, this study integrates the information systems success model (ISSM) from the technical perspective and the expectation-confirmation model (ECM) from the cognitive perspective to demonstrate the influence mechanism on the continuous use intention of hospital mobile apps. For this purpose, an online survey was conducted among 181 Korean adults who have used hospital mobile apps. The results of the structual equation modeling showed that most of the quality factors have significant effects on expectation confirmation, perceived usefulness, and satisfaction. Additionally, expectation confirmation significantly affects perceived usefulness and satisfaction, and both perceived usefulness and satisfaction significantly affect the continuous use intention of hospital mobile apps. This study is of importance in that it integrates the ISSM and ECM and applies them to the context of using hospital mobile apps, which are underutilized in the healthcare field, and provides practical implications for increasing the utilization rate of hospital mobile apps and operating effective and efficient services through the findings.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.157-167
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• 2021

Despite the importance of information technology, research on information-oriented performance management and performance management methods are very insufficient. In this paper, the SSU-ITPM model, a company-wide informatization performance evaluation and management model that reflects the characteristics of the shipbuilding and marine industry with high cooperative and process complexity, was presented. This model consisted of informatization planning and project management, informatization field utilization evaluation, informatization utilization quality evaluation, informatization user satisfaction evaluation, and informatization effect achievement evaluation. In addition, through the application of Company D, the feasibility of practical application of the model was confirmed. This study is expected to provide a practical reference model for informatization performance management of ETO plant-based companies such as the shipbuilding and offshore sector.

• Journal of Integrative Natural Science
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• v.11 no.3
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• pp.131-138
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• 2018

In this paper, we have implemented speeches that utilized the emotion information of the user's speech and image matching and recommendation system. To classify the user's emotional information of speech, the emotional information of speech about the user's speech is extracted and classified using the PLP algorithm. After classification, an emotional DB of speech is constructed. Moreover, emotional color and emotional vocabulary through factor analysis are matched to one space in order to classify emotional information of image. And a standardized image recommendation system based on the matching of each keyword with the BM-GA algorithm for the data of the emotional information of speech and emotional information of image according to the more appropriate emotional information of speech of the user. As a result of the performance evaluation, recognition rate of standardized vocabulary in four stages according to speech was 80.48% on average and system user satisfaction was 82.4%. Therefore, it is expected that the classification of images according to the user's speech information will be helpful for the study of emotional exchange between the user and the computer.

• Journal of The Korean Association of Information Education
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• v.21 no.4
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• pp.437-450
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• 2017

This study derived optimized teaching aids that use the physical computing method as the solution for effective software education at the elementary level. We set standard for selecting physical computing teaching aids in elementary-level by gathering the opinions from previous studies and think tanks and then applied the standard to some aids and choose one. We also made lesson plan and tried it to the experimental group. Subsequently, students' logical thinking skills showed a statistically significant improvement in terms of the t-test. Also, in the analysis of the effect size, it was shown to have a positive influence on the improvement of the students' logical thinking skills. Additionally, survey of satisfaction evaluation from the students showed that the teaching aid selection standard was effective in selecting suitable teaching aids for elementary students and that the classroom activities utilizing physical computing teaching aids were at a suitable level for elementary students.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.459-469
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• 2021

In this paper, a case study of basic data science practice education for field teachers and pre-service teachers was studied. In this paper, for basic data science education, spreadsheet software was used as a data collection and analysis tool. After that, we trained on statistics for data processing, predictive hypothesis, and predictive model verification. In addition, an educational case for collecting and processing thousands of public big data and verifying the population prediction hypothesis and prediction model was proposed. A 34-hour, 17-week curriculum using a spreadsheet tool was presented with the contents of such basic education in data science. As a tool for data collection, processing, and analysis, unlike Python, spreadsheets do not have the burden of learning program- ming languages and data structures, and have the advantage of visually learning theories of processing and anal- ysis of qualitative and quantitative data. As a result of this educational case study, three predictive hypothesis test cases were presented and analyzed. First, quantitative public data were collected to verify the hypothesis of predicting the difference in the mean value for each group of the population. Second, by collecting qualitative public data, the hypothesis of predicting the association within the qualitative data of the population was verified. Third, by collecting quantitative public data, the regression prediction model was verified according to the hypothesis of correlation prediction within the quantitative data of the population. And through the satisfaction analysis of pre-service and field teachers, the effectiveness of this education case in data science education was analyzed.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.243-255
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• 2021

The purpose of this study is to investigate the effect of software education based on physical computing on the CT ability of elementary school students. To this end, previous studies related to physical computing software education and software education in the 2015 revised curriculum were analyzed. In addition, COBL was selected among many physical computing tools on the market in consideration of the level and characteristics of learners in the school to conduct the study, and 'Professor Lee Jae-ho's AI Maker Coding with COBL' was used as the textbook. This study was conducted for 10 sessions on 135 students in 6 classes in 6th grade of H Elementary School located in Pyeongtaek, Gyeong gi-do. The results of this study are as follows. First, it was confirmed that physical computing software education linked to real life was effective in improving the CT ability of elementary school students. Second, the change in competency of CT ability by sector improved evenly from 8 to 30 points in the pre-score and post-score of computing thinking ability. Third, in this study, it was confirmed that 87% of students were very positive as a result of a survey of satisfaction with classes after real-life physical computing software education. We hope that follow-up studies will help select various regions across cities and rural areas, and prove that real-life physical computing software education for various learner members, including large and small schools, will help elementary school students improve their CT ability.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.574-581
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• 2024

This study explores the usability of extended reality (XR) content tailored for production process training, with a focus on user experience. Participants engaged with extended reality training modules, and qualitative data was subsequently collected through interviews. These interviews evaluated the hardware, user interface, and overall user satisfaction. The analysis utilized python packages for keyword extraction and word cloud visualization, offering insights into user perceptions. The findings revealed that although the hardware was deemed comfortable, concerns were raised regarding its weight and heat emission. The interactive interface, which relies on hand tracking, encountered issues with recognition rates, leading to suggestions for alternative input methods. Users acknowledged extended reality's potential impact on industries like healthcare and education, sharing both positive and negative views on the technology. This research enhances our understanding of user responses and guides the future enhancement of extended reality content for industrial applications, aiming to improve its quality and practical usability

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.9-16
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• 2023

In the IoT environment, various objects mutually interactive, and various services can be composed based on this environment. In the previous study, we have developed a resource collaboration system to provide services by substituting limited resources in the user's personal device using resource collaboration. However, in the preceding system, when the number of resources and situations increases, the inference time increases exponentially. To solve this problem, this study proposes a method of classifying users and resources by applying the BIG5 user type classification model. In this paper, we propose a method to reduce the inference time by filtering the user's preferred resources through BIG5 type-based preprocessing and using the filtered resources as an input to the recommendation system. We implement the proposed method as a prototype system and show the validation of our approach through performance and user satisfaction evaluation.