• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.273-285
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• 2024

With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.49-63
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• 2024

Objective : The purpose of this study was to investigate parental perspectives on cognitive rehabilitation using a combination of phenomenological research methodology and word cloud analysis. Methods : Interviews were conducted with five parents of children with developmental disabilities. Word cloud analysis was conducted using Python, and five researchers analyzed the meaning units and themes using phenomenological methods. Words with high frequency were considered as a heuristic tool. Results : A total of 43 meaning units and nine components related to the phenomenon of cognitive rehabilitation were derived, and three themes were finalized. The main themes encompassed the definition of cognitive rehabilitation, challenges associated with cognitive rehabilitation, and factors influencing the selection of a cognitive rehabilitation institute. Cognitive rehabilitation emerged as a treatment focused on improving learning, daily functioning, and cognitive abilities in children with developmental disabilities. The perceived issues with cognitive rehabilitation pertained to treatment methods, therapist expertise, and associated costs. In addition, parents highlighted the importance of therapist expertise, humane personality, and affordability of cost and schedule when choosing a cognitive rehabilitation institute. Conclusion : Parents expressed expectations for substantial improvements in their children's daily functioning through cognitive rehabilitation. However, challenges were identified in clinical practices. Going forward, we expect that cognitive rehabilitation will evolve into a better therapeutic support service addressing the concerns raised by parents.

• The Mathematical Education
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• v.63 no.1
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• pp.1-18
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• 2024

This study aims to analyze low-performing high school students' difficulties in constructed response (CR) mathematics assessments and explore ways to use writing activities to support student learning. The participants took CR assessments, engaged in guided writing activities across 15 lessons, and provided responses to our interviews. The study identified 20 types of student difficulties, which were sorted into two main categories: "mathematical difficulties" and "CR difficulties." The difficult nature of mathematics as a school subject included a lack of understanding of mathematical concepts, students' difficulty with mathematical symbols and notations, and struggles with word problems. Challenges specific to CR assessments included students' difficulties arising from the testing conditions unlike those of multiple-choice items, and included issues related to constructing appropriate responses and psychological barriers. To address these challenges in CR assessments, the study conducted guided writing activities as an intervention, through which six themes were identified: (1) internalization of mathematical concepts, (2) mathematical thinking through relational understanding, (3) diverse problem-solving methods, (4) use of mathematical symbols, (5) reflective thinking, and (6) strategies to overcome psychological barriers.

• Information Systems Review
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• v.21 no.4
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• pp.125-141
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• 2019

With the advent of deep learning technology, which is represented by AlphaGo, artificial intelligence (A.I.) has quickly emerged as a key theme of digital transformation to secure competitive advantage for businesses. In order to understand the trends of A.I. based digital transformation, a clear comprehension of the A.I. business ecosystem should precede. Therefore, this study analyzed the A.I. business ecosystem from the multi-actor network perspective and identified the A.I. platform strategy type. Within internal three layers of A.I. business ecosystem (infrastructure & hardware, software & application, service & data layers), this study identified four types of A.I. platform strategy (Tech. vertical × Biz. horizontal, Tech. vertical × Biz. vertical, Tech. horizontal × Biz. horizontal, Tech. horizontal × Biz. vertical). Then, outside of A.I. platform, this study presented five actors (users, investors, policy makers, consortiums & innovators, CSOs/NGOs) and their roles to support sustainable A.I. business ecosystem in symbiosis with human. This study identified A.I. business ecosystem framework and platform strategy type. The roles of government and academia to create a sustainable A.I. business ecosystem were also suggested. These results will help to find proper strategy direction of A.I. business ecosystem and digital transformation.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of The Korean Association For Science Education
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• v.32 no.1
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• pp.30-45
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• 2012

Educational communities around the world have concentrated on integrative efforts among science, technology, engineering and mathematics (Science, Technology, Engineering, and Mathematics: STEM) subjects. Korea has focused on integrative education among STEAM (Science, Technology, Engineering, Arts, and Mathematics) school subjects to raise talented human resources in the fields of science and technology. The purpose of this study was to analyze secondary school science, technology, and mathematics teacher's perceptions and needs toward integrated education and integrative STEM education. A total of 251 secondary school teachers from all areas of the country who have taught science, mathematics, and technology were surveyed by using a self-reported instrument. The findings were as follows: First, teachers have used little integrated education in their classes due to insufficient time in the actual preparation of the integrated education and the lack of expertise, teaching experience, and teaching-learning materials for the integrated education, while they have positive thoughts about the need of integrated education. Second, they presented several needs to facilitate the integrated education: development of a variety of integrated programs, school administrative and financial support, and in-service teachers' training. Third, overall perception toward integrated STEM education was not sufficient, but most teachers perceived the need toward integrated STEM education due to students' development in their creativity, thinking skills, and adaptability. Fourth, they perceived that it was imperative to develop the various integrated STEM education programs, distribute the materials, and help STEM teachers' understanding toward integrated STEM education. Fifth, they perceived that the most relevant method to integrate STEM subjects was the problem solving approach. In addition, they appreciate that the integrated STEM education is highly efficient in not only developing integrated problem solving skills and STEM related literacy, but also in positively impacting the rise of talented human resources in the fields of science and technology. In order to increase the awareness of STEM-related secondary school teachers and vitalize the integrated STEM education, it is necessary to develop and spread a variety of programs, effective teaching and learning materials, and teachers' training programs.

• Clinical and Experimental Pediatrics
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• v.52 no.7
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• pp.824-831
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• 2009

Purpose : We aimed to investigate the efficacy of and functional recovery after intracerebral transplantation of different doses of mouse mesenchymal stem cells (mMSCs) in immature rat brain with hypoxic-ischemic encephalopathy (HIE). Methods : Postnatal 7-days-old Sprague-Dawley rats, which had undergone unilateral HI operation, were given stereotaxic intracerebral injections of either vehicle or mMSCs and then tested for locomotory activity in the 2nd, 4th, 6th, and 8th week of the stem cell injection. In the 8th week, Morris water maze test was performed to evaluate the learning and memory dysfunction for a week. Results : In the open field test, no differences were observed in the total distance/the total duration (F=0.412, P=0.745) among the 4 study groups. In the invisible-platform Morris water maze test, significant differences were observed in escape latency (F=380.319, P<0.01) among the 4 groups. The escape latency in the control group significantly differed from that in the high-dose mMSC and/or sham group on training days 2-5 (Scheffe's test, P<0.05) and became prominent with time progression (F=6.034, P<0.01). In spatial probe trial and visible-platform Morris water maze test, no significant improvement was observed in the rats that had undergone transplantation. Conclusion : Although the rats that received a high dose of mMSCs showed significant recovery in the learning-related behavioral test only, our data support that mMSCs may be used as a valuable source to improve outcome in HIE. Further study is necessary to identify the optimal dose that shows maximal efficacy for HIE treatment.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Journal of Korean Home Economics Education Association
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• v.19 no.2
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• pp.61-75
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• 2007

The method used in this descriptive study is the survey. The purpose of the study is to investigate performances of middle school home economics(HE) teachers regarding the HE subject. Respondents in this study were 177 HE teachers. Questionnaires from HE teachers were collected through e-mails. With the operation of the SPSS/Win (ver10.1) program, the analyses such as mean, standard deviation, frequencies, percents, t-test and ANOVA are done to see the relations between the related variables. The results of this study were as follows. First, the middle school HE teachers performed well above the standards in terms of planning, execution, and evaluation about self supervision related to HE. Second, the HE teachers collected materials for instruction by using literary (books) survey, Internet and mass media. They mainly focused on improving ways of "teaching and learning" and deepening the studies related to contents of textbooks. Third, the HE teachers used various ways to improve self supervision in the following order: mass media, literary (books) survey, participation in societies for researches, meetings, various training and field trip More than half of the middle school HE teachers proceeded to graduate schools, joined meetings for researches and had experiences of taking classes in private institutes. They also made a field trip once or twice a year and depended much on TV programs and education broadcasting programs as ways of improving their performances related to self supervision. While they were actively sharing information with their peer group, they made little effort at analyzing and evaluating their classes and utilizing expert group for their classes. The main problems as to self supervision were that only the half of the HE teachers responded that they were performing self supervision related to their classes well above the standards and the area where they heavily focused on has been "teaching and learning" and "the studies related to contents of textbooks". Therefore, to motivate incentives of the HE teachers for self supervision, meetings for researches should be activated and various training programs should be developed. In addition, government should give administrative and institutional support through a publication of books introducing detailed ways of self supervision and an establishment of centers and institutions for supporting self supervision.

• Journal of Korean Home Economics Education Association
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• v.30 no.1
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• pp.15-28
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• 2018

Teachers are not completed by appointment, but gradually made through self-development and training for a long time. In order to improve a sense of responsibility of home economics teachers, and also to suggest the purpose and direction of program through job training, the needs of training subjects should be preferentially understood. Thus, this study aims to provide basic data for establishing the developmental operation measures of training for home economics teachers, by researching the needs for training performed after the qualification training for first-grade teachers, targeting the teachers participating in the qualification training program for first-grade teachers of home economics in 2017. About the half of the research subjects received the home economics training one time or less for last three years. Through the training for first-grade teachers, the technical improvement of lesson instruction was demanded the most. As professional qualifications that should be cultivated through training, the ability to develop teaching methods and teaching/learning materials was the highest. Regarding the theme of training, the development of teaching/learning materials for home economics was desired the most. They wanted the training method including direct participation with high utilization for lesson, sublation of competition-centered evaluation, preference of instructors with field experience, continuous opportunity of home economics training, and communicative training. Regarding the needs for the 2015 revised curriculum, the demand for the training of 'human development and family' area was the highest. Therefore, in order to improve the professionalism of teachers through home economics training, it would be necessary to improve the educational environment such as temporal room for training and administrative support, and also to provide diverse types of training like group training, remote training, and smartphone app training suitable for changes in the generation of teachers. Also, on top of forming communities of home economics teachers, and sharing great contents of training, there should be individually-customized training for practice and sharing lesson cases.