• Journal of the Korean Chemical Society
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• v.67 no.4
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• pp.281-295
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• 2023

The purpose of this study was to investigate the effects of role assignment in a group on collaboration in a mid- dle school science class to which Collaborative Problem Solving for Character Competency (CoProC) model was applied. For this purpose, 4 classes in the second year of a middle school located in a small and medium-sized city were selected, two classes among these were assigned roles, and the other classes were not. The science class with 4 topics using CoProC model was carried out. As a result of the study, in middle school science class to which CoProC was applied, it was effective in increasing the collaboration. As a result of analyzing the discussion process using the analysis framework for collaboration developed in this study, the group without role assignment was statistically significantly higher than the group with role assignment in the total score and the four sub-factors, especially in 'partnership building' and 'consensus building' which is a high level of collaboration.

• Journal of Science Education
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• v.44 no.2
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• pp.205-213
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• 2020

The purpose of this study is to investigate the effects of elementary school students' knowledge and information processing competence and collaborative problem-solving ability in scientific inquiry class using data measured with digital inquiry tools. To this end, three classes of 5th grade elementary schools in S-city, Gyeongnam were selected as experimental groups and three classes as control groups. The control group conducted traditional lecture-style classes, and the experimental group conducted scientific inquiry classes using scientific data. The following results were obtained through questionnaires after class. First, science inquiry classes using scientific data helped elementary school students improve their knowledge and information processing competence. Second, scientific inquiry classes using scientific data improved elementary school students' cooperative problem-solving ability. From the above results, it was found that scientific inquiry classes using scientific data are needed to improve the knowledge information processing competence and cooperative problem solving ability of elementary school students. Based on this research, it is necessary to study a specific teaching and learning environment that can activate scientific inquiry class using data measured with digital inquiry tools in the future.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.203-210
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• 2020

Memory-based collaborative filtering is one of the representative types of the recommender system, but it suffers from the inherent problem of data sparsity. Although many works have been devoted to solving this problem, there is still a request for more systematic approaches to the problem. This study exploits distribution of user ratings given to items for computing similarity. All user ratings are utilized in the proposed method, compared to previous ones which use ratings for only common items between users. Moreover, for similarity computation, it takes a global view of ratings for items by reflecting other users' ratings for that item. Performance is evaluated through experiments and compared to that of other relevant methods. The results reveal that the proposed demonstrates superior performance in prediction and rank accuracies. This improvement in prediction accuracy is as high as 2.6 times more than that achieved by the state-of-the-art method over the traditional similarity measures.

• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.9-16
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• 2016

Collaborative filtering(CF) uses the purchase or item rating history of other users, but does not need additional properties or attributes of users and items. Hence CF is known th be the most successful recommendation technology. But conventional CF approach has some significant weakness, such as the new user problem. In this paper, we propose a approach using word embedding with skip-gram for learning distributed item representations. In particular, we show that this approach can be used to capture precise item for solving the "new user problem." The proposed approach has been tested on the Movielens databases. We compare the performance of the user based CF, item based CF and our approach by observing the change of recommendation results according to the different number of item rating information. The experimental results shows the improvement in our approach in measuring the precision applied to new user problem situations.

• Journal of Gifted/Talented Education
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• v.9 no.2
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• pp.153-172
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• 1999

1990년대 이르러 폭발적으로 증가하고 있는 인터넷 사용인구의 증가와 급속한 컴퓨터 응용 기술의 발전은 교육에 있어서 기존의 대면교육을 원격교육으로 대체하게 만드는 원동력이 되었으며, 21세기 국가 경쟁력 향상을 위해 영재교육에 대한 관심이 증대되고 있는 것이 사실이다. 본 논문에서는 멀티미디어와 결합된 원격교육 시스템이 영재교육에 어떻게 응용될 수 있는지를 살펴보고, 기존의 원격교육 시스템 개발방법론과 차이점을 통해 한국과학기술원 과학영재교육센터 원격영재교육 시스템이 가지고 있는 장점에 대해 살펴보도록 한다.

• Asia pacific journal of information systems
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• v.5 no.1
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• pp.219-235
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• 1995

Complexity of some problems often transcends the problem solving capability of human individuals. As such, we cannot but take a collaborative approach to those complex problems. Collaboration while using computing systems can take place through shared objects. However, current commercial DBMSs do not provide a satisfactory control for concurrent access to objects shared by collaborators. A new concurrency control scheme is proposed which will help a group of people work in a more collaborative and natural way. The idea of softlock is refined into three different kinds of softlocks and the roles of collaborators are taken into account in the proposal of the new scheme. Although these softlocks are illustrated together with read/write hardlocks in this paper, the use of softlocks can be extended to be exploited with other kinds of hardlocks, for example, of granularity locking.

• Educational Technology International
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• v.10 no.1
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• pp.137-155
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• 2009

The purpose of this research is to develop Blended-TBL(Team Based Learning) model that emphasizes the active participation and teamwork of students in on-off blended learning environment, and apply it into the college course and explore whether self-regulated learning between one group pretest and posttest is different. For this, this research investigated the concept and the characteristics of Team Based Learning, and developed the Blended-TBL Model to apply it into the college course, and finally prove effects of Blended-TBL model on self-regulated learning using Motivated Strategies for Learning Questionnaire (MSLQ). The participants in this study were 57 college students. They participated in on-off blended-TBL course for 15weeks. Participants followed the content grounded and the problem solving steps in collaborative team-based learning. This research practiced a quantitative research to find out the statistical difference of the self-regulated learning between pretest and posttest using SPSS. The result revealed that Blended-TBL students improved self-regulated learning including motivation, cognitive, metacognitive, and resource management. Based on this result, this research discussed the effects of Blended-TBL on Self-Regulated Learning and suggested the further study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.154-163
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• 2017

Collaborative filtering, one of the most widely used techniques to build recommender systems, is based on the idea that users with similar preferences can help one another find useful items. Credit card user behavior analytics show that most customers hold three or less credit cards without duplicates. This behavior is one of the most influential factors to data sparsity. The 'cold-start' problem caused by data sparsity prevents recommender system from providing recommendation properly in the personalized credit card recommendation scenario. We propose a personalized credit card recommender system to address the cold-start problem, using multiple user profiles. The proposed system consists of a training process and an application process using five user profiles. In the training process, the five user profiles are transformed to five user networks based on the cosine similarity, and an integrated user network is derived by weighted sum of each user network. The application process selects k-nearest neighbors (users) from the integrated user network derived in the training process, and recommends three of the most frequently used credit card by the k-nearest neighbors. In order to demonstrate the performance of the proposed system, we conducted experiments with real credit card user data and calculated the F1 Values. The F1 value of the proposed system was compared with that of the existing recommendation techniques. The results show that the proposed system provides better recommendation than the existing techniques. This paper not only contributes to solving the cold start problem that may occur in the personalized credit card recommendation scenario, but also is expected for financial companies to improve customer satisfactions and increase corporate profits by providing recommendation properly.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.239-250
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• 2003

Recent recommender system user a method of combining collaborative filtering system and content based filtering system in order to slove the problem of the Sparsity and First-Rater in collaborative filtering system. In this paper, to make up for the prediction accuracy in hybrid Recommender system, the harmonic mean weight(CBCF_harmonic_mean) is used for calculating the user similarity weight. After setting up the threshold as 45 considering the performance of content based filtering, we apply significance weight of n/45 to user similarity weight. To estimate the performance of the proposed method, it if compared with that of combing both the existing collaborative filtering system and the content- based filtering system. As a result, it confirms that the suggested method is efficient at improving the prediction accuracy as solving problems of the exiting collaborative filtering system.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.429-436
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• 2017

A design thinking-based collaborative workshop in which various stakeholders in the milk processing industry circulation ecosystem participated shows a new problem innovation paradigm that encourages the spread of practical prototyping culture. in the expression of empathy and collective intelligence among members on facing issues, the conversion of collaboration and communication methods, the business handling of the organization based on the design work method as 'creativity mechanism'. In this workshop, which was promoted in three stages of 'approach to problems', 're-definition of problems', and 'experience-based future vision design', participants themselves redefine real problems in terms of the accuracy of feed orders between feed suppliers and livestock farmers, ordering of feeds on time, cost reduction of feed supply and present new alternatives and expanded business areas. The results suggested in this workshop suggest the usefulness of design thinking in business innovation in that they presented how to approach the problem and a creative thinking system to find its solution to direct and indirect stakeholders of the industry as well as the improvement of supply and demand rate of livestock feed and quality.