• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.199-206
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• 2014

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity.

• Journal of Educational Research in Mathematics
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• v.12 no.1
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• pp.109-124
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• 2002

This study investigated various effects of WBD(web-based discussion) on mathematical communication, interaction and problem solving in the classroom. We developed a web site including BBS and chat room in order to encourage students' mathematical curiosities and self-studies. The web site had been operated for 6 months. Five classes of 1st grade students were selected from an middle school in Daejon. Moreover, we analyzed several cases for interactional behavior and effect. WBD promote dialogue between a teacher and students. Analysis of feed-back from BBS revealed that student's negative attitudes could be changed to positive ones by step-by-step discussions. Moreover, collaborative learning is enhanced by on-line discussion. But the effects of WBD are affected by the character and ability of a student.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.446-465
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• 2015

In this modern era of technology and information, e-learning approach has become an integral part of teaching and learning using modern technologies. There are different variations or classification of e-learning approaches. One of notable approaches is Personal Learning Environment (PLE). In a PLE system, the contents are presented to the user in a personalized manner (according to the user's needs and wants). The problem arises when a new user enters the system, and due to the lack of information about the new user's needs and wants, the system fails to recommend him/her the personalized e-learning contents accurately. This phenomenon is known as cold-start problem. In order to address this issue, existing researches propose different approaches for recommendation such as preference profile, user ratings and tagging recommendations. In this research paper, the implementation of a novel interaction-based approach is presented. The interaction-based approach improves the recommendation accuracy for the new-user cold-start problem by integrating preferences profile and tagging recommendation and utilizing the interaction among users and system. This research work takes leverage of the interaction of a new user with the PLE system and generates recommendation for the new user, both implicitly and explicitly, thus solving new-user cold-start problem. The result shows the improvement of 31.57% in Precision, 18.29% in Recall and 8.8% in F1-measure.

• Journal of Elementary Mathematics Education in Korea
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• v.22 no.2
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• pp.143-159
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• 2018

Since the mathematics learning achievement level is closely related to problem-solving ability, it is necessary to understand the relationship between problem-solving ability and meta-affect ability from the point of view of general mathematics learning ability. In this study, we compared the frequency analysis and the case analysis of the functional aspects of the meta-affect in elementary school students' problem-solving processes according to mathematics learning achievement level in parallel with frequency analysis and case analysis. In other words, the frequency of occurrence of meta-affect, the frequency of meta-affective type, and the frequency of meta-functional types of meta-affect were compared and analyzed according to the mathematics learning achievement level in the collaborative problem-solving activities of small group members with similar mathematics learning achievement level. In addition, we analyzed the representative cases of meta-affect by meta-functional types according to the mathematics learning achievement level in detail. As a result, meta-affect in problem-solving processes of the upper level group acted as relatively various types of meta-functions compared to the lower level group. And, the lower level group, the more affective factors acted in the problem-solving processes.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1672-1683
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• 2004

Recommender system is a kind of web intelligence techniques to make a daily information filtering for people. Researchers have developed collaborative recommenders (social recommenders), content-based recommenders, and some hybrid systems. In this paper, we introduce a new hybrid recommender method - ICHM where clustering techniques have been applied to the item-based collaborative filtering framework. It provides a way to integrate the content information into the collaborative filtering, which contributes to not only reducing the sparsity of data set but also solving the cold start problem. Extensive experiments have been conducted on MovieLense data to analyze the characteristics of our technique. The results show that our approach contributes to the improvement of prediction quality of the item-based collaborative filtering, especially for the cold start problem.

• Journal of the Korean Institute of Educational Facilities
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• v.19 no.2
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• pp.59-66
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• 2012

Community design education has covered the worldview dimension of the collaborative courses for sustainability draws on the architectural expertise developed in a network of community projects and therefore case studies of design education by the collaborative project-based learning in terms of participants, students, teachers and architects, such as 'Learning By Design' for the K-12 comprehensive program in Massachusetts addresses how a local society can make its community sustainable by both design and education. To understand that community design and education can provide professional development in all levels of skills and knowledge across disciplines and opportunities for collaborative learning and problem-solving, this research consists of case studies of the community design education including social systems that assist in organizing the local educational program as well as promoting the programs with public awareness of the community. It covers the UNESCO-UIA agenda of the community design and education that is to enhance the physical environment relating to human interaction by developing innovative alternatives of existing community and contributing voluntarily to neighborhoods through design. As the community design collaborative of design professionals and users is a structural approach to assess design quality, the cases address how to set up the architectural program in order to share pro bono design service and provide high-quality design resources available for sustainable environment.

• 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.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.547-556
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• 2005

Online collaborative teaming, which has emerged as a new type of education in knowledge-based society, is being discussed actively in the areas of action learning at companies and project-based learning and inquiry-based learning at schools. It regards as an effective method for improving learners practical and highly advanced problem solving abilities, and for stimulating their absorption into learning through pursuing common goals of learning together. Different from individual learning, however, collaborative learning involves complicated processes such as organizing teams, setting common goals, performing tasks and evaluating the outcome of team activities .Thus, it is difficult for a teacher to promote and evaluate the whole process of collaborative learning, and it is necessary to develop systems to support collaborative learning. Therefore, in order to monitor and promote interaction among learners in the process of collaborative learning, the present study developed an extensible collaborative teaming supporting agent (ECOLA) in online learning environments.

• Journal of the Korean Chemical Society
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• v.65 no.2
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• pp.151-165
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• 2021

The study applied chemistry classes based on Collaborative Problem-Solving for Competency(CoProC) Instruction Model to 86 high school seniors and recognized the resulting changes in Character Competence through character competence test, analysis of argumentation, and analysis of reflective writing. In addition, the analysis of the correlation between the assessment results showed what each evaluation method meant to assess Character Competence. The study found that the average score of Character Competence rose in all three assessments, but differences were found in the detailed factors. Character competency test is meaningful in helping students participate with a sense of mastery of learning as a self-evaluation, and the analysis of the argumentation process seems to be an appropriate evaluation method to evaluate the Character Competence shown by students' words and actions through course evaluations. An analysis of reflective writing showed the advantage of being able to analyze Character competencies that are difficult to show in action by looking back on the entire course of learning. In addition, given that the correlation between the three assessment results is very low, it is expected that the three Character competency assessment methods will be conducted together to obtain detailed and comprehensive information on students' character competencies.

• Journal of the Korean Chemical Society
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• v.65 no.6
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• pp.468-483
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• 2021

The purpose of this research was to analyze the impact of Collaborative Problem solving for Character competency (CoProC) applied science classes on the character competence and scientific affective characteristics of vocational high school students. To achieve this, two junior classes of chemical industry majors in a vocational high school, were selected as the experimental group with 43 participants, and character competence test, scientific affective characteristic test, group discussion voice recordings, reflection activity sheets were analyzed. Based on the results of the study, the experimental group showed a statistically significant differences in value for the total character competence test score compared to the control group, and it had statistically significant differences in the nine lower character competence factors. Based on the results of the scientific affective characteristic test result, the experimental group was higher in total score to a statistically significant degree compared to the control group, and showed a statistically significant difference in seven of the lower factors, excluding consistency in interest. Therefore, science classes with CoProC applied were effective in cultivating the character competence and enhancing the scientific affective characteristics of vocational high school students.