• The Journal of Korean Association of Computer Education
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• v.14 no.5
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• pp.81-96
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• 2011

With the popularity of smart phones for mobile learning on the rise, cyber universities in Korea are trying to build a reliable mobile campus infrastructure. Such advances in smart phone technologies have made it increasingly easy for users to stay connected and this heightened interaction through smart phones has educational potential for collaborative learning. Thus, to fulfill its educational potential and ultimately provide optimal learning environments on the smart phones, this study has developed a discussion-based interface prototype for collaborative learning. The proposed interface design was evaluated through cognitive walkthrough of the expert reviewers and its usability improvements were also offered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.483-503
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• 2014

In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.

• The Journal of Korean Association of Computer Education
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• v.4 no.1
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• pp.43-52
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• 2001

The aim of this paper is to develop a network-based collaborative learning system based on cooperative learning, computer simulation, role playing, and web-based instruction, which is called NetClass. It is an educational system of hybrid-type, and supports three learning modes as a distributed network, a stand-alone system, or a web browser. To accomplish the purpose of this paper, we have studied on the following topics. First, we selected appropriate learning contents among dilemmas on information ethics. Second, a Collaborative Dilemma-solving Learning Model (CDLM) was designed, and this model means systematic procedures that leaners can notice others' feeling and thinking and predict the results of his actions by introducing interactions among learners on computer networks. Third, Collaborative Learning System Model based on standard architecture of an educational system was proposed. Fourth, we developed many components such as network components, database components, and interface components.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.173-178
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• 2022

Recently, a recommendation system using deep learning in social network services has been actively studied. However, in the case of a recommendation system using deep learning, the cold start problem and the increased learning time due to the complex computation exist as the disadvantage. In this paper, the user-tailored exercise routine recommendation algorithm is proposed using the user's metadata. Metadata (the user's height, weight, sex, etc.) set as the input of the model is applied to the designed model in the proposed algorithms. The exercise recommendation system model proposed in this paper is designed based on the neural collaborative filtering (NCF) algorithm using multi-layer perceptron and matrix factorization algorithm. The learning proceeds with proposed model by receiving user metadata and exercise information. The model where learning is completed provides recommendation score to the user when a specific exercise is set as the input of the model. As a result of the experiment, the proposed exercise recommendation system model showed 10% improvement in recommended performance and 50% reduction in learning time compared to the existing NCF model.

• Journal of The Korean Society of Integrative Medicine
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• v.11 no.1
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• pp.71-78
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• 2023

Purpose : This study was purposed to analyze the effectiveness of PBL (Problem-Based Learning) classes and to derive class improvement plans. Methods : The subjects of the study were 48 students who took the 4th grade clinical dental hygiene course at S University located in Chungcheongnam-do of South Korea in 2021. A single-group pre and post experimental study was designed to verify whether there were significant changes in the research variables of students who participated in the class to which problem-based learning was applied. A paired-sample t-test was conducted for the collected data of 46 respondents. Results : As a result, the degree of improvement in problem clarification, cause analysis, and alternative development among the five sub-areas of problem-solving ability was statistically significant. This means that the problem-based learning class positively affects dental hygiene major students' ability to clarify problems, the ability to analyze causes to collect and analyze information, and the ability to develop alternatives to make decisions, thereby improving overall problem-solving abilities. However, the improved post-score was not statistically significant in the planning/execution and performance evaluation of the remaining two subdomains. In addition, post-scores of the leader aspect, opinion exchange, opinion evaluation, and opinion integration, which are sub-domains of collaborative self-efficacy, all showed great statistical significance. Problem-based learning improved the collaborative efficacy of dental hygiene major students overall by positively influencing the ability to lead a team, exchange and evaluate each other's views, and constructively integrate different views. Conclusion : It was found that both the subject's problem-solving ability and cooperation efficiency improved under the influence of problem-based learning. On the other hand, implications for improvement of the future class such as the necessity of supplementing strategies to promote planning and execution ability for problem solving, and ability to evaluate problem solving performance was suggested.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.732-737
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• 2008

As e-learning is recognized in new education form, Learning Management System that manage general activity of learning to maximize effect of education is being developed actively. Usually, Learning Management System includes course registration and learning as well as learner's learning recording and tracking, evaluation in online. But, most systems is lacking a tool that learners can collaborate with companion learners, and planning learning and set valuation basis as leading. In this paper, we can expect effective collaborative learning activities because can make debate and team project smooth by suggesting collaborative learning module that can drive voluntary participation such as group formation, learning plan, mutually estimation as leading to learner in Learning Management System of blended learning base that support online and offline environment both.

• Journal of The Korean Association of Information Education
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• v.17 no.4
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• pp.497-506
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• 2013

The purpose of this study is to explore and develop a new instructional approach to a technology-enhanced, collaborative learning environment called Smart technology-enhanced Team-Based Learning (S-TBL). We designed a novel instructional model that combines mobile technology, collaborative teamwork, a problem-solving process, and a variety of evaluation techniques from the viewpoint of a conventional team-based model. Based on the traditional TBL model, we have integrated smart learning technologies: 1) to provide a holistic learning environment that integrates learning resources, assessment tools, and problem solving spaces; and 2) to enhance collaboration and communication between team members and between an instructor and his or her students. The S-TBL instructional approach combines: 1) individual learning and collaborative team learning; 2) conceptual learning and problem-solving & critical thinking; 3) both individual and group assessment; 4) self-directed learning and teacher-led instruction; and 5) personal reflection and publication.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.193-215
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• 2014

This study examines undergraduate nursing students' user satisfaction and affective experience of collaborative information behavior in a group-based learning through survey method to see the relationship between these factors. For this purpose, the affective experiences (positive and negative aspects) of collaborative information search were examined using the PANAS scale through the same questionnaire. Correlation between students' experiences of collaborative information search and affective aspects were examined, and statistical significance using the t-test were also conducted to measure the relationship among students' demographic factors, experiences of collaborative information search and affective aspects. The results revealed that there was a significant correlation between experiences of collaborative information search and affective aspects. Also, there were significant relationships among students' demographic factors, experiences of collaborative information search and affective aspects. In particular, there were signigicant differences in students' overall satisfaction of collaboration and positive aspects between male and female students who experienced collaborative information search. This study found out the possibilities for a follow-up study for affective aspects in collaborative information behavior.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.197-211
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• 2004

According to the increase of internet application, the marketing process as well as the research and survey, the education process, and administration of government are very depended on web bases. All kinds of goods and sales which are traded on the internet shopping malls are extremely increased. So, the necessity of automatically intelligent information system is shown, this system manages web site connected users for effective marketing. For the recommendation system which can offer a fit information from numerous web contents to user, we propose an automatic recommendation system which furnish necessary information to connected web user using statistical learning theory and bayesian fuzzy clustering. This system is called collaborative CRM in this paper. The performance of proposed system is compared with the other methods using real data of the existent shopping mall site. This paper shows that the predictive accuracy of the proposed system is improved by comparison with others.

• Educational Technology International
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• v.23 no.1
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• pp.1-39
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• 2022

We study emotion regulation in a distant CABLe (Collaborative Argumentation Based-Learning) setting at university. We analyze how students achieve the group task of synthesizing the literature on a topic through scientific argumentation on the institutional Moodle's forum. Distinguishing anticipatory from reactive emotional regulation shows how essential it is to establish and maintain a constructive working climate in order to make the best out of disagreement both on social and cognitive planes. We operationalize the analysis of anticipatory emotional regulation through an analytical grid applied to the data of two groups of students facing similar disagreement. Thanks to sharp anticipatory regulation, group 1 solved the conflict both on the social and the cognitive plane, while group 2 had to call out for external regulation by the teacher, stuck in a cyclically resurfacing dispute. While the institutional digital environment did afford anticipatory emotional regulation, reactive emotional regulation rather occurred through complementary informal and synchronous communication tools. Based on these qualitative case studies, we draw recommendations for fostering distant CABLe at university.