• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.36-45
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• 2011

An agent in collaborative e-learning has independent function for learners in any circumstance, status and task by the reasonable and general means for social learning. In order to perform it well, communication among agents requires standardized and regular information technology method. This study suggests data model as a communication tool for various agents. Therefore this study shows various agents types for collaborative learning, designation of rule for data model that enable to communicate among agents and data element of agent communication data model. A multi-agent e-learning system using like this standardized data model should able to exchange the message that is needed for communication among agents who can take charge of their independent tasks. This study should contribute to perform collaborative e-learning successfully by the application of communication data model among agents for social learning.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.235-242
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• 2013

Reputation systems aggregate users' feedback after the completion of a transaction and compute the "reputation" of products, services, or providers, which can assist other users in decision-making in the future. With the rapid growth of online e-Learning content providing services, a suitable reputation system for more credible e-Learning content delivery has become important and is essential if educational content providers are to remain competitive. Most existing reputation systems focus on generating ratings only for user reputation; they fail to consider the reputations of products or services(item reputation). However, it is essential for B2C e-Learning services to have a reliable reputation rating mechanism for items since they offer guidance for decision-making by presenting the ranks or ratings of e-Learning content items. To overcome this problem, we propose a novel collaborative filtering based reputation rating method. Collaborative filtering, one of the most successful recommendation methods, can be used to improve a reputation system. In this method, dual information sources are formed with groups of co-oriented users and expert users and to adapt it to the reputation rating mechanism. We have evaluated its performance experimentally by comparing various reputation systems.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.2
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• pp.65-88
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• 2014

This study analyzed cases of collaborative classes between a teacher librarian and Chinese language teacher by applying problem-based learning (PBL) and intended to propose a desirable direction for class in operating collaborative classes of PBL. In order to achieve this purpose, methods to raise problems by BPL at the library of S High School, class content by each round of class, and cases of students' achievements were presented. In addition, statistical analysis of interest in subjects on 101 students in their sophomore year who had participated in PBL class was conducted. According to the study result, students' learning-related desire to accomplish, executive ability of learning, and interest were significantly improved.

• 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 Digital Convergence
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• v.10 no.6
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• pp.33-39
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• 2012

The purpose of this study is to investigate the effect of SNS(Social Network Service) on individual learning performance. To do this, we distribute and collect data by using a survey method. Research results suggest that online social networking engagement and acculturation have an effect on interaction quality with professors. Interaction quality with professors influences individual learning performance as well as collaborative learning. The conclusion and implications are discussed.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.243-248
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• 2018

The most important factor for collaborative learning to be effective is the selection of tools that constitute groups. Grouping is to facilitate collaborative learning, learners form groups based on various characteristics. If a group of students fails to form properly due to the selection of the wrong tools, problems can arise where complaints from students can lead to lectures and the effects of learning. In this paper, we have implemented a group of configuration tools that considered improving learning effects and diagnosing bulling tendency. We have proposed a group composition tool that can take into consideration the learning effect and also diagnose the tendency of the bullring by constructing the group according to the teacher's preference by inputting the class preference and the student's grade through the sociometry survey. We expect that the teacher will be able to grasp the students' friendship in advance and cope with the bulling that can happen in the class, as well as the cooperative learning that can lead the class to improve the learning effect.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.612-615
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• 2007

This research studies the Virtual Reality simulation of Newton's physics law on rigid body type of objects for physics learning. With network support, collaborative interaction is enabled so that people from different places can interact with the same set of objects in Collaborative Virtual Environment. The taxonomy of the interaction in different levels of collaboration is described as: distinct objects and same object, in which there are same object - sequentially, same object - concurrently - same attribute, and same object - concurrently - distinct attributes. The case studies are the interaction of users in two cases: destroying and creating a set of arranged rigid bodies. We identify a specific type of application for contents authoring with modeling systems integrated with real-time physics and implemented in VR system. In our application called Virtual Dollhouse, users can observe physics law while constructing a dollhouse using existing building blocks, under gravity effects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2310-2332
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• 2020

In recent years, deep learning techniques have achieved tremendous successes in natural language processing, speech recognition and image processing. Collaborative filtering(CF) recommendation is one of widely used methods and has significant effects in implementing the new recommendation function, but it also has limitations in dealing with the problem of poor scalability, cold start and data sparsity, etc. Combining the traditional recommendation algorithm with the deep learning model has brought great opportunity for the construction of a new recommender system. In this paper, we propose a novel collaborative recommendation model based on auxiliary stacked denoising autoencoder(ASDAE), the model learns effective the preferences of users from auxiliary information. Firstly, we integrate auxiliary information with rating information. Then, we design a stacked denoising autoencoder based collaborative recommendation model to learn the preferences of users from auxiliary information and rating information. Finally, we conduct comprehensive experiments on three real datasets to compare our proposed model with state-of-the-art methods. Experimental results demonstrate that our proposed model is superior to other recommendation methods.

• Research in Mathematical Education
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• v.26 no.3
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• pp.127-146
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• 2023

Statistical thinking has a broad definition but focuses on the context of regression modelling in the present study. To foster students' statistical thinking within the context, teaching should no longer be seen as transfer of knowledge from teacher to students but as a process of engaging with learning activities in which they develop ownership of knowledge. This study aims at collaborative learning contexts; students were divided into small groups in order to increase opportunities for peer collaboration. Each group of students was asked to do a regression project after class. Through doing the project, they learnt to organize and connect previously accrued piecemeal statistical knowledge in an integrated manner. They could also clarify misunderstandings and solve problems through verbal exchanges among themselves. They gave a clear and lucid account of the model they had built and showed collaborative interactions when presenting their projects in front of class. A survey was conducted to solicit their feedback on how peer collaboration would facilitate learning of statistics. Almost all students found their interaction with their peers productive; they focused on the development of statistical thinking with concerted effort.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.4984-4993
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• 2012

This study was initiated with the need of studies to promote learning and use of collaboration skills that learners should have in collaborative learning in CSCL. The researcher carried out research on 96 students taking the course of 'educational methods and educational technology' in K collage to take a look at the impact of prior training on collaboration in CSCL and interaction of types of collaborative scripts. To answer the first research question, the scores of each group's chatting in collaborative learning process and messages represented in the process of task performance based on collaborative skills were measured and analyzed. In addition, to answer the second research question, the scores of each group's shared mental model formulation based on relevant evaluation standards were analyzed. This study results, First, there was no significant difference in the acquisition of collaboration skills caused by interaction of prior training on collaboration and collaboration skills and collaborative scripts. However, it turned out that types of collaborative scripts give significant impacts on acquisition of collaboration skills. Second, there was also no significant difference between prior training on collaboration and the formulation of shared mental model by the interaction of collaborative scripts. However, it is showed that types of collaborative scripts have significant impacts on the formation of shared mental model.