• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.55-65
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• 2022

As Internet and mobile technology is developing, the educational environment is changing from the traditional passive way into an active one driven by learners. It is important to construct the proper learner's profile for personalized education where learners are able to study according to their learning levels. The existing studies on ICT-based personalized education have mostly focused on vocabulary and learning contents. In this paper, learning profile is constructed with not only vocabulary but grammar to define a learner's learning status in more detailed way. A proficiency metric is defined which shows how a learner is accustomed to the learning contents. The simulational results present the suggested approach is effective to the evaluation essay data with each learner's proficiency that is determined after pre-learning process. Additionally, the proposed analysis technique enables to provide statistics or graphs of the learner's status and necessary data for the learner's learning contents.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.227-233
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• 2016

Typical Web-based learning system is operating the variety of learning contents. However, it is not easy to efficiently select appropriate learning contents. In this paper, we propose a learning content delivery method that can provide the most suitable preferences and feedback to the learner. By analyzing the profile of the learner, it determines the positive feedback and evaluation to be provided to the learner. The result of applying learning techniques were applied to provide the best learning content to adaptively out the form. The proposed method appears as a learning experience and learning outcomes are higher after a study was conducted to suggest that could help in the learning progress of the students themselves. This paper are applied to real learners. And the learners using the system were surveyed by the questionnaire on learning experience and learning outcomes were analyzed.

• The Journal of Korean Association of Computer Education
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• v.5 no.1
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• pp.85-98
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• 2002

In this study, We are developed learner traits analysis and profile management software modules to develop learnable courseware fits to learner's individual traits in cyber learning system. We specified learner's personal information, performance information, preference information and portfolio information as learner's traits variables in this study, these four types of information are managed in learner profile management DB based on elaborate analysis to learner's traits. And we consists of curriculum sequencing module using high and low level sequencing technology, these are used in organizing learning contents sequencing with learning topic and specific learning task. The advice algorithm module developed based on adaptive navigational support and rule based technology. This Result of Research are able to be used for develop learnable courseware fits to learner's individual traits in cyber learning systems.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.477-485
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• 2010

Web based learning systems are operating with various and lots of learning contents. But it is hard to construct learning contents to fit learners when they select learning contents for learning. In this paper, we proposed the recommendation method that can support the learning contents as calculate learner's preference using the learning history information of learner's profile when learner design and compose learning course. In the applying result of this method, we've selected testing learner group and was able to know it can help to learner processing learning by themselves as we've got great learning satisfaction after test.

• Research in Mathematical Education
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• v.26 no.3
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• pp.235-252
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• 2023

We investigated the classification of learner groups for students' mathematical modeling competency and analyzed the characteristics in each profile group for each country and variable using PISA 2012 data from six countries. With a perspective on measuring sub-competency, we applied the latent profile analysis method to student achievement for mathematical modeling variables - Formulate, Employ, Interpret. The findings showed the presence of 4-6 profile groups, with the variables exhibiting high and low achievement within each profile group varying by country, and a hierarchical structure was observed in the profile group distribution in all countries, interestingly, the Formulate variable showed the largest difference between high-achieving and low-achieving profile groups. These results have significant implications. Comparison by country, variable, and profile group can provide valuable insights into understanding the various characteristics of students' mathematical modeling competency. The Formulate variable could serve as the most suitable predictor of a student's profile group and the score range of other variables. We suggest further studies to gain more detailed insights into mathematical modeling competency with different cultural contexts.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.193-202
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• 2004

In this paper, we studied about method that instructor and learner execute teaching-learning activities and about the educational effects of a web based practice instruction. And, in practice instruction, we examined about role and influence of instructor, learner and manager. This study shows the method that instructor and learner execute teaching-learning activities and interaction activities in a "construction of e-business system" curriculum to support the informational education for an industrial workers. The research subject was the 15 industrial workers who enrolled a informational instruction coulee provided for two weeks by kimpo college, As a research method, workers survey, interview, and profile analysis were used for this study. The result of this study show that interaction between instructor, learner and manager was not executed actively, but the manner of lecturing about interest of learner, usage of email, question and answer of bulletin board, online-practice were brought an effect on interaction of learner activities and the educational effects.l effects.

• The Mathematical Education
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• v.61 no.4
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• pp.613-629
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• 2022

This study explored the heterogeneous latent group on the influence of the learner's perceived math teaching method(instructor-centered, learner-centered) on math self-efficacy. In order to profile the characteristics of the detected latent group, the distribution of variables was confirmed, and multi-group analysis was conducted by SEM. According to the analysis results, two latent groups were detected, and the instructor-type group and the learner-type group were named. As a result of post-hoc analysis, the perception of instructor-centered classes and learner-centered classes, and the perception of math teaching ability were similar between the instructor-type and the learner-type group. But the instructor-type group had higher math self-efficacy, math interest, and math class engagement than the learner-type group. Also, in the instructor-type group, the effect of perception of math teaching ability on math self-efficacy and math class engagement was greater than that of the learner-type group. Whereas, in the learner-type group, the effect of math interest on math self-efficacy and math class engagement was greater than that of the instructor-type group. This study presented a new research method on the influence of math teaching methods on learners by applying the REBUS-PLS method.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.467-473
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• 2014

Adaptive learning system means a system that provides adaptively learning materials according to the learning needs of learners. It consists of expert model, instructional model and student model. Expert model is that stores information which is to be taught. Student model stores the data of learning history and learning information of students. Instructional model provides necessary learning materials for actual leaners. This paper has constructed student model through learner's profile information and instructional model through dynamic scenario construction. After that, We have developed adaptively to provide learning to learners by constructing suitable dynamic scenario based on learners profile information. In the end, satisfaction result about this system showed a high degree of satisfaction and 88%.

• Convergence Security Journal
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• v.8 no.4
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• pp.81-89
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• 2008

This paper introduces u-learning service model based on context awareness. Also, it concentrates on agent-based WPAN technology, OSGi based middleware design, and the application mechanism such as context manager/profile manager provided by agents/server. Especially, we'll introduce the meta structure and its management algorithm, which can be updated with learning experience dynamically. So, we can provide learner with personalized profile and dynamic context for seamless learning service. The OSGi middleware is applied to our meta structure as a conceptual infrastructure.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.51-58
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• 2010

Programming education needs learning which is adjusted individual learners' level of their learning abilities. Recommendation system is one way of implementing personalized service. In this research, we propose recommendation method which learning items are recommended for individual learners' learning in web-based programming education environment by. Our proposed system for leveled programming education provides appropriate programming problems for a certain learner in his learning level and learning scope employing collaborative filtering method using learners' profile of their level and correlation profile between learning topics. As a result, it resolves a problem that providing appropriate programming problems in learner's level, and we get a result that improving leaner's programming ability. Furthermore, when we compared our proposed method and original collaborative filtering method, our proposed method provides the ways to solve the scalability which is one of the limitations in recommendation systems by improving recommendation performance and reducing analysis time.