• Journal of Information Technology Services
• /
• v.7 no.4
• /
• pp.231-246
• /
• 2008

This paper suggests an e-learning system model, a goal-driven personalized e-learning system, which increase the effectiveness of learning. An e-learning system following this model makes the learner choose the learning goal. The learner's choice would lead learning. Therefore, the system enables a personalized adaptive learning, which will raise the effectiveness of learning. Moreover, this paper proposes a SCORM standard, which modifies SCORM 2004 that has been insufficient to implement the "goal driven personalized e-learning system." We add a data model representing the goal that motivates learning, and propose a standard for statistics on learning objects usage. We propose each standard for contents model and sequencing information model which are parts of "goal driven personalized e-learning system." We also propose that manifest file should be added for the standard for contents model, and the file which represents the information of hierarchical structure and general learning paths should be added for the standard for sequencing information model. As a result, the system could sequence and search learning objects. We proposed an e-learning system and modified SCORM standards by considering the many factors of adaptive learning. We expect that the system enables us to optimally design personalized e-learning system.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.4
• /
• pp.707-716
• /
• 2004

Recently, many areas of application such as statistics and industrial engineering are interested in the effective education of databases. In this article we design and implement a database learning system based on learner management techniques. The system supports a personalized/ team-centered learning environment, monitoring the learning attitude of learners, and a method for the assessment.

• Fourth Industrial Review
• /
• v.3 no.1
• /
• pp.13-20
• /
• 2023

Purpose - By designing a PEF(Personalized Education Feedback) system for real-time prediction of learning achievement and motivation through real-time EEG analysis of learners, this system provides some modules of a personalized adaptive learning system. By applying these modules to e-learning and offline learning, they motivate learners and improve the quality of learning progress and effective learning outcomes can be achieved for immersive self-directed learning Research design, data, and methodology - EEG data were collected simultaneously as the English test was given to the experimenters, and the correlation between the correct answer result and the EEG data was learned with a machine learning algorithm and the predictive model was evaluated.. Result - In model performance evaluation, both artificial neural networks(ANNs) and support vector machines(SVMs) showed high accuracy of more than 91%. Conclusion - This research provides some modules of personalized adaptive learning systems that can more efficiently complete by designing a PEF system for real-time learning achievement prediction and learning motivation through an adaptive learning system based on real-time EEG analysis of learners. The implication of this initial research is to verify hypothetical situations for the development of an adaptive learning system through EEG analysis-based learning achievement prediction.

• Journal of Industrial Convergence
• /
• v.22 no.2
• /
• pp.13-22
• /
• 2024

In the current epoch of educational technology (EdTech), the realization of a personalized learning system has become increasingly important. This is due to the growing diversity of today's learners in terms of backgrounds, learning styles, and abilities. Traditional educational methods that deliver the same content to all learners often fail to take this diversity into account. This paper identifies models that comprehensively analyze learners' characteristics, interests, and learning histories to meet the growing demand for learner-centered education. Based on these models, we have designed a personalized learning system. This system is structured to support autonomous learning tailored to the learner's current level and goals by identifying strengths and weaknesses based on the learner's learning history. In addition, the system is designed to extend necessary learning elements without changing its architecture. Through this research, we can identify the essential foundations for constructing a user-tailored learning system and effectively develop a system architecture to support personalized learning.

• The Journal of the Korea Contents Association
• /
• v.4 no.1
• /
• pp.8-17
• /
• 2004

In this paper, we design an intelligent loaming management logics which provide personalized teaming considering adaptive learning content dement and content sequencing. We enhance the existing functional model including adaptive learning management functions. Also, we present a system architecture to implement the adaptive learning management system. We realize the adaptive teaming management system based on the SCORM run-time engine.

• The Journal of Korean Association of Computer Education
• /
• v.8 no.4
• /
• pp.49-56
• /
• 2005

Because e-learning system does not have any dynamic contents-delivery mechanism, all students in the same class get identical contents. In this paper, we introduce a personalized learning system, which is carefully designed and implemented based on data stream technology. The proposed system have a mechanism and interface changing lecture contents based on learner's level and ability. The system consists of a dynamic contents-delivery mechanism and learner level-test system. In this paper, we describe what are points to be considered when design and implementing a personalized learning system.

• The Journal of Korean Association of Computer Education
• /
• v.12 no.3
• /
• pp.41-51
• /
• 2009

In this thesis, we suggested an e-learning model, which is named 'goal driven personalized e-learning system' to improve educational effects, and implemented it. The system makes the learner choose the learning goal which could be a motivational power for learning, so it enabled self-directed learning. In order to implement the system, we proposed new standards related to personalization by modifying SCORM 2004 standard. New standards stand for the statistics on learning objects usage, a goal for driving learning. and information of the contents model and the sequencing information model, which are parts of the system previously suggested. We implemented the system, and then proved that personalize e-learning is possible by showing that the system could offer a learning path individually to learners who have different characteristics.

• Information Systems Review
• /
• v.6 no.2
• /
• pp.161-179
• /
• 2004

The purpose of this study is to suggest practical experience to develop small sized e-Learning system. The system is designed to help lecturers can arrange interface, organize contents, submit examinations and assess learner's score with no professional computing skills. The system has three advantages. First, it reduced implementation period through the use of GUI. Second, it is ordered to be personalized to construct format of the whole interface. Third, it has operational convenience which can be implemented on PC based system. These personalized features are enabling Learning on Demand. Also, there is comparatively low cost and high effectiveness on e-Learning implementation which facilitating quick adoption of e-Learning in its lectures.

• Journal of The Korean Association of Information Education
• /
• v.14 no.1
• /
• pp.99-110
• /
• 2010

In order to adapt learners' individual differences in learning ability, individual learning and level-learning have been recommended. However, instructing each student accordingly is not easy issue. In this paper, an online learning support system based on Keller's Personalized System of Instruction theory is developed. As a class-based system, it supports teachers and students to conveniently conduct frequent formative evaluations. It enables students to study at their own learning pace and to reach their learning goals. And it adopts point system and level system to induce self-directed participation. Our implementation results confirm teachers can conduct formative evaluations efficiently.

• Journal of the Korea Convergence Society
• /
• v.11 no.3
• /
• pp.67-75
• /
• 2020

The 'level of difficulty' is one of the major factors for learners when selecting learning contents. However, the criteria for the difficulty level is mostly defined by the contents providers. This approach does not support the personalized education which should consider the abilities and environments of various learners. In this research, the knowledge of the learners and contents were formalized and generalized to resolve the issue, and object models, including a metric for personalized difficulty level, were designed in order to be applied for experiments. And then, based on 100 contents for music education and 20 learners, we performed simulations with an implemented tool to validate our approach. The experimental results showed that our method can calculate the personalized difficulty levels considering the similarities between the knowledges from the learning state and the contents. Our approach can be effectively applied to the on-line learning management system which contains easy access to the learning state and contents data.