• 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.

• The Mathematical Education
• /
• v.62 no.3
• /
• pp.303-326
• /
• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• Journal of the Korea Safety Management & Science
• /
• v.10 no.4
• /
• pp.309-314
• /
• 2008

Many studies on predicting and recommending information and products have been studying to meet customers' preference. Unnecessary information should be removed to satisfy customers' needs in massive information. The some information filtering methods to remove unnecessary information have been suggested but these methods have scarcity and scalability problems. Therefore, this paper explores a personalized recommendation system based on artificial neural network (ANN) to solve these problems. The insurance product recommendation is adapted as an example to demonstrate the proposed method. The proposed recommendation system is expected to recommended a suitable and personalized insurance products for customers' satisfaction.

• Journal of Broadcast Engineering
• /
• v.19 no.5
• /
• pp.631-639
• /
• 2014

Since digital broadcasting service has been begun, user's requirements have been increased for personalized broadcasting system that users can watch the part of programs which they want to watch in anytime. In personalized broadcasting system, metadata is important for searching program information based on user's input data. In this paper, an object-oriented media service metadata management module is implemented. Metadata used in this system is described by extending TV-Anytime specifications which is the International standard for personalized media service. For this, extended segments information is provided including object information which do not existing in previous personalized broadcasting standard. This system can provide better satisfaction to users by using object segmentation information.

• The Journal of the Korea Contents Association
• /
• v.10 no.2
• /
• pp.111-119
• /
• 2010

U-Healthcare provides healthcare and medical services, such as prevention, diagnosis, treatment, and follow-up services whenever and wherever it is needed, and its ultimate goal is to improve quality of life. This study defines the figure of U-Healthcare personalized services for providing U-Healthcare personalized services and proposes a healthcare model. A diet prescription system for personalized services can draw customized calories and rates of nutrition factors and represent a personalized diet through analyzing the personal preference in foods. This system changes the personal preference by monitoring the diet selection behavior of users. Also, this system is designed to be interactively operated with some sensors and devices in various environments using Java-based OSGi middleware.

• 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.

• Asia pacific journal of information systems
• /
• v.14 no.3
• /
• pp.121-144
• /
• 2004

Developing a personalized system on a user's behalf which is working around the Internet-based marketplace is one of the challenging issues in intelligent e-business, especially mobile commenrce. It has been highly recommended that such a mobile personalized system has to perceive the user's needs a priori by tracking user's current context such as location with activity and then to identify the current needs dynamically and proactively. Automatically and unobtrusively getting user's context is an inevitable feature for the development of autonomous mobile commenrce. However, personalization methodologies and their feasible architectures for context-aware mobile commerce have been so far very rare. Hence, this paper aims to propose a context-aware mobile commerce development methodology by applying agent and semantic web technologies for personalized reminder system, which is one of the mobile commerce support system. We revisited associationism to understand a buyer's need identification process and adopt the process as 'purchase based on association' to implement a personalized reminder system. Based on this approach, we have showed how the agent-based semantic web service system can be used to realize need-aware reminder system. NAMA(Need-Aware Multi-Agent), a prototype system, has been implemented to show the feasibility of the methodology and framework under mobile setting proposed in this paper. NAMA embeds bluetooth-based location tracking module and identify what a user is currently looking at through her/his mobile device such as PDA. Based on these capabilities, NAMA considers the context, user profile with preferences, and information about currently available services, to aware user's current needs and then link her/him to a set of services, which are implemented as web services.

• Journal of Digital Contents Society
• /
• v.11 no.3
• /
• pp.357-365
• /
• 2010

Personalized web search engine provides personalized results to users by query expansion, re-ranking or other methods representing user's intention. The personalized result page includes URL, page title and small text fragment of each web document. which is known as snippet. The snippet is the summary of the document which includes the keywords issued by either user or search engine itself. Users can verify the relevancy of the whole document using only the snippet, easily. The document summary (snippet) is an important information which makes users determine whether or not to click the link to the whole document. Hence, if a search engine generates personalized document summaries, it can provide a more satisfactory search results to users. In this paper, we propose a personalized document summary system for personalized web search engines. The proposed system provides increased degree of satisfaction to users with marginal overhead.

• Journal of Broadcast Engineering
• /
• v.9 no.4 s.25
• /
• pp.345-356
• /
• 2004

In this paper, we present a design and implementation of a personalized broadcasting system using TV-Anytime metadata for providing personalized services. The TV-Anytime specifies metadata schema, metadata coding and delivery, and provides service models to provide personalized broadcasting content services at anytime when users want to consume using metadata, which includes ECG (Electronic Content Guide) and content descriptive information in a PDR (Personal Digital Recorder)-centric environment. The proposed personalized broadcasting system consists of a server that provides metadata binary-coding, encapsulation and multiplexing, and a client terminal that takes charge of de-multiplexing, metadata decoding, and metadata processing for personalized content accessing and consumption. This paper presents the details of the design of each functional module, and the evaluation results with a set of service scenarios in an end-to-end broadcasting test-bed.

• 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.