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

• Korean Journal of Community Nutrition
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• v.18 no.1
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• pp.65-76
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• 2013

The purpose of this study was to investigate the effects of a nutrition education and personalized lunch service program in a senior welfare center. A total of 30 elderly (14 males, 16 females) aged 62~89 years participated in this study. Nutrition education lessons (2 hour/lesson/week) were provided for 4 weeks. Also, ten weeks from week 3rd to week 12th, personalized lunch providing 1/3 personal needed energy was served 5 times for a week. After the nutrition intervention program, we compared anthropometric characteristics, blood biochemical characteristics, nutrition knowledge, dietary attitude and dietary intake using 24 hr recall with those before the intervention. The body weight (p < 0.001) and body mass index (BMI) (p < 0.001) were decreased. There were significant increases in score of nutrition knowledge (p < 0.01) and consumption of milk & milk products for snacks. There was a positive effect on fasting blood sugar (FBS) showing significant decreases in portion of impaired fasting glucose and diabetes mellitus (p < 0.05). Also, serum triglyceride (TG) was significantly decreased (p < 0.05). In evaluation of nutrient intake by Dietary Reference Intakes for Koreans (KDRIs), riboflavin (p < 0.01), vitamin C (p < 0.001), calcium (p < 0.05) were positively improved. The index of nutritional quality (INQ) and intakes of vitamin C (p < 0.001), riboflavin (p < 0.05), Ca (p < 0.01) and Fe (p < 0.05) were increased. In conclusion, this nutrition education and lunch service program providing 1/3 personal needed energy can be used to develop and implement a tailored nutritional intervention programs in the setting of a community senior welfare center to improve health and nutritional status of Korean elderly.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.71-80
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• 2021

Artificial intelligence (AI) will have a huge impact on future education. We look at the role of AI in education and changes in schools. Personalized education is being attempted in limited services, and an interactive tutor service with speech recognition/dialog technology is being developed. In the future, we look forward to fully personalized education for individual students through AI teachers. Teachers are expected to make more effort to teach creative thinking, critical thinking, communication, and collaboration. As the speed of development of AI technology accelerates, we expect that AI-based education will be deeply established around us in the near future. We first introduce the details of the personalization technology and then discuss the AI-based foreign language speaking education research conducted by ETRI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.70-76
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• 2010

In this paper, we propose a personalized Chinese character education system using RankBoost algorithm on a smartphone. In a typical Chinese character education scenario, a trainee is supplied with a finite number of Chinese characters as an input set in the beginning. And, as the training session repeats, the trainee will notice her/his difficult characters in the set which she/he hardly answers. Those characters reflect their personalized degrees of difficulty. Our proposed system constructs these personalized degrees of difficulty using RankBoost algorithm. In the beginning, the algorithm start with the set of Chinese characters, of which each is associated with the same weight values. As the training sessions are repeated, the algorithm increase the weights of Chinese characters that the trainee mistakes, thereby eventually constructs the personalized difficulty degrees of Chinese characters. The proposed algorithm maximizes the educational effects by having the trainee exposed to difficult characters more than easy ones.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.191-201
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• 2023

As Edutech arises which is integrating IT technology into education, many related attempts have been tried on music education area. The focus has been shifted from the teachers to the learners, and this makes the personalized learning emerge. The learner's proficiency is an essential factor to support the personalized learning. The chord fingering is an important technique in piano learning. In this paper, a personalized learning tool for piano chords has been suggested. And then, several utilization ways have been described by analyzing the chords patterns. Specifically, the difficulty of the chords and the proficiency of the learner are derived from the accumulated practicing log data of the users. More effective learning way of the chords has been presented through hierarchical clustering based on chords similarity. Furthermore, the suggested approach where only the practicing log data are used lessens the learner's burden to measure the proficiency and the chord's difficulty without additional efforts like taking tests.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.288-294
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• 2022

The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

• The Mathematical Education
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• v.62 no.3
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• pp.303-326
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• 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 Korean Data and Information Science Society
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• v.15 no.4
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• pp.707-716
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• 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.

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

• Journal of Nutrition and Health
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• v.57 no.1
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• pp.75-87
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• 2024

Purpose: Dietary habits are strongly related to the symptoms of people with irritable bowel syndrome (IBS). Therefore, personalized nutrition management can help reduce symptoms and improve the quality of life of people with IBS. This study assessed the effectiveness of a personalized web-based nutrition management based on the types of food that trigger IBS symptoms. Methods: Sixty Korean adults with IBS according to Rome IV criteria in their 20s and 30s were enrolled in this study. The data from the final 49 patients who completed a three-month personalized nutrition intervention were analyzed. The general information, anthropometry, dietary intake survey, and gut microbiota were examined pre and post-intervention. The gut microbiota analysis included the relative abundance and the Shannon index. The food intake was recorded for two days for personalized nutrition education, followed by three months of personalized nutrition intervention. Statistical analysis was performed using the Wilcoxon signed-rank test in SPSS 26.0, with the significance set to p < 0.05. Results: The relative abundance of the gut microbiota changed after personalized nutrition management, with a significant decrease in the presence of Veillonella (p = 0.048). Furthermore, when the gut microbiota was analyzed according to the type of food that triggers symptoms, the diversity was increased significantly in the high fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) type (p = 0.031) and FODMAPs-containing gluten-type personalized nutrition intervention types (p < 0.001). Conclusions: Gut microbial diversity and gut microbiota distribution changed after using web-based personalized nutrition management. Hence, personalized nutrition management that considers trigger foods may improve IBS symptoms.