Earticle

대통령기록물은 일반적인 공공기록물과 비교하여 사료적 가치가 높다고 평가되며, 당대의 사회상을 풍부하게 반영한 신뢰성 있는 자료로서 교육 분야에 있어서 그 활용성과 가치가 높다. 이에 본 연구에서는 대통령기록관의 정보기관으로써의 역할 증대와 대통령기록관에 대한 긍정적 인식을 이끌어 낼 수 있도록 G러닝환경에서 대통령기록물을 활용한 모바일 교육 콘텐츠를 개발할 수 있는 방법론을 제안하고자 하였다. 대통령기록물을 활용한 G러닝 모바일 콘텐츠 개발에 대한 방법론 7단계 - 사전계획, 사전 설계, 대통령기록물 선정, 대통령기록물 스토리텔링, 스토리보드 제작, 게임 구현, 공유 및 평가 - 를 먼저 제안한 후, 5학년 학생을 대상으로 한 교육 콘텐츠를 구현 사례로 제시하였다.

Presidential archives have higher historical value than other public documentaries. It is a reliable documentary reflecting aspects of contemporary life and has high value and availability in the education field. This study suggests how to intensify the role as an intelligence service of presidential archives and how to develop the utilized-Presidential Archives mobile education contents in G-learning environments to lead the positive awareness on Presidential archives. After suggesting the 7 levels methods about the development of mobile education contents using presidential archives in G-learning environments, This study shows the case of the applied educational contents on the subject of $5^{th}$ grade at the elementary school. 7 levels methods include pre-planning, pre-design, selecting presidential records, presidential records story-telling, making the storyboard, implementing a game, sharing and assess.

In B5G heterogeneous cellular networks, a rapid increase in the number of small cell base stations (SBSs) to support a massive number of devices tends to waste a considerable amount of energy. Therefore, intelligent management of SBSs’ power consumption is one of the most important research issues. We herein propose quasi-distributed Q-learning-based cell breathing (QD-QCB) considering full and partial SBS collaborations for maximizing network energy efficiency. Also, the concept of an aggregated active SBS set based on regional user distributions is proposed for computing- and energy-efficient operation. Through intensive simulations, we show that the proposed QD-QCB algorithm can achieve optimal energy efficiency, and improve the network energy efficiency significantly compared with conventional algorithms such as no transmit power control, random cell breathing, and greedy cell breathing algorithms.

5G-based MANET has received a lot of attention recently. Its fundamental feature is that nodes are constantly subjected to high traffic loads, while QoS requirements are extremely stringent. When applied to 5G-based MANETs, existing routing protocols have shown drawbacks. In this paper, we propose an enhanced AODV protocol solution for 5G-based MANETs. Using reinforcement learning, each node updates a state information database of intermediate nodes along routes to destinations. This database is used by the routing algorithm to find guaranteed QoS routes. Our solution is highly efficient in terms of throughput, end-to-end delay, and SNR, according to the simulation results.

Due to the recent increase in the mobile streaming market, mobile traffic is increasing exponentially. IMT-2020, named as the next generation mobile communication standard by ITU, is called the 5th generation mobile communication (5G), and is a technology that satisfies the data traffic capacity, low latency, high energy efficiency, and economic efficiency compared to the existing LTE (Long Term Evolution) system. 5G implements this technology by utilizing a high frequency band, but there is a problem of path loss due to the use of a high frequency band, which is greatly affected by system performance. In this paper, small cell technology was presented as a solution to the high frequency utilization of 5G mobile communication system, and furthermore, the system performance was improved by applying machine learning technology to macro communication and small cell communication method decision. It was found that the system performance was improved due to the technical application and the application of machine learning techniques.

The IEEE 802.1 time sensitive networking (TSN) and IETF deterministic networking (DetNet) standards guarantee ultra-low latency (ULL) communications in 5G networks and beyond. The DetNet standard can warrant deterministic ULL through the use of reinforcement learning (RL)-based data forwarding algorithms. Therefore, this study presents an overview of the DetNet mechanisms and explores the RL data forwarding techniques. It is shown that RL algorithms are capable of adjusting effectively the data transmission for deterministic applications, according to the resource usage of the networks.

5G 상용화가 교육분야의 변화에도 영향을 줄 것으로 전망된다. 본 연구는 5G로 인한 미래 대학교육 시나리오를 단말유형, 학습분야, 학습콘텐츠, 학습장소, 이용요금지불 등 5가지 속성(attributes)과 세부 수준(levels) 별로 구체화하였다. 그리고 이들 특성을 반영한 5G 기반 대학교육 혁신 서비스 이용의향과 선호도를 대학생 102명 대상으로 컨조인트 방법을 통해 분석하였다. 분석결과 5G 교육서비스에 대한 대학생의 이용의향은 86%로 높게 나타났으며, 이용요금형태(37%), 학습분야(26%), 학습콘텐츠(24%), 단말유형(8%), 학습장소(5%) 순으로 중요하게 고려하였다. 특히 속성별 각 수준에서 스마트 기기, 체험형 학습콘텐츠(Practice and experienceable), 언제 어디서나 활용할 수 있는 학습, 실습중심 과목(Practice-oriented subject), 무료이용(Cost free)에 대한 선호가 상대적으로 높은 것으로 나타났다. 본 연구는 4차 산업혁명 시대 대학교육 혁신 방안으로 5G 확산과 활용 전략을 마련하는데 기초자료와 전략적 시사점을 제공해 준다.

This study commercialization of 5G will enable transformation of university education. This study identifies five attributes (device type, learning place, learning content, learning field and expense payment) and corresponding levels to study the impact of 5G in the future of university education. The attributes and the levels are then combined into few 5G education service alternatives for respondents to rank. 102 students ranked the alternatives based on their preferences and intent to use. Results indicate that the intent to use 5G-based education service was high with 86% and the most important factor was expense payment (37%), followed by learning field (26%), learning content (24%), device type (8%) and learning place (5%). Specifically, students preferred smart device, practical and experiential content, ubiquitous (no limitation of space and time) learning, practical education and free rate when adopting 5G-based education service. These will provide implications to accelerate adoption of and exploitation of 5G for innovating university education.

G-러닝은 게임기술과 게임이론을 바탕으로 교육용 콘텐츠를 개발하고, 개발된 콘텐츠를 사용자들이 사용하면서 학습하는 것을 말하며, 게임 시장의 유망한 분야로 널리 연구되고 있다. 하지만 현재까지 나온 대부분의 G러닝 콘텐츠는 학습적인 요소들만을 강조하고, 제작하는데 에 많은 어려움을 있기 때문에 사용자들이 재미가 떨어지고, 궁극적으로 교육적인 효과까지 떨어지는 문제가 있다. 본 논문에서는 이러한 G러닝 콘텐츠를 사용하는 사용자들이 재미와 교육적인 효과를 모두 얻을 수 있도록 가상 애니메이션 장르인 머시니마 기술을 사용하였다. 제안된 시스템은 사용자들이 G러닝 콘텐츠를 머시니마 기법을 사용하여 쉽게 제작하고, 제작된 콘텐츠가 사용자들의 커뮤니티에 의해서 확대 및 재생산 되도록 함으로써, 사용자들의 참여를 유도 하였다. 제안된 시스템은 RPG 게임에 나오는 요소들을 이용하여 블록 맞추기 및 최소 거리 찾기 등의 문제를 해결해 나가는 교육요소를 적용하였다.

G-Learning is developed educational contents based on game technologies and theories, and users learn this educational content from playing the G-Learning. It is widely used as a promising application for game industry. However, conventional G-learning methods are focused on educational elements, and it is also difficult to create contents. In this paper, we proposed a G-Learning authoring tool using Machnima. The proposed system provides an authoring method using Machnima, and provides a collaborative virtual environment for various users to attend the created G-Learning content and modify it. The proposed method was applied to a 3D block design and finding a shortest path using resources, where role playing game are used.

This study suggests effectiveness of G-Learning (teaching and learning methodology utilizing interactions derived from game play) English afterschool class, which had been implemented for 3 months to 496 elementary school students in 5th grade at 31 elementary schools spread in the whole regions of Gyeonggi province. To achieve the goals of this study, two hypotheses were set in this study: 1) after conducting G-Learning English class, students' achievement in English study will increase, and 2) after conducting G-Learning English class, students' interest and confidence to English study will increase. Pre and post proficiency tests were conducted to verify the effectiveness of the G-Learning English class. A survey was also carried out with the participants of the class. The results showed that the students' achievement in reading was increased from 24.7 to 36.4 and vocabulary increased from 21.1 to 33.5 with statistical significance. The increase of the test score in three proficiency groups was as follow: high group was 9 points, middle group was 25 points, and low group was 38 points. Moreover, as for the affective factors toward English study, students' interest improved from 3.28 to 3.54 and confidence improved from 3.17 and all the aforementioned results showed statistical significance.

제시되는 개발 사례는 창의성 개발을 위한 스마트 교육 콘텐츠 개발내용으로서 학습자의 성향에 맞는 상호작용이 가능한 G-러닝 기반 교육교재 소프트웨어의 디자인 접근 및 개발내용을 제시하였다. 무엇보다도 게임의 특성인 상호작용을 극대화 할 수 있도록 디자인 접근방식에 초점을 두어 학습자의 성향에 따른 교육 수준 레벨별 몰입이 가능한 교육 콘텐츠를 개발한 것으로서 레벨 디자인 설계에 따른 난이도 기반 콘텐츠 구성이 가능한 콘텐츠이다. 또한, 시각적 측면에서 출현하는 오브젝트 및 캐릭터의 비주얼 커스터마이징(Customizing) 기능을 구현하여 학습자의 성향에 따라서 몰입할 수 있는 비주얼 환경을 설정하여 효과적인 교육이 가능하도록 구현한 사례이다.

The development case presented is about the development of smart education contents for development of creativity, and suggests the development contents and approach to design of software of teaching materials based on G-Learning which allow learner to interact depending on their dispositions. Above all, focusing on design approach in order to maximize interaction which is the characteristic of game, the education contents that enable learner to be immersed by education level as per learner’s disposition have been developed, and it allows to compose the level of difficulty based contents according to level design plan. Also, it is the case that the contents allow for effective education by setting visual environment which enables learner to be immersed depending on learner’s disposition with the realization of object which appears in respect of vision and visual Customizing of character.

본 연구의 목적은 G-러닝의 도입 배경과 교육환경의 변화에 맞추어 2012년에 개발한 기초학습부진 학생을 위한 기초셈하기 G-러닝 콘텐츠의 효과성 및 만족도를 분석하는데 있다. 이를 위해 서울시에 소재한 초등학교 3~6학년 기초셈하기 부진 학생 146명을 대상으로 G-러닝 콘텐츠 학습 전․ 후의 성취도 동형검사를 실시하여 통계적으로 유의미한 변화가 있는지 파악하였다. 또한 학생, 교사, 학부모를 대상으로 G-러닝 콘텐츠의 효과성에 대한 설문조사를 실시해 G-러닝 콘텐츠 및 활용에 대한 성향 및 현장의 만족도를 조사하였다. 연구결과 기초셈하기 G-러닝 콘텐츠를 활용한 학습자의 기초셈하기 능력은 전반적으로 향상되었다. 또한 기초셈하기 G-러닝 콘텐츠를 활용해 학습을 한 기초학습부진 학생들의 만족도는 좋은 편이었으며, 게임을 활용한 수학학습 이후 계산에 대한 자신감이 늘어나고, 수학곤란은 줄어들었다. 또한 학부모들은 기초셈하기 G-러닝 콘텐츠를 활용한 수학학습이 자녀들의 수학에 대한 자신감을 높여줄 뿐만 아니라 연산 능력 향상에도 도움이 된다는 긍정적인 반응을 보였다. 교사들 역시 프로그램에 대한 만족도는 높았지만 게임을 활용한 수학학습을 운영하면서 발생하는 콘텐츠 상의 오류, 멀티미디어 확보의 어려움, 게임 자체를 학습하게 되는 문제점 등을 지적하였다. G-러닝 콘텐츠 프로그램의 개발 및 효과성을 높이기 위해 보다 수학콘텐츠의 정교화 및 학생들의 심리연구 등에 대한 장기간의 광범위한 연구가 지속되어야 함을 제안하였다.

This study was to analyze the effects of basic computational abilities using G-learning contents, which was developed for mathematically slow learners. The participant students were 146 mathematically slow learners in grade 3-6 in Seoul. The researchers analyzed the difference between pre and post test scores to check their effectiveness. Also, teachers and parents as well as students responded survey items to check dispositions and satisfactions towards the program. The research results showed that the application of the G-learning contents on basic computation areas was effective to develop students’basic computational skills. In addition, students also showed that they were satisfied studying basic computations with the G-learning contents. They had increased beliefs about and decreased difficulties in mathematics. Parents and teachers also had satisfactions in using the G-learning programs in spite of some negative effects such as errors in the contents, use of computers, and concentration on the game itself. For the improvement of G-learning contents, we need to keep studying on G-learning contents with wide range of areas and long term studies.

이 연구는 기업교육 방법의 하나로 실시된 H금융기관 연수원 액션러닝 프로그램에 참여한 성인학습자를 대상으로 액션러닝 프로그램에 대한 경험 의미를 탐색하기 위한 것이다. 연구목적은 액션러닝 프로그램이 학습에 참여한 학습자들의 학습동기 증진과 직무문제해결능력 향상과 액션러닝 프로그램 구성요소 중 학습동기 증진과 직무문제해결능력 향상에 영향을 미치는 핵심 요소를 탐색하는 것이다. 연구방법은 액션러닝 프로그램에 참여한 학습자 9명을 대상으로 학습동기, 직무문제해결능력, 액션러닝의 구성요소관련 중심 질문 3개와 하위질문 15개를 구성한 후 포커스그룹 인터뷰(F.G.I)를 실시하였다. 연구결과, 액션러닝프로그램은 주의집중과 직무관련성이 연계하여 학습동기가 향상되고, 학습 팀 구성 정도가 학습동기 향상의 핵심 요소로 나타났다. 또한 대안개발과 계획/실행을 통하여 참여자의 직무문제해결능력 향상에 영향을 미치는 것으로 나타났고, 스폰서의 관심과 지지가 직무문제해결능력 향상의 핵심 요소로 탐색되었다. 결론적으로 기업의 직무교육활동에서 액션러닝프로그램은 참여자의 학습동기를 향상시킴으로, 직무교육 참여자의 직무문제해결능력 향상을 위해서는 프로그램 운영 시 주의집중과 직무관련성 강화 그리고 액션러닝 프로그램 구성 요소 중 적절한 학습 팀 구성에 관심과 주의를 기울여할 것이다. 이와 함께 계획/실행력을 증진시키기 위해서는 스폰서가 참여자의 문제인식을 파악하고 이들에 대한 지속적 관심과 지지가 필요하다.

The present study is aimed at inquiring into the meaning of experience of action learning program for adult learners who participated in action learning program of H financial company which was carried out as a means of corporate training. The goal of study is to examine the essential factors of action learning program impacting on the increase of motivation for learning and the improvement of job-related problem-solving ability of the learners who participated in the learning as well as on the increase of motivation for learning and the improvement of job-related problem-solving ability among the components of action learning program. As for research method, 3 main questions and 15 sub-questions about motivation for learning, job-related problem-solving ability, and components of action learning were prepared for 9 learners who participated in the action learning program, and then focus group interviews (F.G.I) were conducted. The results show that action learning program increased motivation for learning by combining concentration of attention and relevance to job, and the degree of organization of learning team was a key element to improving motivation for learning. Also, through development of alternatives and planning/execution, it impacted on improving job-related problem-solving ability of participants. And the interest and support of the administrator were key elements to improving job-related problem-solving ability. In conclusion, the results show that action learning program in corporate job training activities improves motivation for learning of the participants. Therefore, in order to improve job-related problem-solving ability of the participants in job training, more focus should be put on concentration of attention and reinforcement of relevance to the job and more interest and support should be given to organization of appropriate learning teams among components of action learning program. Along with this, the administrator needs to grasp participants' awareness of problems and pay attention and give support to the participants to enhance the performance of planning/execution.

본고에서는 新常用漢字表에서 중국어 語頭子音 g/k/, k/kʰ/를 해당하는 115字를 추출하여 중국어음과 일본한자음의 대응관계를 분석하였다. 그 결과 중국어 語頭子音 g/k/에 해당하는 일본한자음은 k 91音, g 5音에 해당하였으며, 語頭子音 k/kʰ/에 해당하는 일본한자음은 k 48音, g 2音에 해당하였다. g/k/:k 대응은 91音으로, 모두 見母 k에 해당한다. 見母는 일본한자음에서는 呉音･漢音 모두 カ行 k로 반영되었으며, 현대 중국어음에서 舌根音 g/k/, j/ʨ/로 분화되었다. 洪音일 경우 中古音부터 현대까지 g/k/의 발음을 유지해 왔다. g/k/:g 대응은 5音에 해당하는데, 모두 慣用音에 해당한다. 이는 淸濁의 混同으로 정착된 慣用音에 해당한다. k/kʰ/:k 대응은 溪母 kʰ가 41音으로 일본한자음에서는 呉音･漢音 모두 カ行 k로 반영되었다. 溪母는 中古音에서 kʰ로 재구되는데 현대 중국어음에서 대부분 kʰ를 유지하고 있다. 일본한자음에서는 有氣音이 존재하지 않기 때문에 呉音･漢音 모두 カ行 k로 代替된 것이다. k/kʰ/:g 대응은 2音으로 모두 溪母 kʰ에 해당하며 淸濁의 混同으로 인해 정착된 慣用音이다.

In this study, we extracted only Chinese characters with a On’yomi in the Joyokanji Table(2010) and used them as research data. Then, after extracting 115 Chinese characters corresponding to the g/k/, k/kʰ/ consonants of Modern Chinese, we analyzed the correspondence relationship between Modern Chinese and Sino-Japanese. As a result, g/k/ consonant corresponding to Sino-Japanese is k 91 sounds, g 5 sounds. And k/kʰ/ consonant corresponding to Sino󰠏Japanese is k 48 sounds, g 2 sounds. g/k/:k corresponds to 91 sounds all appear as initial Jian(見k). Initial Jian(見k) can be reflected as k and kʰ in Modern Chinese but appear as Ka-gyo(k) in Sino-Japanese both Go’on and Kan’on. g/k/:g corresponds to 5 sounds all appear as initial Jian(見k). k:g can be seen as Kanyo’on because the confusion of unvioced sound and voiced sound. k/kʰ/:k corresponds to 48 sounds among these initial Xi(溪kʰ) 41 sounds, initial Jian(見k) 3 sounds, initial Xia(匣ɦ) 2 sounds, initial Qun(群g) 1 sound and initial Xiao(曉h) 1 sound. Initial Xi(溪kʰ) appears as k consonant in Modern Chinese and also reflect as Ka-gyo(k) in Sino-Japanese both Go’on and Kan’on. Corresponding examples in initial Xia(匣ɦ) and initial Xiao(曉h) appears as a kʰ consonant shows a high possibility that laryngeal consonant ɦ and h can be interchange to velar consonant kʰ in Ancient Chinese. As exception, some corresponding examples in initial Jian(見k) and initial Qun(群g) can be shown as kʰ consonant. k/kʰ/:g corresponds to 5 sounds all appear as initial Xi(溪kʰ). k/kʰ/:g can be seen as Kanyo’on because the confusion of unvioced sound and voiced sound.

New learning method and the need for e-learning technology of the constructivist paradigm which consist the individual experience-centered learning experience, knowledge increased by escaping from the videos and flash-based simple one-side education contents.In this paper, the augmented reality English learning contents for the students to learn through the role and mission in the virtual space as the contents of new forms for the experiential learning through the augmented reality and TOLED(Transparent, Organic Light Emitting Diodes) system by using the vibrating Bluetooth maker cube for themulti maker configuration was designed and the system was designed to service it.

This study proposes the G-SLASH (Global Senior Learning Automated Smart Hub) model, an AI- and IoTbased automated recording framework for senior learning, addressing design, operational strategies, and policy implications. The model non-invasively captures daily activities of older adults and transforms them into global learning content through AI-based automated editing, summarization, and translation, while a central platform provides learning analytics and personalized feedback. The core architecture consists of five modules: automated recording, AI content generation, learning analytics, central platform and sharing, and governance. Operational scenarios encompass various living environments, rural and community activities, and instructor-led courses, minimizing technological burden and promoting sustained learning engagement. This study suggests that the G-SLASH model can enhance educational participation, social inclusion, policy feasibility, and cultural and economic impact. Additionally, it facilitates efficient use of resources in local universities and municipalities, activates global peer learning, and integrates lifelong learning policies with digital education strategies. This study offers a practical and policy-oriented foundation for digital transformation and global sharing of senior lifelong learning.

본 논문에서는 기존의 내용 전달 위주의 학습 메타버스 플랫폼이 아닌 실제 수업 활동에서 이루어지는 다양한 학습 상호작용에 기반한 가상 학습 플랫폼을 제안한다. 본 연구에서는 AI와 가상환경을 융합한 학습 환경을 제공하여 실시간 AI와 대화하며 문제를 풀어가는 방식을 활용하고 있다. 또한, 수업의 몰입도를 향상하기 위해 G-러닝 기법을 적용하였다. 본 연구를 통해 개발한 VirtualEdu 플랫폼은 자기주도적 학습, 게임을 통한 흥미 유발, 그리고 PBL 수업 방식을 조합하여 효과적인 학습 경험을 제공하고 있다. 이를 기반으로 학생들의 참여도와 학습 효과를 향상 시키는 새로 운 교육 방식을 제안하고 있다. 실험으로는 50명 이상의 학습자가 실시간 화상 학습 활동 기반의 다양한 학습 활동애 대해 성능 실험을 하였고, 결과로서 안정하게 원활한 수업이 진행됨을 얻을 수 있었다.

In this paper, we propose a virtual learning platform based on various interactions that occur during real class activities, rather than the existing content delivery-oriented learning metaverse platform. In this study, we provide a learning environment that combines AI and a virtual environment to solve problems by talking to real-time AI. Also, we applied G-learning techinques to improve class immersion. The Virtual Edu platform developed through this study provides an effective learning experience combining self-directed learning, simulation of interest through games, and PBL teaching method. And we propose a new educational method that improves student participation learning effectiveness. Experiment, we test performance on learninng activity based on real-time video classroom. As a result, it was found that the class progressing stably.

The digital age has brought about a series of changes. Against the background of the continuous integration of digital technology products and the teaching, the traditional classroom has begun to shift from a teacher-centered space to a student-centered space. The “digital natives”, who are born with digital technology, have become the main learners nowadays, and they are accustomed to using smart phones and tablets to learn. Therefore, E-Learning and its main branch, G-Learning, have come into being. G-Learning refers to complete teaching and learning through games. One of the most popular learning methods is the Kahoot! learning interactive platform. The Kahoot! learning interactive platform has been proven by many educators to improve students’ learning through classroom practices. However, in the Chinese classrooms in Korea, the Kahoot! is not very popular among teachers. The author examines the impact of Kahoot! on Korean learners by practicing it in Korean universities. Through interviews with students, this paper summarizes the applicability of Kahoot! in oral Chinese classes, and the advantages of Kahoot! include its easy operation, rich game elements, its applicability to a wide range of lessons and quizzes, and the automatic generation of result reports at the end of the game. Therefore, the use of Kahoot! brings a lot of convenience and fun to both teachers and students. In addition, since the ultimate goal of G-Learning is to improve learning performance, this paper provides a case study on a small number of students to learn about the changes in their academic performance before and after using Kahoot! by comparing the results of the pre- and post-tests. We believe that Kahoot! is conducive to stimulating students’ interest in learning, increasing their engagement in learning, and ultimately improving their academic performance. Of course, the changes in students’ performance may be affected by a number of factors, but we have to say that Kahoot! as a supplementary teaching tool has brought positive effects on teaching and learning.

This paper constructs Croup Technology process-based learning curve model adjusted to a Group Technology environment which accounts for shared learning that occurs when multiple products utilize some of the same process steps. Through this constructed model, the estimated times and productivity of labor calculated by the Group Technology process-based learning curve model are compared with those generated by employing product-based 1 earning curve model. For sensitivity analysis of the model, the impact of learning rate and the ordered production quantity on the ratio differences between Group Technology process-based learning curve model and product-based learning curve model are examined. These results indicate the critical importance of employing Group Technology process-based learning curve model when a process spans multiple products.

Background: Although ginsenosides such as Rg1, Rb1 and Rg3 have shown promise as potential nutraceuticals for cognitive impairment, their use has been limited due to high production cost and low potency. In particular, the process of extracting pure Rg3 from ginseng is laborious and expensive. Methods: We described the methods in preparing ginseol k-g3, an Rg3-enriched fraction, and evaluated its effects on scopolamine-induced memory impairment in mice. Results: Ginseol k-g3 (25-200 mg/kg) significantly reversed scopolamine-induced cognitive impairment in the passive avoidance, but not in Y-maze testing. Ginseol k-g3 (50 and 200 mg/kg) improved escape latency in training trials and increased swimming times within the target zone of the Morris water maze. The effect of ginseol k-g3 on the water maze task was more potent than that of Rg3 or Red ginseng. Acute or subchronic (6 d) treatment of ginseol k-g3 did not alter normal locomotor activity of mice in an open field. Ginseol k-g3 did not inhibit acetylcholinesterase activity, unlike donezepil, an acetylcholinesterase inhibitor. Rg3 enrichment through the ginseol k-g3 fraction enhanced the efficacy of Rg3 in scopolamine-induced memory impairment in mice as demonstrated in the Morris water maze task. Conclusion: The effects of ginseol k-g3 in ameliorating scopolamine-induced memory impairment in the passive avoidance and Morris water maze tests indicate its specific influence on reference or long-term memory. The mechanism underlying the reversal of scopolamine-induced amnesia by ginseol k-g3 is not yet known, but is not related to anticholinesterase-like activity.

본 논문에서는 G-러닝 콘텐츠를 사용자 수준에 맞는 난이도 조절을 위해 학습자의 수준을 평가하여 반영하고자 한다. 이때, 학습자의 수준은 게임의 적응도까지 고려하여 설계함으로써 사용자의 적응 훈련도까지 고려한 난이도 조절을 설계한다. 그럼으로써 학습자의 난이도에 맞는 G-러닝이 진행될 수 있도록 한다.