• Educational Technology International
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• 제24권2호
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• pp.295-329
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• 2023

The recent development of metaverse-related technology has led to efforts to overcome the limitations of time and space in education by creating a virtual educational environment. To make use of this platform efficiently, applying learning analytics has been proposed as an optimal instructional and learning decision support approach to address these issues by identifying specific rules and patterns generated from learning data, and providing a systematic framework as a guideline to instructors. To achieve this, we employed an inductive, bottom-up approach for framework modeling. During the modeling process, based on the activity system model, we specifically derived the fundamental components of the learning analytics framework centered on learning activities and their contexts. We developed a prototype of the framework through deduplication, categorization, and proceduralization from the components, and refined the learning analytics framework into a 7-stage framework suitable for application in the metaverse through 3 steps of Delphi surveys. Lastly, through a framework model evaluation consisting of seven items, we validated the metaverse learning analytics framework, ensuring its validity.

• 지능정보연구
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• 제26권4호
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• pp.27-65
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• 2020

많은 정보통신기술 기업들은 자체적으로 개발한 인공지능 기술을 오픈소스로 공개하였다. 예를 들어, 구글의 TensorFlow, 페이스북의 PyTorch, 마이크로소프트의 CNTK 등 여러 기업들은 자신들의 인공지능 기술들을 공개하고 있다. 이처럼 대중에게 딥러닝 오픈소스 소프트웨어를 공개함으로써 개발자 커뮤니티와의 관계와 인공지능 생태계를 강화하고, 사용자들의 실험, 적용, 개선을 얻을 수 있다. 이에 따라 머신러닝 분야는 급속히 성장하고 있고, 개발자들 또한 여러가지 학습 알고리즘을 재생산하여 각 영역에 활용하고 있다. 하지만 오픈소스 소프트웨어에 대한 다양한 분석들이 이루어진 데 반해, 실제 산업현장에서 딥러닝 오픈소스 소프트웨어를 개발하거나 활용하는데 유용한 연구 결과는 미흡한 실정이다. 따라서 본 연구에서는 딥러닝 프레임워크 사례연구를 통해 해당 프레임워크의 도입 전략을 도출하고자 한다. 기술-조직-환경 프레임워크를 기반으로 기존의 오픈 소스 소프트웨어 도입과 관련된 연구들을 리뷰하고, 이를 바탕으로 두 기업의 성공 사례와 한 기업의 실패 사례를 포함한 총 3 가지 기업의 도입 사례 분석을 통해 딥러닝 프레임워크 도입을 위한 중요한 5가지 성공 요인을 도출하였다: 팀 내 개발자의 지식과 전문성, 하드웨어(GPU) 환경, 데이터 전사 협력 체계, 딥러닝 프레임워크 플랫폼, 딥러닝 프레임워크 도구 서비스. 그리고 도출한 성공 요인을 실현하기 위한 딥러닝 프레임워크의 단계적 도입 전략을 제안하였다: 프로젝트 문제 정의, 딥러닝 방법론이 적합한 기법인지 확인, 딥러닝 프레임워크가 적합한 도구인지 확인, 기업의 딥러닝 프레임워크 사용, 기업의 딥러닝 프레임워크 확산. 본 연구를 통해 각 산업과 사업의 니즈에 따라, 딥러닝 프레임워크를 개발하거나 활용하고자 하는 기업에게 전략적인 시사점을 제공할 수 있을 것이라 기대된다.

• 인터넷정보학회논문지
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• 제24권4호
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• pp.37-45
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• 2023

Adaptive has gained significant attention in Education Technology (EdTech), with personalized learning experiences becoming increasingly important. Next-generation chatbots, including models like ChatGPT, are emerging in the field of education. These advanced tools show great potential for delivering personalized and adaptive learning experiences. This paper reviews previous research on adaptive learning and the role of chatbots in education. Based on this, the paper explores current and future chatbot technologies to propose a framework for using ChatGPT or similar chatbots in adaptive learning. The framework includes personalized design, targeted resources and feedback, multi-turn dialogue models, reinforcement learning, and fine-tuning. The proposed framework also considers learning attributes such as age, gender, cognitive ability, prior knowledge, pacing, level of questions, interaction strategies, and learner control. However, the proposed framework has yet to be evaluated for its usability or effectiveness in practice, and the applicability of the framework may vary depending on the specific field of study. Through proposing this framework, we hope to encourage learners to more actively leverage current technologies, and likewise, inspire educators to integrate these technologies more proactively into their curricula. Future research should evaluate the proposed framework through actual implementation and explore how it can be adapted to different domains of study to provide a more comprehensive understanding of its potential applications in adaptive learning.

• ETRI Journal
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• 제41권5호
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• pp.608-618
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• 2019

We propose a general framework for keyed learning, where a secret key is used as an additional input of an adversarial learning system. We also define models and formal challenges for an adversary who knows the learning algorithm and its input data but has no access to the key value. This adversarial learning framework is subsequently applied to a more specific context of anomaly detection, where the secret key finds additional practical uses and guides the entire learning and alarm-generating procedure.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.480-483
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• 2003

We propose a new framework that aims at multi-purpose image recognition, a difficult task for the conventional rule-based systems. This framework is farmed based on the idea of computer-based learning algorithm. In this research, we introduce the new functions of an additional learning and a knowledge reconstruction on the Fuzzy Inference Neural Network (FINN) (1) to enable the system to accommodate new objects and enhance the accuracy as necessary. We examine the capability of the proposed framework using two examples. The first one is the capital letter recognition task from UCI machine learning repository to estimate the effectiveness of the framework itself, Even though the whole training data was not given in advance, the proposed framework operated with a small loss of accuracy by introducing functions of the additional learning and the knowledge reconstruction. The other is the scenery image recognition. We confirmed that the proposed framework could recognize images with high accuracy and accommodate new object recursively.

• 한국멀티미디어학회논문지
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• 제6권4호
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• pp.676-684
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• 2003

eLearning can be defined as an approach to teaching and teaming that utilises Internet technologies to communicate and collaborate in an educational context. This includes technology that supplements traditional classroom training with web-based components and learning environments where the educational process is experienced online. The use of hypertext as an educational tool has a very rich history. The advent of the internet and one of its major application, the world wide web (WWW), has given a tremendous boost to the theory and practice of hypermedia systems for educational purposes. However, the web suffers from an inability to satisfy the heterogeneous needs of a large number of users. For example, web-based courses present the same static teaming material to students with widely differing knowledge of the subject. Adaptive hypermedia techniques can be used to improve the adaptability of eLearning. In this paper we report an approach to the design a unified implementation framework suitable for web-based eLearning that accommodates the three main dimensions of hypermedia adaptation: content, navigation, and presentation. The framework externalises the adaptation strategies using XML notation. The separation of the adaptation strategies from the source code of the eLearning software enables a system using the framework to quickly implement a variety of adaptation strategies. This work is a part of our more general ongoing work on the design of a framework for adaptive content delivery. parts of the framework discussed in this paper have been imulemented in a commercial eLearning engine.

• Educational Technology International
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• 제18권1호
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• pp.1-25
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• 2017

Educational applications of big data analysis have been of interest in order to improve learning effectiveness and efficiency. As a basic challenge for educational applications, the purpose of this study is to develop a comprehensive data set scheme for learning analytics in the context of digital textbook usage within the K-12 school environments of Korea. On the basis of the literature review, the Start-up Mega Planning model of needs assessment methodology was used as this study sought to come up with negotiated solutions for different stakeholders for a national level of learning metrics framework. The Ministry of Education (MOE), Seoul Metropolitan Office of Education (SMOE), and Korean Education and Research Information Service (KERIS) were involved in the discussion of the learning metrics framework scope. Finally, we suggest a proposal for the national learning metrics framework to reflect such considerations as dynamic education context and feasibility of the metrics into the K-12 Korean schools. The possibilities and limitations of the suggested framework for learning metrics are discussed and future areas of study are suggested.

• 한국컴퓨터정보학회논문지
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• 제22권10호
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• pp.129-135
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• 2017

This research is to identify an easy and effective method of teaching-learning plan. The teaching-learning plan is a blue_print applied for designing effective lessons. However, most of the teachers regard it as a difficult and inefficient job. This study proposed the concrete instructional model framework as a tool to develop the teaching-learning plan easily and effectively. The concrete instructional model framework will represent a decomposed instructional strategy applied for each step of the instructional model developed by educational researchers. This method is applied to develop a computer teaching-learning plan. Therefore, the proposed method will expand an easier teaching-learning plan. Furthermore, the proposed method develops a teaching-learning plan with fluent content in detail based on low-level instruction strategies applied in the concrete instruction model framework.

• International Journal of Computer Science & Network Security
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• 제23권2호
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• pp.39-46
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• 2023

The purpose of this study is to introduce a proposed Framework for Evaluating the Return on Investment (ROI) of E-Learning Programs at Saudi Universities. To achieve this goal, the descriptive analysis methodology is used to analyze the literature review about e-learning and its evaluation from different viewpoints, especially from the ROI-related perspective. As well as the literature reviews related to ROI and the methods of calculating it inside society institutes. This study suggests a conceptual framework for evaluating the ROI of E-Learning Programs at Saudi Universities. This framework is based on the merging process among the analyze, design, develop, implement, and evaluate (ADDIE) model for designing e-learning programs, which gives detailed procedures for executing the program, several evaluating models for e-learning, and the Kirkpatrick model for evaluating the ROI of e-learning. It consists of seven stages (analysis, calculating the costs, design, development, implementation, calculation of the benefits, and calculation of the final ROI).

• Asia Marketing Journal
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• 제17권1호
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• pp.27-53
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• 2015

Learning organization has been an important issue in both management and marketing areas. Also learning capability is a key construct of innovation process in a firm. Especially, in marketing context, several researchers have studied market-based learning and its relation with performance. Previous studies have shown that market-based learning has a positive impact on overall firm performance. However, there has been inconsistency in the concept of market-based learning itself and its relationships with antecedents and consequences. Given this conflicting and inconsistent results of previous research, this study has two main objectives. First, this paper proposed a conceptual framework that marketbased learning has two types of processes and each types of market-based learning will generate different types of performance. Second, the mediating role of marketing capability in learning-performance link is proposed. The proposed conceptual framework shows that organizations which have marketbased learning for innovation management can enjoy ambidextrous firm performance on both side of effectiveness and efficiency via marketing capability. Moreover our research model proposes key drivers of market based organizational learning.