• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.203-210
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• 2023

As the environment changes become more complex, learners should establish the learning strategy for the 4th industrial era and the post-COVID-19, also change. This paper focuses on the importance of self-regulated learning. Through this learning strategy, learners will form more positive attitudes and reduce negative attitudes toward the 4th industrial era. This attitude change will lead to an improvement in learners' career decision-making efficacy as a sense of future efficacy. As a result of the study, it was demonstrated that self-regulated learning improves career decision-making efficacy through the mediating effect of positive attitude formation toward the fourth industry. This article emphasizes the necessity of self-regulated learning as a valid learning strategy for the new era. The effect of self-regulated learning is explained as an improvement in attitude toward the future and a sense of efficacy. Through this learning strategy, learners' future performance could be improved.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.81-87
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• 2019

It is changing to the 4^th Industrial Revolution rapidly as the information age through the Internet is changing, and it is rapidly changing to the era of the IoT using all things. In education, with the change to the Internet of Things, interest in education for the 4th Industrial Revolution is increasing. It is necessary to change from NetPBL method using Internet to T-PBL using Triz. In this paper, we focus on the task-based learning (T-PBL) method using Triz and examine the necessity and importance of its use. We propose a teaching model using Triz as a tool for T-PBL. Triz is being used as a tool to solve problems in creative ways. We will design a model applying Triz to the blockchain system security class related to the IoT.

• The Journal of Korean Association of Computer Education
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• v.13 no.4
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• pp.61-68
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• 2010

One often thinks that those doing any activity on the Internet are likely to be addicted to it so that they tend to rather restrain the educational use of what the Internet can provide. However, the online edu-games deserve a good learning material which can not only provoke learners' interest but also draw out a smoother interaction between teachers and learners. Even the preliminary study on immersion verified that the Internet could work positively for the learners. Considering that online edu-games can be a useful tool for individual learning, more studies on immersion should be conducted focusing on the individualization in the future. This paper shows the differences among the components of learning immersion depending on the different individual cognitive styles in the online edu-games.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2188-2203
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• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.102-107
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• 2006

While Internet-based distance learning has proliferated, its educational effectiveness remains controversial. As such, investigation into the problems of Internet-based distance learning is important and fundamental for an assessment of its educational effectiveness. In this study, problems of Internet-based distance learning are grouped into four categories, environmental problems, student problems, course design problems and operational problems. Based on survey data from 606 distance learning participants, perceptional and relative seriousness of problems are analysed. The results indicate that perceptional seriousness of all the problems is not statistically important. However, the findings indicate that the relative seriousness of self willingness among student problems and cheating within operational problems is most remarkable. In contrast, the relative seriousness of traditionally recognized problems such as H/W availability and network speed among environmental problems is least remarkable. An analysis of demographic differences such as sex, employment and age in terms of seriousness of problem is also performed. The results reveal the existence of statistically significant differences according to sex, employment, and age difference with regard to seriousness of problems.

• Journal of Internet Computing and Services
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• v.2 no.1
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• pp.39-48
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• 2001

In learning activities. research learning is mostly carried out in a laboratory. Learners can approach a learning process with ease and are given the chance to do the self-directed study one research experiments in advance by designing a process of research learning in the laboratory by a web-based simulation courseware. And this can offer a learner-centered model with which learners can share. exchange and interact information each other. Using a web in instructing and learning can be an appropriate implement of research and also gives learner-centered learning environment. This thesis is a study on design and implementation of a web-based simulation courseware for learning Kinetic energy through the research learning which is one of the self leading learning methods.

• Journal of The Korean Association of Information Education
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• v.13 no.1
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• pp.77-84
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• 2009

Along with developments of information and communication technologies, internet has spread not only all over the society, but also our everyday life deeply. Also requirements for e-learning using internet in the educational aspect have a great influence on the changes of school educations. The benefits of e-learning are many, including cost-effectiveness, enhanced responsiveness to change, consistency, and timely contents. Therefore, the e-learning has been introduced to the universities. However, the e-learning is operated inefficiently because of introduction to the university with no definite idea about effects of education and economy in the university. Therefore, in this paper we analysed the category of e-learning based the curriculum operation forms in the university, surveyed tests about students preference and the studied what is desirable e-learning operation forms.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2540-2542
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• 2003

This paper presents an internet-based self-learning educational system which can be enhancing efficiency in the learning process of Java language. The proposed self-learning educational system is called Java Web Player(JWP), which is a Java application program and is executable through Java Web Start technologies. In this paper, three important sequential learning processes : concept learning process, programming practice process and assessment process are integrated in the proposed JWP using Java Web Start technologies. This JWP enables the learners to achieve efficient and interesting self-learning since the learning process is designed to enhance the multimedia capabilities on the basis of educational technologies. Also, online voice presentation and its related texts together with moving images are synchronized for efficient language learning process. Furthermore, a simple/useful compiler is included in the JWP for providing language practice environment such as coding, editing, executing and debugging Java source files. Finally repeated practice can make the learners to understand easily the key concepts of Java language. Simple multiple choices are given suddenly to the learners while they are studying through the JWP and the test results are displayed on the message box.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2799-2823
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• 2019

With the help of learning analytics, MOOCs have wider potential to succeed in learning through promoting self-regulated learning (SRL). The current study aims to apply and validate visualization design guidelines for a MOOC dashboard to enhance such SRL capabilities based on learning analytics. To achieve the research objective, a MOOC dashboard prototype, LM-Dashboard, was designed and developed, reflecting the visualization design guidelines to promote SRL. Then, both expert and learner participants evaluated LM-Dashboard through iterations to validate the visualization design guidelines and perceived SRL effectiveness. The results of expert and learner evaluations indicated that most of the visualization design guidelines on LM-Dashboard were valid and some perceived SRL aspects such as monitoring a student's learning progress and assessing their achievements with time management were beneficial. However, some features on LM-Dashboard should be improved to enhance SRL aspects related to achieving their learning goals with persistence. The findings suggest that it is necessary to offer appropriate feedback or tips as well as to visualize learner behaviors and activities in an intuitive and efficient way for the successful cycle of SRL. Consequently, this study contributes to establishing a basis for the visual design of a MOOC dashboard for optimizing each learner's SRL.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4776-4794
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• 2020

We propose a rapid adaptive learning framework for streaming object detection, called EER-ASSL. The method combines the expected error reduction (EER) dependent rollback learning and the active semi-supervised learning (ASSL) for a rapid adaptive CNN detector. Most CNN object detectors are built on the assumption of static data distribution. However, images are often noisy and biased, and the data distribution is imbalanced in a real world environment. The proposed method consists of collaborative sampling and EER-ASSL. The EER-ASSL utilizes the active learning (AL) and rollback based semi-supervised learning (SSL). The AL allows us to select more informative and representative samples measuring uncertainty and diversity. The SSL divides the selected streaming image samples into the bins and each bin repeatedly transfers the discriminative knowledge of the EER and CNN models to the next bin until convergence and incorporation with the EER rollback learning algorithm is achieved. The EER models provide a rapid short-term myopic adaptation and the CNN models an incremental long-term performance improvement. EER-ASSL can overcome noisy and biased labels in varying data distribution. Extensive experiments shows that EER-ASSL obtained 70.9 mAP compared to state-of-the-art technology such as Faster RCNN, SSD300, and YOLOv2.