• The Journal of Information Systems
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• v.30 no.2
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• pp.127-146
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• 2021

Research Purpose Advances in digital technology have facilitated the widespread adoption of online learning, which has become a substantial way of learning. Although digital immigrants have become a main group of users of learning online, there is a lack of understanding of their online learning. This study aims to explore digital immigrants' adoption of online learning from the goal-pursuit perspective to gain insight into how they use online learning. Research Method A laddering interview was conducted with 22 Korean adults to elicit their goals in online learning. Then, a means-end chain analysis was used to derive their hierarchical goal structure. Findings The results reveal digital immigrants' goal structure of online learning, consisting of four attributes of online learning (e.g., accessibility, diversity, up-to-dateness, and repeatability) and six goals (e.g., self-esteem, enjoyment, recognition, productivity, gaining insights, and positive relations). This study contributes to the literature by providing a rich picture of their use of online learning.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.83-92
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• 2023

The majority of product users rely on the reviews that are posted on the appropriate website. Both users and the product's manufacturer could benefit from these reviews. Daily, thousands of reviews are submitted; how is it possible to read them all? Sentiment analysis has become a critical field of research as posting reviews become more and more common. Machine learning techniques that are supervised, unsupervised, and semi-supervised have worked very hard to harvest this data. The complicated and technological area of feature engineering falls within machine learning. Using deep learning, this tedious process may be completed automatically. Numerous studies have been conducted on deep learning models like LSTM, CNN, RNN, and GRU. Each model has employed a certain type of data, such as CNN for pictures and LSTM for language translation, etc. According to experimental results utilizing a publicly accessible dataset with reviews for all of the models, both positive and negative, and CNN, the best model for the dataset was identified in comparison to the other models, with an accuracy rate of 81%.

• Journal of East Asia Management
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• v.4 no.2
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• pp.39-62
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• 2023

Online and offline mixed teaching mode has become an important way to promote the connotative development of higher education. Under the background that offline teaching has become mature, in order to further promote the development of online education, and promote the implementation of the mixed teaching mode, to mix and to provide basis for the construction of the mixed teaching mode, this study takes the online learning effect as the evaluation basis, adopts the online questionnaire survey to conduct statistical analysis of the online learning behavior of 2213 college students, and discusses the differentiation phenomenon of online learning groups from the micro, meso and macro perspectives. It is found that there are significant differences in the online learning effect of college students in terms of the type of learning platform, whether the school implements the online offline mixed teaching mode, education background, grade (bachelor's degree), and region. Colleges and universities should strengthen the promotion of online and offline mixed teaching mode; The online learning platform should improve the platform function and strengthen the functional differentiation design of learning resources for students. Education departments pay attention to the learning effect of online learners in different regions, and bridge the gap in regional education.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.360-370
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• 2022

Demand for machine learning systems continues to grow, and cloud machine learning platforms are widely used to meet this demand. Recently, the performance improvement of the application processor of smartphones has become an opportunity for the machine learning platform to move from the cloud to On-Device AI, and mobile applications equipped with machine learning functions are required. In this paper, machine learning tools for mobile applications are investigated and compared the characteristics of these tools.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.287-295
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• 2020

This study defined the characteristics of micro-learning emerging by mobile learning and micro-contents in the e-learning field, and analyzed the satisfaction of application, to see if micro-learning could become a new learning type in the future. To this end, the characteristics of micro-learning were defined through preliminary literature analysis, the characteristic satisfaction was verified in the well-equipped micro-learning site, and any other technical functions were suggested through expert opinion gathering. It was suggested that the future technology of e-learning should be linked to technical functions such as learning analysis and performance measurement. According to the results of this study, if micro-learning reflects its functional characteristics well, it will become an effective learning type in the e-learning field and will greatly contribute to education, learning, and training for the new millennial.

• IE interfaces
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• v.18 no.4
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• pp.412-417
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• 2005

This paper describes the development of on-line Programmable Logic Controller(PLC) laboratories to teach the detailed operation of a PLC using distance learning approach. The PLC has become a key component to provide intelligence for machines in CIM environment. This study introduces a case study that teaches PLC programming in distance learning environment. The study describes the contents of PLC laboratories and workstation set ups. The study concludes with problems found and proposes the ways to improve the on-line laboratories.

• Journal of the Korean School Mathematics Society
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• v.3 no.2
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• pp.111-122
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• 2000

This study is focused on vocational high school students who feel hardly interested in mathematics and are considered to have very limited basic scholastic ability. It analyzes the data obtained by applying the material, extracted from the Internet and literature to school classes from March to July, for the purposes of improving the degree of scholastic achievement on the basis of the fact that interest induced learning materials were developed and applied to the students to bring about their motivation resulting in a positive change in understanding and attitudes to mathematics. According to the result of the analysis, the level of students' scholastic ability of both the comparative class and the experimental class were too low to become interested in mathematics. However, the experimental class students seemed to feel familiar to the learning materials rather than reluctant, and it appeared that their interest and behavior of learning began to change gradually in an extent. In addition to that, as an aspect of scholastic achievement there was not considerable difference between the two classes, but as time went, some valuable changes were found. Unfortunately, the size of group of the research was small and the period of the experimental classes was not extensively long, and therefore the same result might not occur in other groups. However, it is believed that in class-time, educating students by putting in learning materials bringing about relevant motivation to the class, will lead them to become interested in mathematics, and change their attitudes and understanding of mathematics. After all, scholastic achievement will be effective.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.277-283
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• 2022

Email phishing has become very prevalent especially now that most of our dealings have become technical. The victim receives a message that looks as if it was sent from a known party and the attack is carried out through a fake cookie that includes a phishing program or through links connected to fake websites, in both cases the goal is to install malicious software on the user's device or direct him to a fake website. Today it is difficult to deploy robust cybersecurity solutions without relying heavily on machine learning algorithms. This research seeks to detect phishing emails using high-accuracy machine learning techniques. using the WEKA tool with data preprocessing we create a proposed methodology to detect emails phishing. outperformed random forest algorithm on Naïve Bayes algorithms by accuracy of 99.03 %.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.345-353
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• 2006

Over the past few years, training professionals have become more pragmatic in their approach to technology-based media by using it to augment traditional forms of training delivery, such as classroom instruction and text-based materials. This trend has led to the rise of the term blended learning. Blended learning, an environment of e-learning, is a powerful learning solution created through a mixture of face-to-face and online learning delivered through a mix of media and superior learning experiences. In this article we design and implement an e-learning environment for blended learning. The environment focused on following factors: learning activity and participation of learners, and real time feedback of instructor.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.21-36
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• 2009

As the World Wide Web (WWW) has become a major channel for information delivery, the data accumulated in the Internet increases at an incredible speed, and it derives the advances of information search technologies. It is the search engine that solves the problem of information overloading and helps people to identify relevant information. However, as search engines become a powerful tool for finding information, the opportunities of plagiarizing have increased significantly in e-Learning. In this paper, we developed an online plagiarism detection system for detecting plagiarized documents that incorporates the functions of search engines and acts in exactly the same way of plagiarizing. The plagiarism detection system uses morpheme analysis to improve the performance and sentence-based comparison to investigate document comes from multiple sources. As a result of applying this system in e-Learning, the performance of plagiarism detection was improved.