• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.9-15
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• 2019

Large global online shopping malls, such as Amazon, offer services in English or in the language of a country when their products are sold. Since many customers purchase products based on the product reviews, the shopping malls actively utilize the sentimental analysis technique in judging preference of each product using the large amount of review data that the customer has written. And the result of such analysis can be used for the marketing to look the potential shoppers. However, it is difficult to apply this English-based semantic analysis system to different languages used around the world. In this study, more than 500,000 data from Amazon fine food reviews was used for training a deep learning based system. First, sentiment analysis evaluation experiments were carried out with three models of English test data. Secondly, the same data was translated into seven languages (Korean, Japanese, Chinese, Vietnamese, French, German and English) and then the similar experiments were done. The result suggests that although the accuracy of the sentimental analysis was 2.77% lower than the average of the seven countries (91.59%) compared to the English (94.35%), it is believed that the results of the experiment can be used for practical applications.

• English Language & Literature Teaching
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• v.17 no.4
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• pp.97-121
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• 2011

This study aims to examine how motivational constructs are interrelated with social, context-specific factors and, as a result, contribute to L2 writing achievement within the framework of self-determination theory. The data consisted of 67 Korean college students' questionnaire responses, final scores in an on-offline blended writing course, and qualitative interviews with 5 students. In the descriptive and the correlation analyses, the participants' extrinsic motivation was found higher than intrinsic motivation, with low amotivation. Among social factors, immersion environment, foreign instructor, and peer comparison marked high scores, whereas Korean instructor and online material gained low scores. Those contextual factors were interrelated with each other, such that the immersion factor correlated significantly with Korean instructor and peer comparison. Extrinsic and intrinsic motivational subscales engendered strong correlations with the high-scored social factors, i.e., immersion, foreign instructor, and peer comparison, which were also closely interrelated with L2 writing achievement. The findings illuminate intricate workings of motivation in its effects on L2 achievement and corroborate the roles of contextual factors. The effect of motivational subscales on achievement may be valid through interplay with some social factors. The dynamics of motivation is discussed for pedagogical applications.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.329-331
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• 2020

Edutech is a compound word of education and technology, and is an educational paradigm in the era of the 4th industrial revolution. This refers to next-generation education using information and communication technology (ICT) such as big data, artificial intelligence (AI), robots, and virtual reality (VR) of the 4th industrial revolution. e-Learning is being used as an online lecture for education in ICT, but edutech is attracting attention along with e-learning as the feeding of non-face-to-face education has rapidly increased due to COVID-19. Therefore, this paper summarizes the reviewed papers on the blockchain-based badge service platform, simulation-based collaborative e-Learning system, video English dictionary, and blockchain-based access control audit system.

• Journal of Korea Game Society
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• v.15 no.3
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• pp.151-160
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• 2015

This paper presents English vocabulary memorization system using forgetting curve to automatically adjust the vocabulary difficulty to match learner's level. Our system will decide the appropriate repetition cycle, depending on the number of memorizing words through the forgetting curve, then requires an iterative learning. No matter what learners know or do not know, words are reviewed. To save time by reviewing some words which have the highest probability that learners forget. And it provides vocabulary based on learner level, which makes learner maintain their interest and achievement. A general system provides vocabularies which difficulty matches with evaluated ones, or randomly provides some vocabularies without consideration of users' level. But we apply the "Glicko" system which is being used in the online chess game ranking system to adjust the vocabulary's difficulty. We utilize the system used in the one-by-one player system to our vocabulary-human system. As a result, learners's level and the vocabularies's difficulty is measured in the review process. Moreover it maximizes the performance of English vocabulary memorization by applying feedbacks from practice testing and distributed learning.

• The Journal of Industrial Distribution & Business
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• v.11 no.5
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• pp.17-26
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• 2020

Purpose: Previous studies rarely investigated the effects of the metacognitive reading strategies on reading engagement, particularly in globalized higher education, while those studies examined reading problems and engagement with lower reading level. The purpose of this study is to investigate the effects of the metacognitive reading strategies including global reading, problem solving, and supporting reading on reading engagement that include argentic, behavior, emotional, and cognitive engagement in global learning environment. This study investigated research questions: how do global reading, problem solving, and supporting reading strategies affect argentic, behavior, emotional, and cognitive reading engagement? Research design, Data, and methodology: This study collected data via online survey in globalized learning environment. This study applied statistical analyses, such as factor and regression analyses and ANOVA. Results: The results of this study showed that metacognitive reading strategies had significant effects on student reading engagement while they were reading class materials in English for academic purposes. Conclusions: This study provides managerial implications in higher education by providing better strategies to enhance learning skills in global context. In particular, this study provides implications that the effects of problem solving and supporting strategies could be improved by adopting better management systems in globalized education.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.334-342
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• 2022

Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.101-112
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• 2024

Telugu language is considered as fourth most used language in India especially in the regions of Andhra Pradesh, Telangana, Karnataka etc. In international recognized countries also, Telugu is widely growing spoken language. This language comprises of different dependent and independent vowels, consonants and digits. In this aspect, the enhancement of Telugu Handwritten Character Recognition (HCR) has not been propagated. HCR is a neural network technique of converting a documented image to edited text one which can be used for many other applications. This reduces time and effort without starting over from the beginning every time. In this work, a Unicode based Handwritten Character Recognition(U-HCR) is developed for translating the handwritten Telugu characters into English language. With the use of Centre of Gravity (CG) in our model we can easily divide a compound character into individual character with the help of Unicode values. For training this model, we have used both online and offline Telugu character datasets. To extract the features in the scanned image we used convolutional neural network along with Machine Learning classifiers like Random Forest and Support Vector Machine. Stochastic Gradient Descent (SGD), Root Mean Square Propagation (RMS-P) and Adaptative Moment Estimation (ADAM)optimizers are used in this work to enhance the performance of U-HCR and to reduce the loss function value. This loss value reduction can be possible with optimizers by using CNN. In both online and offline datasets, proposed model showed promising results by maintaining the accuracies with 90.28% for SGD, 96.97% for RMS-P and 93.57% for ADAM respectively.

• The Journal of Korean Association of Computer Education
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• v.18 no.1
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• pp.81-97
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• 2015

Although Flipped Classroom(FC) which has recently attracted attention of educational field, showed its various educational effects such as learning academic achievement, attitude, collaborative learning and self-regulated learning. other studies also showed a number of significant problems and challenges in practically implementing. Thus, this study aims to investigate in-service and pre-service teachers awareness of FC in order to explore its educational feasibility for successfully adopting it to classrooms through the alternative solutions to its limitations. To achieve this goal, we firstly conducted literature review on teaching and learning models and guidelines to draw educational prerequisites and then analyzed needs of 156 pre-service teachers and 42 in-service teachers. According to survey results, 80% of teachers are willing to apply FC to their classes and hope to be offered with pre-learning activity materials and guidelines. They consider junior high school students and college students as appropriate learners, social science, science, Korean, and English as suitable subjects, and video content as optimal materials for pre-learning activities.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.135-140
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• 2021

The present research intends to examine how college students' self-determination affects their beliefs in and achievement in foreign language learning in the current pandemic times. The data under discussion was collected from a survey questionnaire conducted to a group of 107 students attending at a four-year university in Cheonan. With the software SPSS Version 21.0, a set of statistical methods were employed: (i) descriptive statistics along with (ii) correlation analysis and (iii) regression analysis. The current analysis identified a positive correlation between their self-determination and both beliefs Foreign Langage Learning and Learning Outcomes, which means that the former exerts a significant impact on the latter. The results are expected to help educators arrange strategic plans that can enhance collegians' self-determination for their better performance of foreign language learning.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.6
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• pp.1556-1568
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• 2015

The objectives of this study were to inquiry of application types and use methodology of EBS-CSAT prep books of vocation education division in specialized vocational high schools. Research participants are 8 specialized vocational high school teachers in Seoul and Gyeonggi, and subjects are basic industry and basic drawing. The teachers had using EBS-CSAT prep books in class or after-school. The results are as follows: The teachers used items explanation of after-school rather than regular classes using EBS-CSAT prep books of vocation education division in specialized vocational high schools. Online lectures were used for self-directed learning of specialized vocational high school students rather than regular classes. Students and teachers of specialized vocational high school needed EBS-CSAT prep books of vocation education division by free gift instead of EBS-CSAT prep books of Korea language, english, math.