• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.355-363
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• 2011

Level-Based Education is necessary for the multi-cultural learners because they tend to have the academic underachievement and learning deficiency that cause the huge educational gap. However, it is very hard to make the best of competence for the multi-cultural learners in the classroom. So, it is needed to suggest how we can use the educational contents that are appropriate for the Level-Based Learning and Individual Learning to make good use of teaching the learners from multi-cultural families. However, developing the new educational contents takes much time and cost, we have to improve existing contents for the student from multi-cultural families to use it. Hence, the purpose of this thesis is to develop the educational appropriateness evaluation scale to verify the educational contents that are for the multi-cultural students based on the educational content's evaluation tool, so by developing the scale, I intend to evaluate the 4~6 grades' Korean contents of the E-learning service and provide the ways of improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.263-283
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• 2024

Users' comments after online shopping are critical to product reputation and business improvement. These comments, sometimes known as e-commerce reviews, influence other customers' purchasing decisions. To confront large amounts of e-commerce reviews, automatic analysis based on machine learning and deep learning draws more and more attention. A core task therein is sentiment analysis. However, the e-commerce reviews exhibit the following characteristics: (1) inconsistency between comment content and the star rating; (2) a large number of unlabeled data, i.e., comments without a star rating, and (3) the data imbalance caused by the sparse negative comments. This paper employs Bidirectional Encoder Representation from Transformers (BERT), one of the best natural language processing models, as the base model. According to the above data characteristics, we propose the F_MixBERT framework, to more effectively use inconsistently low-quality and unlabeled data and resolve the problem of data imbalance. In the framework, the proposed MixBERT incorporates the MixMatch approach into BERT's high-dimensional vectors to train the unlabeled and low-quality data with generated pseudo labels. Meanwhile, data imbalance is resolved by Focal loss, which penalizes the contribution of large-scale data and easily-identifiable data to total loss. Comparative experiments demonstrate that the proposed framework outperforms BERT and MixBERT for sentiment analysis of e-commerce comments.

• Journal of The Korean Association of Information Education
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• v.19 no.3
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• pp.311-322
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• 2015

This study analyzed the trend and problems in the design of contents developed by teachers, and suggested strategies for improvement. It analyzed the contents ranked as the first level in the Research Competition on Educational Informatization for the last 3 years. Concerning the 8 types of instructional activities and the 6 types of knowledge acquisition, most contents took limited types(i.e., the individual tutoring type, the concept learning type and the principle learning type). In addition, when the contents were evaluated according to the quality certification criteria for educational software, it was found that the quality level of the design was low in many criteria. When the content analysis was applied for the in-depth analysis of design characteristics, various problems were found in the areas such as evaluation, feedback and learning objectives. Also other common problems were found in the design areas such as level-based differentiated learning, interaction between students and contents, presentation of text and narration, utilization of information on a student, screen design, the content level appropriate for students. In relation to the problems found from the analysis, some strategies for improvement were suggested concerning the following topics: question selection and guidance for evaluation, content and types of feedback, statement of learning objectives, selection of content, interaction, and screen design.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.137-142
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• 2021

Distance learning universities provide online course content. The main methods of providing class contents are on-demand and live-streaming. This means that students are not restricted by time or space. The advantage is that students can take the course anytime and anywhere. Therefore, unlike commuting students, there is no commuting time to the campus, and there is no natural process required to take classes. However, despite this convenient situation, the attendance rate and graduation rate of distance learning universities tend to be lower than that of commuting universities. Although the course environment is not the only factor, students cannot obtain a bachelor's degree unless they fulfill the graduation requirements. In both commuter and distance learning universities, taking classes is an important factor in earning credits. There are fewer time and space constraints for distance learning students than for commuting students. It is also easy for distance learning students to take classes at their own timing. There should be more ease of learning than for students who commute to school with restrictions. However, it is easier to take a course at a commuter university that conducts face-to-face classes. I thought that the reason for this was that commuting to school was a part of the process of taking classes for commuting students. Commuting to school was thought to increase the willingness and motivation to take classes. Therefore, I thought that the inconvenient constraints might encourage students to take the course. In this research, I focused on the act of commuting to school by students. These situations are also applied to the distance learning environment. The students have physical time constraints. To achieve this goal, I will implement a course restriction method that aims to promote the willingness and attitude of students. Therefore, in this paper, I have implemented a virtual school system called "virtual go to school (VG2S)" that reflects the actual route to school.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.47-64
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• 2023

The current elementary mathematics curriculum does not include intensive quantity. However, other subjects also deal with intensive quantity. In order to find a solution to this problem from a pedagogical point of view, the curriculum of mathematics, science, social studies, and elementary textbooks were compared and analyzed, focusing on intensive quantity. As a result of the analysis, the learning contents of intensive quantity were not explicitly presented or the term was not used in the elementary mathematics curriculum. However, intensive quantity was used as a material of activity and word problems in elementary mathematics textbooks. In science and social studies, it was also found that the learning order and content did not match, such as calculating the intensive quantity. For effective learning, it is necessary to consider presenting intensive quantity in elementary mathematics, and to be careful in the composition of learning order and content.

• Communications of Mathematical Education
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• v.30 no.3
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• pp.309-333
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• 2016

This study is part of app development research based on user centered design which targets silver generation learners. The mathematical contents provided by Senior math application focus on Numeracy issues. In order to finalize the user interface and the mathematical contents which is for developing the mathematic application, teaching experiment was carried out through 9 senior learners. Also CIPP program evaluation model was used for monitoring the result of this teaching experiment. Factors such as 'educational objectives' 'requirement analysis' 'educational environment' 'curriculum' 'learning content' 'learning matter' 'interaction' 'program administration' 'supporting environment' 'satisfaction' 'study result' 'substantiality of learning' were checked and as a result the Senior Mathematic application was developed through these feedbacks.

• Journal of Korean Elementary Science Education
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• v.28 no.3
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• pp.245-262
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• 2009

This research was to examine the understandings of elementary school teachers on the phenomena related to light and image, and to survey their perception change related to learning contents of optics. The subjects were selected from the elementary teachers who were enrolled in a graduate course, 'Science education seminar' at an education college located in Chungchungbuk-Do, South Korea. Among the five students who exposed their perceptions clearly in the class, the three of them were selected who agreed to the proposal of the case study. To achieve the purpose of this study, semi-structured interviews following the conception test with the 3 elementary teachers were conducted. During the analysis of the data, additional interviews by phone, e-mail, and internet messenger were conducted if necessary. According to the results, all of the elementary school teachers lacked the scientific conceptions of the phenomena related to light and image. Unfortunately, their learning experiences did not help them to understand the scientific concepts. During the interviews, the teachers recognized the importance of the viewpoints of seeing, image, cognition of light, point light source to understand the phenomena related to light and image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1424-1440
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• 2015

It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1055-1062
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• 2021

As face-to-face education becomes difficult due to the spread of COVID-19, the use of e-learning content and virtual training is increasing. In the case of information security education, practice to learn response techniques is important, so simulation hacking and vulnerability analysis activities have been supported as virtual training for a long time. In order to increase the educational effect, contents should be designed similar to real situation, and learning activities to achieve the learning goals should be designed. In addition, excellent functions and scalability of the system supporting learning activities are required. The researcher developed an LMS evaluation index that supports non-face-to-face education by considering the key elements of non-face-to-face education and training. The developed evaluation index was applied to the information security education platform to verify its practical utility.