• Proceedings of the Korea Society for Industrial Systems Conference
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• 1996.10a
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• pp.29-48
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• 1996

Previous studies on user training have largely focused on assessing models which describe the determinants of information technology usage or examined theeffects of training, on user satisfaction, productivity, performance and so on. Scant research efforts have been made, however, to examine those effects of training by using theoretical models. This study presented a conceptural model to predict intention to use information technology and conducted an experimentto understand how training for computer skill acquisition affects primary variables of the model. The data were obtained from 32 student subjects of an experimental group and 31 students of a control group, and the information technology employed for this study was a university's electronic mail system. The study results revealed that attitude toward usage and perceived behavioral control helped to predict user intentions ; outcome expectations were positively related to attitude toward usage ; and self-efficacy was positively related to perceived behavioral control. Thd hands-on training for the experimental group led to increases in perceived ease of use, self-efficacy and perceived behaviroal control. The changes in those variables suggest more causal effects of user training than other survey studies.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.264-270
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• 2012

e-Training focusing on the experience and practice accelerates actual-active learning and enforces the learning effects against the existing theory based education. The most typical hans-on training system is augmented reality. Especially, in the training field installed augmented reality system, the automobile maintenance trainee experiences effective training with the immediate information, which is indicating the location of parts and the procedure of repairing. The tracking is the core technology of the augmented reality system. The performance of augmented reality system depends on the tracking technology. Therefore, this paper suggests the tracking technology which is proper to the e-Training augmented reality service technology for the car mechanics.

• The Journal of Korean Association of Computer Education
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• v.20 no.4
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• pp.37-46
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• 2017

Since 2018, the level of informatics education that is mandatory in junior high schools depends on the subject matter expertise of Informatics & Computer teachers. The purpose of this study is to analyze whether secondary teacher training institutes provide curriculum that guarantees the subjectivity of Informatics & Computer teachers. In order to achieve the goal, this study first compares curriculum courses for educating Informatics & Computer teachers of Korea secondary teacher training institutes with subjects based on the content system of J07-CS, the informatics education in Japan. Second, we compare the basic subjects offered by the Ministry of Education with the vocational subjects. Third, we analyzed the basic subjects of each university. As a result of the study, the number of informatics-related courses opened by Korean secondary teacher training institutions was insufficient compared to the number of subjects in J07-CS. Even though the standard of comparison was limited to basic subjects, the content elements were insufficient, and the ratio of the basic subjects of each university was low. In order to achieve the goal of informatics education from 2018, it is urgent to improve the curriculum of secondary education teachers.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.233-236
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• 2011

This paper proposes to use gesture recognition technology to develop 3D game for prevention of dementia. In the game, the user can choose camera mode or mouse mode to play game. In the game design, We focused on the characteristics of dementia, Developed four types of games, Including Memory training game, Math game, Logical training game and 3D visual sense training game. Each type of game is composed by a number of small games. Common feature of all the game is random, This ensures that when user play games, Basically the game will not have the same situation. For the older elderly, If can take 10 minutes a day to play the game and has always insisted on playing, For dementia preventive have a positive effect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4028-4042
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• 2021

Aiming at the problem of software defect prediction difficulty caused by insufficient software defect marker samples and unbalanced classification, a semi-supervised software defect prediction model based on a tri-training algorithm was proposed by combining feature normalization, over-sampling technology, and a Tri-training algorithm. First, the feature normalization method is used to smooth the feature data to eliminate the influence of too large or too small feature values on the model's classification performance. Secondly, the oversampling method is used to expand and sample the data, which solves the unbalanced classification of labelled samples. Finally, the Tri-training algorithm performs machine learning on the training samples and establishes a defect prediction model. The novelty of this model is that it can effectively combine feature normalization, oversampling techniques, and the Tri-training algorithm to solve both the under-labelled sample and class imbalance problems. Simulation experiments using the NASA software defect prediction dataset show that the proposed method outperforms four existing supervised and semi-supervised learning in terms of Precision, Recall, and F-Measure values.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.265-270
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• 2014

This study in coping with the current trend is to propose the environment for training 3-Tier App development being focused on the system to develop mobile applications where its related developers are scarce. Design and implementation of training system for the development of 3-Tier App in this paper is to realize the environment for software development for colleges as same as that in IT companies. For 3-Tier App development training system, 3 students with 3 computers work as a group. The above-mentioned 3 computers include a computer for development, Gateway server, and DB server together with legacy system. Also, each of the 3 students shall be given roles of the foregoing sections. We have educated 3-Tier App training system as a practical class for 64 students in junior students of computer information major. Through training session, it was confirmed that we can foster the students as custom-made talents who understand company's development environment. Also, the Comparison of 3-Tier and Stand-alone App Development Training System for 10 distinct description, we know that 3-Tier app development training system was very superior to stand-alone app development training system in the educational effects.

• Proceedings of the Korea Association of Information Systems Conference
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• 1996.11a
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• pp.29-48
• /
• 1996

Previous studies on user training have largely focused on assessing models which describe the determinants of information technology usage or examined the effects of training on user satisfaction, productivity, performance, and so on. Scant research efforts have been made, however, to examine those effects of training by using theoretical models. This study presented a conceptual model to predict intention to use information technology and conducted an experiment to understand how training for computer skill acquisition affects primary variables of the model. The data were obtained from 32 student subjects of an experimental group and 31 students of a control group, and the information technology employed for this study was a university's electronic mail system. The study results revealed that attitude toward usage and perceived behavioral control helped to predict user intentions; outcome expectations were positively related to attitude toward usage; and self - efficacy and perceived behavioral control. The changes in those variables suggest more causal effects of user training than other survey studies.

• Journal of the Korea Computer Industry Society
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• v.5 no.4
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• pp.415-426
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• 2004

Distance teacher training is on the increase raplidly because of its merit. But distance teacher training's weak points with its quantitative increasement has been proposed. Especially many study said commonly that distance tearcher training has weak points for contents, teaching method, evaluation method. So in this study, we will develop the teaching method of distance teacher training to solve weak points of distance teacher training with microteaching, cognitive apprenticeship model, teacher evaluation method. We think this teaching method will improve a teacher's teaching ability.

• Journal of the Korea Computer Industry Society
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• v.5 no.4
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• pp.517-530
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• 2004

Nowadays, there is need to teachers' in service education, beacuse of growing knowledge and information that teachers should know. So, Distance Teacher Training was widely spread. Nevertheless, inspite of strong point of Distance Teacher Training, there are some ploblems(interaction, evaluation, lecuterer, teaching material, etc). In order to solve this ploblems, we, in this article, explor some Distance Teacher Training Model and we show 8 factors that should considered when we develop Distance Teacher Training Model in the future. This factors should be a good guidance to develop distance teacher training model

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.45-50
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• 2020

A Language model with neural networks commonly trained with likelihood loss. Such that the model can learn the sequence of human text. State-of-the-art results achieved in various language generation tasks, e.g., text summarization, dialogue response generation, and text generation, by utilizing the language model's next token output probabilities. Monotonous and boring outputs are a well-known problem of this model, yet only a few solutions proposed to address this problem. Several decoding techniques proposed to suppress repetitive tokens. Unlikelihood training approached this problem by penalizing candidate tokens probabilities if the tokens already seen in previous steps. While the method successfully showed a less repetitive generated token, the method has a large memory consumption because of the training need a big vocabulary size. We effectively reduced memory footprint by encoding words as sequences of subword units. Finally, we report competitive results with token level unlikelihood training in several automatic evaluations compared to the previous work.