• Journal of the Korean Chemical Society
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• v.60 no.2
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• pp.137-143
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• 2016

Effective teaching and learning is a continuous process of monitoring and re-organization of teaching method, so to benefit both students and educators. Reflective journal writing is an effective method for students to reflect on their learning experience about a new concept or subject taught and at the same time enables educators to improve on their academic skills. In the present paper, we have examined and evaluated the effectiveness of the Uncritical Inference Test (UIT) that was conducted in our basic organic chemistry course through a systematic network built based on students’ reflective writing. From the data analysis, the UIT has benefited students in three dimensions, namely cognitive, affective and group learning domains. Moreover, the UIT activity instilled an active learning environment in organic chemistry classroom and deeper learning among chemistry students as shown in the collected data. In future, this activity could be adapted as a teaching method to enhance students’ critical thinking skills and question-asking capability in other teaching courses.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.626-637
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• 2018

Human exchanges information not only through words, but also through body gesture or hand gesture. And they can be used to build effective interfaces in mobile, virtual reality, and augmented reality. The past 2D gesture recognition research had information loss caused by projecting 3D information in 2D. Since the recognition of the gesture in 3D is higher than 2D space in terms of recognition range, the complexity of gesture recognition increases. In this paper, we proposed a real-time gesture recognition deep learning model and application in 3D space using deep learning technique. First, in order to recognize the gesture in the 3D space, the data collection is performed using the unity game engine to construct and acquire data. Second, input vector normalization for learning 3D gesture recognition model is processed based on deep learning. Thirdly, the SELU(Scaled Exponential Linear Unit) function is applied to the neural network's active function for faster learning and better recognition performance. The proposed system is expected to be applicable to various fields such as rehabilitation cares, game applications, and virtual reality.

• The Journal of Sustainable Design and Educational Environment Research
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• v.9 no.3
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• pp.20-33
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• 2010

The purpose of this research is to investigate and analyze the recognition of students and teachers towards an influence of a subject classroom system to teacher's learning activities and student's learning attitude. The study was subjected to students and teachers at a school that has innovatively operated subject classroom system from before 2009. The results of the research are as follows. First, the result of investigation shows that the quality of class has been improved. The formats of managing class and class materials have become various. Second, there is an affirmative exchange in student's learning attitude, such as student's active participation, concentration, preparation and interest toward a class. Third, the fifty percent of teachers answered it that a block time system and intensive study system is required to manage an efficient subject classroom system. Lastly, the investigation shows that teachers and students are generally satisfied with running the subject classroom system. However, the satisfaction ratio of students is lower than the one of teachers.

• Journal of Engineering Education Research
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• v.13 no.1
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• pp.78-86
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• 2010

Training Curriculum Integrated Information Network is allowed to searching the all curriculums and courses related with training but also is a one stop handling integrated learning system to cover a course registration, learning and analysis of learning performance. Through developing and managing the Training Curriculum Integrated Information Network, it is available to get the various curriculum thus it is for trainers able to enforce the self oriented course choice and then high quality of training could be proposed by the diverse training curriculums and competitions. To manage Training Curriculum Integrated Information Network more effectively, active public relations marketing activities, high reliable correct information service and rich contents are required. It is essential to manage the learner and learning contents supplier, stable financial resources, personal security issue and protecting a copyright of training curriculum to be a successful network system.

• Journal of Gifted/Talented Education
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• v.13 no.2
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• pp.43-56
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• 2003

In this study, learning materials that can be applied for web-based distant learning model were developed based on the characteristics of elementary school science in which investigation skills and thinking ability are considered to be important. And the effect of students' activity in a discussion room on student's investigating and thinking ability was investigated. Through very active on-line discussion, students showed their ability to come up with new ideas and to design and implement diverse experimental methods. Especially, since all of the study tasks given to the students were aimed to utilize experimental means and tools that are so common in everyday life, shortfalls that might reside in the web-based distant learning program could be overcome and students' investigative activity might be stimulated.

• Knowledge Management Research
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• v.19 no.3
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• pp.173-187
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• 2018

This study was aimed at suggesting an integrative framework for creating collective intelligence and enhancing group performance after reviewing previous studies including those related to learning organizations, organizational learning, knowledge management, and collective intelligence. In the first, we examined that the similarities and differences between collective intelligence and other similar concepts, such as learning organizations, organizational learning, and knowledge management. Next, an integrative framework for creating collective intelligence and channeling it into strong group performance were suggested. In this process, we reviewed conditions for creating collective intelligence and segmented the major variables as expectancy, valence, and instrumentality, according to Vroom's (1964) expectancy theory. Characteristics of problems and the roles of leaders were respectively considered as valence for inducing collaboration and expectancy for managing probability to achieve goals. Instrumental factors were also adopted from conditions for creating group intelligence suggested from several researchers, such as creativity, openness, willingness for working together, horizontal communication, centralization in decision making, and building effective information and communication technology system and active usage of it. We discussed two potentially disputable matters about the scope and level of collective intelligence and group performance and suggest several theoretical and practical implications in the Discussion.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.74-81
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• 2017

Recently, there are many companies that use systems based on artificial intelligence. The accuracy of artificial intelligence depends on the amount of learning data and the appropriate algorithm. However, it is not easy to obtain learning data with a large number of entity. Less data set have large generalization errors due to overfitting. In order to minimize this generalization error, this study proposed DGA(Dropout Genetic Algorithm) which can expect relatively high accuracy even though data with a less data set is applied to machine learning based genetic algorithm to deep learning based dropout. The idea of this paper is to determine the active state of the nodes. Using Gradient about loss function, A new fitness function is defined. Proposed Algorithm DGA is supplementing stochastic inconsistency about Dropout. Also DGA solved problem by the complexity of the fitness function and expression range of the model about Genetic Algorithm As a result of experiments using MNIST data proposed algorithm accuracy is 75.3%. Using only Dropout algorithm accuracy is 41.4%. It is shown that DGA is better than using only dropout.

• Hwankyungkyoyuk
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• v.20 no.3
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• pp.31-44
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• 2007

The solution of the environment problem is the common issue all over the world, for this reason the necessity of the environmental education of school has emphasized. On this a variety method for environmental education is needed, this paper planned and applied the 'ecology & environment' for high school which are based on GBS theory and presented a new model of environment education. GBS(Goal-Based Scenario) is that learners are presented with an end goal that is motivating and challenging. This goal is structured such that, in order to successfully meet it learners are required to build a predetermined core set of skills and knowledge by process mission and scenario. GBS is an active learning environment in which learners are trained in study that have a real-world context. When they are back in real-world they have increased ability to apply what was learned by reflecting on the GBS learning experience. This study was designed on GBS theory and taught a class by using internet Blog. As a result, when carefully reviewing the materials such as final presentation reflect journal, we conclude that the students' awareness of a learning environment is improved and the students seems to try to apply the learning outcome to a real life.

• Korean Journal of Artificial Intelligence
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• v.7 no.2
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• pp.19-24
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• 2019

Lung cancer is a chronic disease which ranks fourth in cancer incidence with 11 percent of the total cancer incidence in Korea. To deal with such issues, there is an active study on the usefulness and utilization of the Clinical Decision Support System (CDSS) which utilizes machine learning. Thus, this study reviews existing studies on artificial intelligence technology that can be used in determining the lung cancer, and conducted a study on the applicability of machine learning in determination of the lung cancer by comparison and analysis using Azure ML provided by Microsoft. The results of this study show different predictions yielded by three algorithms: Support Vector Machine (SVM), Two-Class Support Decision Jungle and Multiclass Decision Jungle. This study has its limitations in the size of the Big data used in Machine Learning. Although the data provided by Kaggle is the most suitable one for this study, it is assumed that there is a limit in learning the data fully due to the lack of absolute figures. Therefore, it is claimed that if the agency's cooperation in the subsequent research is used to compare and analyze various kinds of algorithms other than those used in this study, a more accurate screening machine for lung cancer could be created.

• Fashion, Industry and Education
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• v.14 no.1
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• pp.50-58
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• 2016

Passive learning attitudes and lack of enthusiasm in a retailing math course is quite common and a significant number of students do express their frustrations and struggles by seeking extra help outside the classroom. In order to promote students' active participation in class and to improve their performance and overall satisfaction with the course, a modified team-based learning (TBL) method was implemented in a retailing math course in two consecutive semesters. Implementing TBL into a retailing math course would improve students' accountability for their own learning, increase student interactions and engagement, and develop teamwork and collaboration skills. The scores on the midterm and final tests indicated that students' performance improved especially for the students who scored below 80% on each test when TBL was implemented. Students' reflection on the TBL activities done in class throughout the semester indicated that these TBL activities help them solidify the concepts taught in class better. They were able to realize their own mistakes and other group members who got the question right helped them understand. To maximize the benefit of TBL, it is suggested to implement TBL within the flipped classroom. Further research is called for to evaluate the effect of TBL on long-term knowledge retention among college students.