• 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 smart convergence
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• v.7 no.1
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• pp.24-32
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• 2018

An outlier detection method using mixed prediction model has been described in this paper. The mixed prediction model consists of time-series model and regression model. The parameter estimation of the prediction model was performed using supervised learning and a genetic algorithm is adopted for a learning method. The experiments were performed in artificial and real data set. The prediction performance is compared with the existing prediction methods using artificial data. Outlier detection is conducted using the real sensor measurements in a dam. The validity of the proposed method was shown in the experiments.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.1
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• pp.97-102
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• 2011

Learning system on virtual environment gives the immersive feeling that lacks in existing E-Learning system, excites user's interest, and offers dangerous and expensive education contents. In this paper, we classified the learning categories into four classes: realtime lecture, anytime study, practice education, and the activity of study group. We built the on-line lecture system using Second Life that supports 3D virtual world and mixed reality. We provided virtual learning environment as running developed virtual world on-line lecture system.

• International Journal of Contents
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• v.5 no.1
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.619-624
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• 2014

This paper introduces a robot-based learning system which is designed to teach multiplication to children. In addition to a small humanoid and a smart device delivering educational content, we employ a type of mixed-initiative operation which provides enhanced multi-modal cognition to the r-learning system through human intervention. To investigate major factors that influence people's intention to use the r-learning system and to see how the multi-modality affects the connections, we performed a user study based on TAM (Technology Acceptance Model). The results support the fact that the quality of the system and the natural interaction are key factors for the r-learning system to be used, and they also reveal very interesting implications related to the human behaviors.

• The Journal of Sustainable Design and Educational Environment Research
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• v.2 no.1
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• pp.105-112
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• 2002

New buildings are to be needed for an aging society. But, there may be a solution on the multi-purpose & mixed-use existing facilities. Therefore this study is focused on verification of mixed-use school facilities's potentialities. If possible, I want to suggest some directions of renewal primary school planning. The results of this study are as follows : 1) It is important to make a policy for improving the educational environment, 2) Future buildings must be planned by the principles based on the lifelong learning, 3) Mixed-use building blocks need to be laid out by the concept of accessibility, 4) We can use existing primary school's areas as a elderly welfare facilities without any renovation and increasing areas.

• Journal of the Korean Chemical Society
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• v.66 no.6
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• pp.472-492
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• 2022

The purpose of this study was to investigate secondary science teachers' PCK components and subcomponents that are specific to online and offline learning environment. Data collection consisted of survey, class observation, and individual interviews of twelve science teachers. This study used a theoretical framework of PCK for deductive data analysis and articulated codes and themes through the following inductive analysis. Data analysis revealed that each of PCK components showed different specificity to the online and offline learning environment. And subcomponents of each PCK component were different according to the specificity of the online and offline learning environment. Teaching orientation toward science had a specific orientation for the online learning environment, i.e., 'learning science concept' and 'lecture centered instruction.' Knowledge of the science curriculum had online-offline mixed learning environment specific knowledge, i.e., 'reorganization of curriculum' and online learning environment specific knowledge, i.e., 'development of learning goal' and 'science curricular materials.' Knowledge of science teaching strategies had online learning environment specific knowledge, i.e., 'topic-specific strategy', 'subject-specific strategy', and 'interaction strategy' and COVID-19 offline learning environment specific knowledge, i.e., 'topic-specific strategy' and 'interaction strategy'. Knowledge of student science understanding had online learning environment specific knowledge, i.e., 'student preconception', 'student learning difficulty', 'student motivation and interest', and 'student diversity' and COVID-19 offline learning environment specific knowledge, i.e., student learning difficulty'. Knowledge of science assessment had online-offline mixed learning environment specific knowledge and online learning environment specific knowledge, i.e., assessment contents and assessment methods for each.

• Korean Institute of Interior Design Journal
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• v.17 no.1
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• pp.138-145
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• 2008

This study is conducted to formulate various spatial compositions for mixed-use elementary schools in order to use them as community centers. Accordingly, this study is conducted to analyze currently operating community-use elementary schools to find out about the current condition of mixed-use facilities, and the types of mixed-use facilities will be derived from the analysis. In addition, a more effective method of planning mixed-use elementary schools is investigated. By incorporating various educational curricula and teaching/learning activities, major points, which should be considered when planning elementary schools, will be suggested to effectively respond to the changes of educational environment in the future. The results show that in terms of inner traffic flow type, 9 schools out of the schools under study showed a unificated traffic flow type or a cross traffic flow type. When traffic overlaps, problems of noise, visual distraction, and decreased learning performance can appear. To prevent the conflict between areas and to manage areas effectively, each area should be differentiated by installing doors and shutters and by marking guides, and the facility used for community residents and students should also be scheduled separately to avoid time conflict. In addition, to accommodate the changes of users, flexible space planning options should be considered.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.74-81
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• 2006

In this paper, we deal with the separation of data by concurrently determined, piecewise nonlinear discriminant functions. Toward the end, we develop a new $l_1$-distance norm error metric and cast the problem as a mixed 0-1 integer and linear programming (MILP) model. Given a finite number of discriminant functions as an input, the proposed model considers the synergy as well as the individual role of the functions involved and implements a simplest nonlinear decision surface that best separates the data on hand. Hence, exploiting powerful MILP solvers, the model efficiently analyzes any given data set for its piecewise nonlinear separability. The classification of four sets of artificial data demonstrates the aforementioned strength of the proposed model. Classification results on five machine learning benchmark databases prove that the data separation via the proposed MILP model is an effective supervised learning methodology that compares quite favorably to well-established learning methodologies.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.19-28
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• 2020

Vehicle license plate recognition system is not generalized in Malaysia due to the loose character layout rule and the varying number of characters as well as the mixed capital English characters and italic English words. Because the italic English word is hard to segmentation, a separate method is required to recognize in Malaysian license plate. In this paper, we propose a mixed character level and word level English license plate recognition algorithm using deep learning neural networks. The difference of Gaussian method is used to segment character and word by generating a black and white image with emphasized character strokes and separated touching characters. The proposed deep learning neural networks are implemented on the LPR system at the gate of a building in Kuala-Lumpur for the collection of database and the evaluation of algorithm performance. The evaluation results show that the proposed Malaysian English LPR can be used in commercial market with 98.01% accuracy.