• Knowledge Management Research
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• v.15 no.4
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• pp.147-170
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• 2014

This study investigates the main characteristics of Chinese automobile industry based on the technology learning, architecture theory and cluster. As a case study sample, we chose three most representative automobile firms from three main cities in China, FAW from northern part of China, SAIC from middle part of China, and BYD from southern part of China. According to the research findings, FAW has equipped self-production ability in virtue of political support but felled behind in future transportation due to lack of convergence with local cluster. In case of SAIS, similar phenomenon happened in spite of highest purchasing power of shanghai. BYD has achieved great quantum jump through the aggressive investment strategy in electric vehicle even though there are still many technological learning and experience to be cumulated. Overall, this research extends the current literature on key roles (technological learning, architecture, and cluster features) in the automobile industry growth by suggesting their crucial aspects in knowledge management and strategic planning to a newly emerging market, China, and sheds light on the relationship between regional characteristics and automobile growth.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.419-426
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• 2024

Due to the government's announcement of the 2025 policy mandating coding education, there is a growing need for effective coding learning methods in elementary education. However, there are few methods available that can easily help younger students understand coding. While text-based coding and visual block coding methods exist, they have limitations. To address these issues, we propose a block coding learning platform that combines virtual reality (VR) technology with gamification elements. The traditional two dimensional (2D) block coding methods have some limitations, so this platform aims to overcome these by providing an environment where learners can intuitively understand and experience coding in a three dimensional (3D) virtual space. The primary goal is to enhance immersive, learner-centered experiences and improve creative problem-solving skills and computational thinking. This study proposes an experimental approach to demonstrate the effectiveness of a learning platform that combines VR technology with block coding. Furthermore, we expect that the VR-based platform will significantly contribute to improving the quality of education and promoting self-directed learning among students.

• The Journal of Korean Association of Computer Education
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• v.21 no.6
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• pp.27-37
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• 2018

In this paper, we propose a design and development method of an elevator simulator that can be used as an embedded application layer software learning tool and a teaching and learning method using it. The simulator provides students with an environment to implement the operating principle and control method of the elevator system in the application layer excluding the issues of hardware and embedded OS layer. This allows students to have a reactive and real-time embedded application development experience. In addition, we present a four-week embedded application software training course with hands-on exercises that add step-by-step functionality using a simulator. As a result of training for actual students, we obtained 83.3 points of learning achievement score and proved that the curriculum has a significant effect on embedded application learning.

• Asia-Pacific Journal of Business
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• v.12 no.4
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• pp.13-40
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• 2021

Purpose - The purpose of this study is to predict corporate corruption in emerging markets such as Brazil, Russia, India, and China (BRIC) using different machine learning techniques. Since corruption is a significant problem that can affect corporate performance, particularly in emerging markets, it is important to correctly identify whether a company engages in corrupt practices. Design/methodology/approach - In order to address the research question, we employ predictive analytic techniques (machine learning methods). Using the World Bank Enterprise Survey Data, this study evaluates various predictive models generated by seven supervised learning algorithms: k-Nearest Neighbour (k-NN), Naïve Bayes (NB), Decision Tree (DT), Decision Rules (DR), Logistic Regression (LR), Support Vector Machines (SVM), and Artificial Neural Network (ANN). Findings - We find that DT, DR, SVM and ANN create highly accurate models (over 90% of accuracy). Among various factors, firm age is the most significant, while several other determinants such as source of working capital, top manager experience, and the number of permanent full-time employees also contribute to company corruption. Research implications or Originality - This research successfully demonstrates how machine learning can be applied to predict corporate corruption and also identifies the major causes of corporate corruption.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.209-215
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• 2018

The college liberal arts mathematics is opened as a required course in science and engineering field, but students with low achievement experience difficulty in learning. Therefore, flip learning, which is well known as an effective teaching method based on self-led and learner, is suggested as an alternative. However, some problems are pointed out in this pedagogy. As an alternative to flip learning, we apply flip PBL classes that apply PBL to flip learning to general math subjects to supplement the problems of existing flip learning classes and increase interest in mathematics I want to know the effectiveness of whether it can be done. In this study, we investigated the educational effectiveness of the comparison study between the experimental group applying flip PBL class and the control group applying the existing flip learning class. First, the experimental group showed higher than the control group by 22 points Second, in the reflection journal analysis, in contrast to the control group, there was a positive effect on the improvement of the interest of the mathematics in the experimental group, It is expected that it will be applied as a teaching method that can complement the learning.

• Journal of Fisheries and Marine Sciences Education
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• v.17 no.3
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• pp.373-382
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• 2005

The aim of this study is to analyze critically the meaning of 'good instruction'. In this article, the researchers emphasized the activities of teaching and learning as two essential elements of good instruction. The antecedent studies on good instruction have limitations in that they regarded good instruction as an instrument rather than valuable activity itself. This study consisted of three parts. Firstly, the researchers tried to clarify the meaning of good instruction underlying antecedent studies on instruction. Secondly, the researchers tried to analyze characteristics of good insturction suggested by antecedent studies. Thirdly, the researchers attempted to define a new meaning of good instruction. A new meaning of good instruction should be defined in accordance with characteristics of three commonplaces composing instruction such as teaching activity, learning activity and good interactions between teacher and learner. Good instruction can be defined as followings. Good instruction means an instructional activity which can change the student's meanings of experience as a result of interactions among teacher, learner, and educational materials.

• Korean Journal of Clinical Pharmacy
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• v.27 no.2
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• pp.55-62
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• 2017

Experiential education is a core curriculum of pharmacy education. In experiential education, formative feedback is an integral component of learning and teaching process. Feedback is defined as information provided by a preceptor regarding student's performance based on direct observation. With effective feedback, students can have opportunities to reinforce or correct behaviors and to acquire knowledge or skills. Students highly value and appreciate feedback. They rank provision of effective feedback as one of the most important qualities of preceptors. Preceptors, however, lack an understanding of feedback or practical skills necessary for providing effective feedback. As a result in reality, the feedback provided to students can be differentially effective in improving students' learning. This article describes a theoretical understanding of feedback including definition and value, as well as types of feedback. In addition, practical aspects in providing feedback, such as contents, timing, techniques, and models, are addressed. By understanding the value of feedback and mastering various feedback skills, preceptors will promote students' learning and enhance educational outcomes of experiential education.

• Journal of Digestive Cancer Research
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• v.11 no.3
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• pp.130-140
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• 2023

Gastric cancer (GC) is one of the most common malignant tumors worldwide, with a 5-year survival rate of < 40%. The diagnosis and treatment decisions of GC rely on human experts' judgments on medical images; therefore, the accuracy can be hindered by image condition, objective criterion, limited experience, and interobserver discrepancy. In recent years, several applications of artificial intelligence (AI) have emerged in the GC field based on improvement of computational power and deep learning algorithms. AI can support various clinical practices in endoscopic examination, pathologic confirmation, radiologic staging, and prognosis prediction. This review has systematically summarized the current status of AI applications after a comprehensive literature search. Although the current approaches are challenged by data scarcity and poor interpretability, future directions of this field are likely to overcome the risk and enhance their accuracy and applicability in clinical practice.

• Journal of Engineering Education Research
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• v.17 no.6
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• pp.62-68
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• 2014

The purpose of this work is to provide systematic lecture materials for instructers who search for the effective teaching of applied mechanics of materials course with respect to lecture contents, teaching methods, and itemized course evaluations according to each class learning objective. For this. the evolution of teaching contents since 2010 until 2014 are briefly depicted and then most recent course learning objectives, lecture contents, and evaluation schemes are presented in detail. The results of this study may be used as base line data for the lecturers who teach similar courses and for the evaluation of program outcomes in ABEEK scheme through course-embedded assessment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.79-86
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• 2024

In this paper, we propose a virtual learning platform based on various interactions that occur during real class activities, rather than the existing content delivery-oriented learning metaverse platform. In this study, we provide a learning environment that combines AI and a virtual environment to solve problems by talking to real-time AI. Also, we applied G-learning techinques to improve class immersion. The Virtual Edu platform developed through this study provides an effective learning experience combining self-directed learning, simulation of interest through games, and PBL teaching method. And we propose a new educational method that improves student participation learning effectiveness. Experiment, we test performance on learninng activity based on real-time video classroom. As a result, it was found that the class progressing stably.