• Journal of the Korean Society of Earth Science Education
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• v.6 no.2
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• pp.152-158
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• 2013

The purpose of this work is to investigate pre-service elementary teachers' belief in science gifted education. To do that, from September to November 2012, this research had been conducted with 42 students who were in the third year of P University of Education. The conclusions of this work are presented as follows: First, the pre-service elementary teachers considered exploration ability to be the most important talent for the gifted students in science, and chose task commitment as the next most important. They regarded intelligent ability and leadership ability as the relatively less important. Secondly, regarding the most important tool in choosing scientifically gifted students, the pre-service elementary teachers preferred creativity test. It was found that they considered the intelligence test and academic achievements, which require intelligent ability, to be the less important. Thirdly, regarding the special knowledge related to science gifted education, the pre-service elementary teachers considered pedagogical knowledge about the gifted to be the most important. Fourthly, regarding a class type for gifted students in science, the pre-service elementary teachers most preferred project learning. Project learning is a learning method in which students choose an interesting problem and solve the problem in cooperation with group members. It is the most widely used exploration class in gifted education. It is in the same context as the result that exploration ability is the most important factor to elementary gifted students in science. This work revealed that, with regard to a talent for the gifted in science, judgment of the gifted in science and science gifted education, the potential ability and affective ability of gifted students are considered to be more important than their intelligent ability. Therefore, it was analyzed that pre-service elementary teachers' belief in the gifted students in science is almost consistent with the recent trend of gifted education.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.291-302
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• 2018

The purpose of this study is to investigate pre-service middle school earth science teachers' perceptions about the learning of geological field trip. The study sample consists of 39 undergraduate students at the university located in a metropolitan city. Additionally, 4 pre-service earth science teachers are semi-structure interviewed. The instrument of the study includes a 5-category perception about the learning of geological field trip, which consists of needs, educational values, educational experience, teaching methods, and training for learning. The results are as follows. First, participants are important to the need and educational values of learning about the geological field trip regardless of gender and grade level. Second, all participants have experienced geological field trip in college. They have more opportunities to experiment for field trip as they advance to higher grade. There is significant difference between lower and higher graders in terms of the goal of learning about geological field trip. It needs a new lesson model to teach geology between men and women regarding teaching methods category. In order to practice geological field trip in school, participants perceive that they need the knowledge of geological context, experiment of field trips, and how to teach geological field trip to students. This study suggests that pre-service earth science teachers' perceptions include how to teach and learn geological field trip during their college year.

• Korean journal of medical education
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• v.30 no.4
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• pp.339-346
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• 2018

Purpose: The purpose of this study was to examine whether non-cognitive student attributes such as learning style and personality type affected academic performance in a flipped learning classroom of a pre-dental undergraduate science course. Methods: 'Biodiversity and Global Environment,' a 15-week, 3-credit course, was designed as a flipped class in Seoul National University School of Dentistry in 2017. Second-year pre-dental students were required to enroll in the course and to engage in online learning and in-class discussion. The Kolb's Learning Style Inventory and the Myers-Briggs Type Indicator were conducted to measure non-cognitive student factors. Independent samples t-test and multivariate regression analyses were used to examine the relationships between self-rated measurements and academic achievement. Results: More than half of the students enrolled in the flipped science course had an assimilator learning style (50%), followed by convergers (24%), accommodators (16%), and divergers (10%), and their personality types were dominated by the introverted, sensing, thinking, and judging types, respectively. Examining group differences using the t-test demonstrated a significant relationship between the diverger group and higher academic success. In particular, the multivariate regression analysis indicated that both thinking types and female students performed better in discussion than feeling types and male students. Conclusion: To operate the flipped learning classroom more effectively in medical and dental education, the instructor should carefully develop and apply a more tailored facilitation and relevant assessment by considering student learning styles and personality types.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2073-2081
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• 2021

Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.

• Journal of Korean Elementary Science Education
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• v.25 no.2
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• pp.191-205
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• 2006

The purpose of this study was to explore strategies used by pre-service elementary science teachers in planning a science lesson. The participants were six senior students from a national university of education located in the midwestern area of Korea. Data regarding their planning strategies were gathered through both thinking-aloud and observation. Research findings suggest that: three of the teachers had little understanding of the necessity of reviewing unit contents or prior learning for planning a science lesson; five student teachers relied heavily on learning objectives presented in teachers' guidebooks without considering their appropriateness; all teachers exhibited an intention of composing different activities or teaching approaches from teachers' guidebooks; only two teachers thought about learners' prior knowledge or understanding levels; five and three teachers had poor understanding of discovery learning models and importance of teacher's questioning, respectively; and five teachers paid little attention to assessment.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.1025-1031
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• 2000

Pre-existing pattern recognition techniques, in the case of character recognition, have limited on the application field. But CAI character learning system and writer's recognition system are very important parts. The application field of pre-existing system can be expanded in the content that the learning of characters and the recognition of writers in the proposed paper. In order to achieve these goals, the development contents are the following: Firstly, pre-processing method by understanding the image structure is proposed, secondly, recognition of characters are accomplished b the histogram distribution characteristics. Finally, similarity measure functions are defined from standard character pattern for matching of the input character pattern. Also the effectiveness of this system is demonstrated by experimenting the standard primitive image.

• Research in Mathematical Education
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• v.11 no.4
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• pp.221-234
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• 2007

A comparison of mathematics teachers' personal beliefs between in- and pre-service teachers for Chinese secondary schools (grades 7-12) about mathematics theories, teaching and learning has been studied. In-service teachers' beliefs are close to constructivist's aspect and pre-service teachers' beliefs are close to absolutist's views. Based on the results, we give some suggestions to both teacher education and in-service teachers' training.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.119-128
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• 2022

Recently, due to the development of related technologies for autonomous vehicles, driving work is changing more safely. However, the development of support technologies for level 5 full autonomous driving is still insufficient. That is, even in the case of an autonomous vehicle, the driver needs to drive through forward attention while driving. In this paper, we propose a method to monitor driving tasks by recognizing driver behavior. The proposed method uses pre-trained deep convolutional neural network models to recognize whether the driver's face or body has unnecessary movement. The use of pre-trained Deep Convolitional Neural Network (DCNN) models enables high accuracy in relatively short time, and has the advantage of overcoming limitations in collecting a small number of driver behavior learning data. The proposed method can be applied to an intelligent vehicle safety driving support system, such as driver drowsy driving detection and abnormal driving detection.

• English Language & Literature Teaching
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• v.18 no.3
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• pp.93-120
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• 2012

This paper aims to address the gains and losses of the CMC environment in Language learning. Data were attained from twelve middle school ESL students who took English as a second language class and twelve pre-service teachers taking ESL foundation course. This exploration describes the role of CMC focusing on its' advantages and disadvantages which language teachers need to consider. The findings revealed that the teachers, tasks, and other elements involved in the CMC environment provided several gains and losses for many areas of learning. This implies that CMC alone does not provide an optimal learning environment, but rather it is used as an essential tool in providing opportunities to enhance language learning. Several suggestions are made for teachers and pre-service teacher education how CMC instruction might be better designed. The paper concludes with some practical considerations for future research in the area of CMC.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.223-229
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• 2021

Classification of different blood cell types is an essential task for human's medical treatment. The white blood cells have different types of cells. Counting total White Blood Cells (WBC) and differential of the WBC types are required by the physicians to diagnose the disease correctly. This paper used transfer learning methods to the pre-trained deep learning models to classify different WBCs. The best pre-trained model was Inception ResNetV2 with Adam optimizer that produced classification accuracy of 98.4% for the dataset comprising four types of WBCs.