• Journal of the Korean Society of Earth Science Education
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• v.15 no.1
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• pp.62-75
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• 2022

In this study, experiential STEAM program using 3D printer was produced focusing on the content elements of 'solar' in the 2015 revised science curriculum, and in order to find out the effectiveness of the STEAM program, analyzed creative problem solving, STEAM attitude, and STEAM satisfaction by applying it to two middle school 77 students simple random sampled. The results of this study are as follows. First, a solar tactile model was produced using a 3D printer, and a program was developed to enable students to actively learn experience-oriented activities through visual impairment experiences. Second, in the response sample t-test by the difference in pre- and post-score of STEAM attitude tests, significant statistical test results were shown in 'interest', 'consideration', 'self-concept', 'self-efficacy', and 'science and engineering career choice' sub-factors except 'consideration' and 'usefulness / value recognition' sub-factors (p<.05). Third,, the STEAM satisfaction test conducted after the application of the 3D printer-based STEAM program showed that the average value range of sub-factors were 3.66~3.97, which improved students' understanding and interest in science subjects through the 3D printer-based STEAM program.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.51-63
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• 2023

The purpose of this study is to develop and implement a secondary teacher training program based on the TPACK model to strengthen the capacity of teachers of youth entrepreneurship education in the context of the increasing importance of entrepreneurship as a future competency, and to provide theoretical and practical implications based on it. To this end, a teacher training program was developed through the process of analysis, design, development, implementation, and evaluation based on the ADDIE model, and 22 secondary school teachers in Gangwon Province were trained and the effectiveness and validity were analyzed. First, the results of the paired sample t-test of TPACK in entrepreneurship education conducted before and after the program showed statistically significant improvements in all sub-competencies. Second, the satisfaction survey of the training program showed that the overall satisfaction was high with M=4.83. Third, the validity of the program was reviewed by three experts, and it was found to be highly valid with a validity of M=5.0, usefulness of M=4.7, and universality of M=5.0. Based on the results, it is suggested that in order to expand entrepreneurship education, opportunities for teachers' holistic capacity building such as TPACK should be expanded, teachers' understanding and practice of backward design should be promoted, and access to various resources that can be utilized in entrepreneurship education should be improved.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.219-231
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• 1996

The aim here is to analyse the system of description of GIS in all of the high school textbooks passed with the official approval, to find the degree to which teachers understand about GIS, and to consider the present condition of GIS instruction. Most of the authors of textbooks generally underestimate importance of GIS, and there is difference among their awareness. In the system of description of GIS, there are only a few kinds of textbooks in which explanation of GIS is made coherently from the purpose of instruction aim through the chapter summary and to overall test in both of the Korean Geography and the World Geography. This trend is due to the degree of distribution of the GIS specialists in writing a textbook while the other texts books shows just a brief introduction of GIS concept. Although there is the limit for teachers to study how to teach GIS due to its very technological aspect as well as few previous training and teacher's guide. Thus it is evident that about a half of teachers who responded taught high school students without a knowledge on GIS, and a few of them even never referred to that concept. These facts may negatively affect the status of a geography in the society of information. For the solution of these issues, it is considered how to repair the description system and its contents. Besides, the variation among textbooks is reduced at the further revision of the 7th curriculum. And the printed matters of GIS are sufficiently provided for the teachers to use as their teaching aids. It is desirable that the GIS instruction models should be further developed for college education, and the programs for the on-the-job teachers training should be arranged. Besides, the previous training for the on-the-job teachers should be achieved more practically with enough time before the revision of curriculum.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1283-1297
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• 2023

Mid-wave infrared (MWIR) imagery, due to its ability to capture the temperature of land cover and objects, serves as a crucial data source in various fields including environmental monitoring and defense. The KOMPSAT-3A satellite acquires MWIR imagery with high spatial resolution compared to other satellites. However, the limited spatial resolution of MWIR imagery, in comparison to electro-optical (EO) imagery, constrains the optimal utilization of the KOMPSAT-3A data. This study aims to create a highly visible MWIR fusion image by leveraging the edge information from the KOMPSAT-3A panchromatic (PAN) image. Preprocessing is implemented to mitigate the relative geometric errors between the PAN and MWIR images. Subsequently, we employ a pre-trained pixel difference network (PiDiNet), a deep learning-based edge information extraction technique, to extract the boundaries of objects from the preprocessed PAN images. The MWIR fusion imagery is then generated by emphasizing the brightness value corresponding to the edge information of the PAN image. To evaluate the proposed method, the MWIR fusion images were generated in three different sites. As a result, the boundaries of terrain and objects in the MWIR fusion images were emphasized to provide detailed thermal information of the interest area. Especially, the MWIR fusion image provided the thermal information of objects such as airplanes and ships which are hard to detect in the original MWIR images. This study demonstrated that the proposed method could generate a single image that combines visible details from an EO image and thermal information from an MWIR image, which contributes to increasing the usage of MWIR imagery.