• Geomechanics and Engineering
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• v.30 no.6
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• pp.489-502
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• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.591-614
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• 2023

For a long time, mathematics education institutions such as NCTM(National Council of Teachers of Mathematics) have emphasized the essential role of writing, and recent surveys by the Ministry of Education report a decline in foundational academic skills in the post-COVID19 period. The purpose of this study is to redefine the significance of mathematics writing in mathematics education, focusing on competencies highlighted in the field, particularly in the areas of problem-solving, communication, and reasoning. The research findings indicate that writing in problem-solving enhances cognitive organization, fostering the ability to grasp concepts and methods. Writing in communication builds confidence through the meta-cognitive process, and writing in inference allows self-awareness of step-by-step identification of areas lacking understanding. Particularly in the future society where artificial intelligence(AI) is utilized, changes in the learning environment necessitate research for the establishment of authenticity judgment through writing and the cultivation of a proper writing culture.

• Journal of The Korean Association For Science Education
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• v.36 no.1
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• pp.15-28
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• 2016

The purpose of this study is to investigate the changes of students' modeling ability in terms of 'meta-modeling knowledge' and 'modeling practice' through co-construction of scientific model. Co-construction of scientific model instructions about astronomy were given to 41 middle-school students. The students were given a before and after instruction modeling ability tests. The results show that students' 'meta-modeling knowledge' has changed into a more scientifically advanced thinking about models and modeling after the instruction. Students were able to be aware that 'they could express their thoughts using models', 'many models could be used to explain a single phenomena' and 'scientific models may change' through co-construction modeling process. The change in the 'modeling practice' of the students was divided into four cases (the level improving, the level lowering, the high-level maintaining, the low-level maintaining) depending on the change of pre-posttest levels. The modeling practice level of most students has improved through the instruction. These changes were influenced by co-construction process that provides opportunities to compete and compare their models to other models. Meanwhile, the modeling practice level of few students has lowered or maintained low level. Science score of these students at school was relatively high and they thought that the goal of learning is to get a higher score in exams by finding the correct answer. This means that students who were kept well under traditional instruction may feel harder to adapt to co-construction of scientific model instruction, which focuses more on the process of constructing knowledge based on evidences.

• Information Systems Review
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• v.18 no.1
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• pp.57-78
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• 2016

Hacking has raised many critical issues in the modern world, particularly because the size and cost of the damages caused by this disruptive activity have steadily increased. Accordingly, many significant studies have been conducted by behavioral scientists to understand hackers and their practices. Nonetheless, only qualitative methods, such as interviews, meta-studies, and media studies, have been employed in such studies because of hacker sampling limitations. Existing studies have determined that intrinsic motivation was the dominant factor influencing hackers, and that their techniques were mainly acquired from online hacking communities. However, such results have yet to be causally proven. This study attempted to identify the causal factors influencing the motivational and environmental factors encouraging hackers to learn hacking skills. To this end, hacker community members using the theory of planned behavior were observed to identify the causal factors of their learning of hacking skills. We selected a group of students who were developing their hacking skills. The survey was conducted over a two-week period in May 2015 with a total of 227 students as respondents. After list-wise deletion, 215 of the responses were deemed usable (94.7 percent). In summary, the hackers were aware that hacking skills are considered socially unethical, and their attitudes toward the learning of hacking skills were affected by both intrinsic and extrinsic motivations. In addition, the characteristics of the online hacking community affected their perceived behavioral control. This study introduced new concepts in the process of conducting a causal relationship analysis on a hacker sample. Moreover, this research expanded the discussion on the causal direction of subjective norms in unethical research, and empirically confirmed that both intrinsic and extrinsic motivations affect the learning of hacking skills. This study also made a practical contribution by raising the educational and policy response issues for ethical hackers and demonstrating the necessity to intensify the punishment for hacking.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Journal of The Korean Association For Science Education
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• v.35 no.2
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• pp.313-323
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• 2015

The purpose of this study is to investigate the cognitive process of student's modeling on a modeling-emphasized argument-based general chemistry experiment. The participants were twenty-one freshman students. Six topics were carried out during the first semester and semi-structured interview was implemented at the end of the semester. Semi-structured interview questions were used to elicit elements of effective model, modeling strategies, difficulties that students have experienced during modeling, and resolving the difficulties that students have experienced during modeling. All student interview data were collected and transcribed. The results of this study are summarized as follows: (1) Elements of effective model were considered to be visual expression, persuasive explanation, and rhetorical structure. (2) Modeling strategies included arranging important keywords or writing the outline, and during the modeling process, students used various data, suggested data after reconstructing, suggested definitions and explanations of core concepts, used meta-cognition, and considering rhetorical structure. (3) Difficulties students have experienced during modeling could be categorized as lack of modeling strategy and understanding. (4) Resolving difficulties students have experienced during modeling could be categorized as modeling strategy and understanding. Students learn the strategy by feedback, modeling experience, evaluation of experimental report, models which they constructed previously and references, and the understanding of contents were achieved through arguments which occurred during classes and during the process of writing the experimental reports. These results suggest that when using modeling in teaching and learning, the argument-based learning strategy can be effective in enhancing students' modeling by helping them to understand meta-modeling with scientific concepts.

• Journal of the Korean School Mathematics Society
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• v.10 no.2
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• pp.149-171
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• 2007

This study is aimed at development of pedagogical content knowledge on fraction in the elementary school mathematics. Elementary students regard fraction as the difficult topic in school mathematics. Furthermore, fraction is the fundamentally important concept in studying mathematics. So it is important to develop the pedagogical content knowledge on fraction. The reason of attention to the pedagogical content knowledge is that improving the quality of teaching is the central focus of a high quality mathematics education. Shulman suggested that various knowledges are required for teacher to improve their classes. Of course, pedagogical content knowledge is the most valuable in teaching mathematics. Pedagogical content knowledge is related to the promotion of students' understanding about the learning. Pedagogical content knowledges are categorized by five factors in this study. These are understanding about curriculum, understanding about students and students' knowledge, understanding about teachers and teachers' knowledge, understanding about the methods, contents, and management of class, and understanding about methods of assessments. I develop the pedagogical content knowledge on fraction according to the these categories. I concentrate on the two types of pedagogical content knowledges in developing. That is, I present knowledges which teachers have to know for teaching fraction effectively and materials which teachers can use during the teaching fraction. Pedagogical content knowledges guarantee teachers as the professionalists. Teachers should not teach only content knowledges but teach various knowledges including the meta-knowledges which have relation to fraction.

• Journal of the Korean Chemical Society
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• v.64 no.5
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• pp.277-290
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• 2020

In this study, four gifted students in the second year of middle school at Gifted Education Center of the National University in Jeollanam-do were surveyed students' perceptions of the effectiveness of science class using science writing heuristic in terms of metacognition and the goals of the 2015 revised science curriculum. Through questionnaires and interviews with gifted science students, science gifted students recognized that the science class using science writing heuristic had a positive effect on the four subdomains (planning, monitoring, control, and evaluation) of metacognition. For this reason, the science gifted students presented self-directed experience in designing experiments, continually checking the collected experimental data, feedback process, and reflecting experience in preparing conclusions. Science gifted students recognized that science class using science writing heuristic had a positive effect on the goals of the 2015 revised science curriculum(attitudes, inquiry, knowledge, Science·Technology·Society(STS), and the enjoyment and usefulness of science learning) that correspond to through inquiry science writing lessons. For this reason, the science gifted students presented self-directed inquiry experiences, continual inquiry experiences on the same subject, thinking process at each stage of inquiry, learning experiences through inquiry, experience of the whole inquiry process, and inquiry of phenomena closely related to real life. Therefore, for the effective science class, it is necessary to apply the characteristics of science class using science writing heuristic which is responded by science gifted students to general science class as well as science gifted class later.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• Journal of Korean Home Economics Education Association
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• v.34 no.1
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• pp.35-57
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• 2022

This study developed an 'Eco-friendly Clothing Life Cycle' class applying gamification. And the effect of and learners' satisfaction on the class were examined after implementation. The developed class was applied to 40 sophomore students from "A" high school in Gyeonggi-do from February 3, 2022, to February 10, 2022, in a total of 4 sessions. The class was conducted in the stages of production-distribution-consumption-disposal, and was conducted in a way that a mission is solved after learning in Gather Town. It is designed so that learners continuously repeat learning until they accomplish the mission. The learners completed pre-class and post-class questionnaires. And a focus group interview was conducted with a randomly selected group of three learners. According to the pre-/post-class test comparison, the gamification class on the theme of "Eco-friendly Clothing Life Cycle" was found not to have a significant effect on learners' immersion or self-directed learning attitudes. However, in the case of the learners with high levels of non-immersion tendency, the level of immersion in the class increased, and the satisfaction level was positively associated with the level of immersion and self-directed attitude. Learners expressed 'concern' and 'expectation' about the gamification class, and said that although the developed class was using a 'new teaching method', 'appropriate use' was necessary. And learners were evaluated this class as a 'student-centered class' and acknowledged that it allowed 'self-directed learning'. The teacher who implemented the class said that this class was more effective in attracting students' expectations and interests compared to the conventional classes, and that the class in the meta-verse environment was perceived as a new type of class in the non-face-to-face era. The teacher also mentioned that when applied to the actual educational field, a detailed design is needed that allows the learners to proceed smoothly, and the role of the teacher in the class was more important. And the teacher also mentioned that the class should be properly designed so that the expectations given by the 'game' do not obscure the essence of the class.