• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.235-243
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• 2019

Universities are opening related majors and subjects to nurture the problem-solving fusion that businesses want. The time has come when rapid technological. On this thesis, we analyzed three years (2017-2019) of survey result of Women University students in order to figuring out and dealing with the change in 4th industrial revolution and intellectual information technology. It turns out that 1) there was an increase of interest in 4th industrial revolution from 59% in 2017 to 80% in 2019, 2) IoT, ICT, Artificial Intelligence, and Education Research System became top priority in technical strategy, 3)the prime keyword is AI, robot, job, 4)the expectation on increasing of the opportunity and the number of jobs in science technology field was 50%, 5)the importance of universities and companies was 50%, 80% each, 6) the information needed for science technology were educational discipline, change in future science, prospective future information in order, and 7)the most needed education were education on creativity, coding, cross-subject, engineering in order. In the era of the fourth industrial revolution, it is essential to expand the SW manpower base in various fields. University education, which should provide connectivity for super-fusion, should provide curriculum optimized for industrial demands such as, fusion and connected education, creative thinking, self-directed problem solving and etc.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.473-481
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• 2020

Data science starts with small data analysis and includes machine learning and deep learning for big data analysis. Data science is a core area of artificial intelligence technology and should be systematically reflected in the school curriculum. For data science education, The Entry also provides a data analysis tool for elementary education. In a big data analysis, data samples are extracted and analysis results are interpreted through statistical guesses and judgments. In this paper, the big data analysis area that requires statistical knowledge is excluded from the elementary area, and data science education examples focusing on the elementary area are proposed. To this end, the general data science education stage was explained first, and the elementary data science education stage was newly proposed. After that, an example of comparing values of data variables and an example of analyzing correlations between data variables were proposed with public small data provided by Entry, according to the elementary data science education stage. By using these Entry data-analysis examples proposed in this paper, it is possible to provide data science convergence education in elementary school, with given data generated from various subjects. In addition, data science educational materials combined with text, audio and video recognition AI tools can be developed by using the Entry.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.95-103
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• 2023

This paper proposes an artificial intelligence convergence education program for teaching the main concept and principle of Support Vector Machines(SVM) at elementary schools. The developed program, based on Jeju's natural environment theme, explains the decision boundary and margin of SVM by vertical and parallel from 4th grade mathematics curriculum. As a result of applying the developed program to 3rd and 5th graders, most students intuitively inferred the location of the decision boundary. The overall performance accuracy and rate of reasonable inference of 5th graders were higher. However, in the self-evaluation of understanding, the average value was higher in the 3rd grade, contrary to the actual understanding. This was due to the fact that junior learners had a greater tendency to feel satisfaction and achievement. On the other hand, senior learners presented more meaningful post-class questions based on their motivation for further exploration. We would like to find effective ways for artificial intelligence convergence education for elementary school students.

• The Mathematical Education
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• v.63 no.2
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• pp.165-186
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• 2024

Despite the growing attention on artificial intelligence-based automated scoring technology as a support method for the introduction of descriptive items in school environments and large-scale assessments, there is a noticeable lack of foundational research in mathematics compared to other subjects. This study developed an automated scoring model for two descriptive items in first-year middle school mathematics using the Random Forest algorithm, evaluated its performance, and explored ways to enhance this performance. The accuracy of the final models for the two items was found to be between 0.95 to 1.00 and 0.73 to 0.89, respectively, which is relatively high compared to automated scoring models in other subjects. We discovered that the strategic selection of the number of evaluation categories, taking into account the amount of data, is crucial for the effective development and performance of automated scoring models. Additionally, text preprocessing by mathematics education experts proved effective in improving both the performance and interpretability of the automated scoring model. Selecting a vectorization method that matches the characteristics of the items and data was identified as one way to enhance model performance. Furthermore, we confirmed that oversampling is a useful method to supplement performance in situations where practical limitations hinder balanced data collection. To enhance educational utility, further research is needed on how to utilize feature importance derived from the Random Forest-based automated scoring model to generate useful information for teaching and learning, such as feedback. This study is significant as foundational research in the field of mathematics descriptive automatic scoring, and there is a need for various subsequent studies through close collaboration between AI experts and math education experts.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.229-238
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• 2020

Upcoming 4th industrial revolution era and the post-covid19 made procedure, contents, and the ways of education innovative changes. Thesis analyzed the changes of educational procedures of universities unsing Bigkinds of 'KPF', (which is Korea Press Foundation) and DataLab system of 'Naver'. The following three results were derived from relational analysis, monthly keyword trend, and related word analysis with 633 cases searched for the keyword of "university curriculum innovation, creativity, and convergence." Firstly, the frequency of relationship keyword analysis of recent 4 years(2016~2020) was ministry of education(190), industrial revolution(154), system(137), career(136), global(131), smart(97), and enrolled students(95) in order. Secondly, The frequency of keywords related to the related words was Human Resources Development (136), Industrial-Academic Cooperation (119), Education Ministry (86), Specialization (69), and LiNC (62), which showed the importance of supporting the government (Ministry of Education) and fostering human resources, industry-academic cooperation, LiNC, and characterization in order to foster human resources in universities. According to this study, the paradigm of education is the artificial intelligence environment of the fourth industrial revolution, which is meaningful in presenting the direction of specialization, industry-academic cooperation, smart, and globalization, and the future direction of education that fosters creative talent in the era of the fourth industrial revolution.

• Communications of Mathematical Education
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• v.35 no.3
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• pp.213-231
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• 2021

This study is intended to investigate contents related to parents' perception and satisfaction level of school mathematics curriculum. Based on the results, this study intended to deduce implications for mathematics education in schools, child education, and parent education. According to the result of the survey, the more positively the parents perceived the value of the mathematics learning, the more positively the child perceived, and the higher the parent's participation rate in mathematics-related education was. In terms of perception of teaching and learning activities, it showed that the willingness to participate in educational programs was lower for the parents of middle and high school students than the parents of elementary school students and the parents of elementary school students also showed higher satisfaction level of school mathematics curriculum. parents have perceived the necessity of teaching and mathematics education to develop artificial intelligence or data analysis skills. It was also found that the parents of middle and high school students' participation experience in education had an effect on the satisfaction level of their children's math teacher's class preparedness. Parents perceived positively to how pragmatic mathematics curriculum can be and provided answers to what they wish in specific mathematics classes in learning methods and future mathematics learning. As this is for educational experts to consider much in-depth in the future, this study suggested the need for diverse parents' education related to mathematics including the expansion of mathematics education with parents' participation, the creation of a mathematics learning environment for future mathematics learning.

• Informatization Policy
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• v.28 no.2
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• pp.34-56
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• 2021

According to the Fourth Industrial Revolution, demand for and interest in jobs in the field of AI and data science - such as artificial intelligence/data analysts - are increasing. In order to keep pace with this trend, and to supply human resources that can effectively perform such jobs in the relevant fields in a timely manner, job seekers must develop the competencies required by the companies, and universities must be in charge of training. However, it is difficult to devise appropriate response strategies at the level of job seekers, companies and universities, which are stakeholders in terms of supplying suitably competent personnel. Therefore, the purpose of this study is to determine which competencies are required in practice in order to cultivate and supply human talents equipped with the necessary job competencies, and to propose plans for the development of the required competencies at the university level. In order to identify the required competencies in the field of AI and data science, data on job postings on the LinkedIn site, the recruitment platform, were analyzed using text mining techniques. Then, research was conducted with the aim of devising and proposing concrete plans for competency development at the university level by comparing and verifying the results of the international graduate school curriculum in the field of AI and data science, and the interview results with the hiring managers, respectively, with the results of the topic model.

• Journal of the Korean Chemical Society
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• v.68 no.3
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• pp.160-175
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• 2024

The purpose of this study is to examine the effects of a Chemistry I class based on an artificial intelligence (AI) classification model. To achieve this, the research investigated the development and application of a class utilizing an AI classification model in Chemistry I classes conducted at D High School in Gyeongbuk during the first semester of 2023. After selecting the curriculum content and AI tools, and determining the curriculum-AI integration education model as well as AI hardware and software, we developed detailed activities for the program and applied them in actual classes. Following the implementation of the classes, it was confirmed that students' self-efficacy improved in three aspects: chemistry concept formation, AI value perception, and AI-based maker competency. Specifically, the chemistry classes based on text and image classification models had a positive impact on students' self-efficacy for chemistry concept formation, enhanced students' perception of AI value and interest, and contributed to improving students' AI and physical computing abilities. These results demonstrate the positive impact of the Chemistry I class based on an AI classification model on students, providing evidence of its utility in educational settings.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.311-321
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• 2020

The purpose of the study is to verify the effectiveness the Freshman Preliminary Health Administrators(FPHA)' Empathic Problem Solving Ability(EPSA) through the application of Medical Service Design Thinking(MSDT) conducted by undergraduate school of SNS hospital marketing education. The pre-post questionnaire survey was conducted on 39 students in the freshman year of the Department of Health Administration after applying MSDT for 15 weeks from September to December, 2019 at a college in Daegu. MSDT was positive influenced on the improvement of Empathic Imagine, Empathic interest, Empathic awakening of the FPHA' EPSA. In the analysis of key common words, the use of neutral and negative words was low, while the use of positive words was high. In order to systematically equip Empathic problem solving job competency in the age of artificial intelligence, it is meaningful to develop a program for the freshmen curriculum and to conduct a analysis of the structured and unstructured data to verify its effectiveness. Additional program development research is needed for the application of theoretical subjects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.855-860
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• 2018

The IT technologies applying to IoT(Internet of Things), Big Data, and AI(Artificial Intelligence) are needed in the era of 4th industrial revolution. So, the IT convergence courses of computer science major which will be required in the companies in order to prepare the crises of 4th industry revolution are necessary. And, one approach to cope with this problem is the training of IT convergence man power based on NCS(National Competency Standard) education. In this paper, we propose and analyze the NCS education courses for computer science major in order to teach the students who are needed in the Korean domestic companies preparing the 4th industrial revolution. The skills and applications of Chatbot, Blockchain, and CPS(Cyber Physical System) for the post mobile and post Internet technologies are included in the proposed courses.