• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.99-106
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• 2020

In this paper, we analyzed the units related to robot education in the Practical Arts textbooks according to the 2015 revised curriculum. As a result, all textbooks had a common system of introduction, development, and organization, and all of them showed a similar flow. Learning objectives were presented in all textbooks, but no affective goals were presented except cognitive and functional goals. The contents of robot learning suggest the meaning and type of robots, the structure and sensors of robots, and the activities of making robots, but the contents of robot ethics, the production and activities of various robot works, and the use of robots in the problem solving process are not presented. The assembly robot and the infrared sensor are used in common, and it consists of presenting robot production and control training materials in experience activities and arranging units through evaluation, and the A, C, and F textbooks also provide the unit auxiliary data. In the future, it will be necessary to include the contents of robot ethics education centered on the design/manufacturer and user-oriented robot ethics such as the recognition of the limits of robots, the principles of using robots correctly, safety education, personal information and privacy protection.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.25-31
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• 2022

The purpose of this study is to explore the implications for the systematic operation of the AI curriculum by analyzing the current status of the AI major curriculum in universities. To this end, This study analyzed the relevant curriculum of domestic universities(a total of 51 schools) and overseas QS Top 10 universities based on the industry demand-based standard of AI major curriculum developed through prior research. The main research results are as follows. First, in the case of domestic universities, Python-centered programming subjects were lacking. Second, there were few subjects for advanced learning such as AI application and convergence. Third, the subjects required to perform the AI developer job were insufficient. Fourth, in the case of colleges, the ratio of AI mathematics-related subjects was low. Based on these results, this study presented implications for the systematic operation of the AI major education.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.459-469
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• 2021

In this paper, a case study of basic data science practice education for field teachers and pre-service teachers was studied. In this paper, for basic data science education, spreadsheet software was used as a data collection and analysis tool. After that, we trained on statistics for data processing, predictive hypothesis, and predictive model verification. In addition, an educational case for collecting and processing thousands of public big data and verifying the population prediction hypothesis and prediction model was proposed. A 34-hour, 17-week curriculum using a spreadsheet tool was presented with the contents of such basic education in data science. As a tool for data collection, processing, and analysis, unlike Python, spreadsheets do not have the burden of learning program- ming languages and data structures, and have the advantage of visually learning theories of processing and anal- ysis of qualitative and quantitative data. As a result of this educational case study, three predictive hypothesis test cases were presented and analyzed. First, quantitative public data were collected to verify the hypothesis of predicting the difference in the mean value for each group of the population. Second, by collecting qualitative public data, the hypothesis of predicting the association within the qualitative data of the population was verified. Third, by collecting quantitative public data, the regression prediction model was verified according to the hypothesis of correlation prediction within the quantitative data of the population. And through the satisfaction analysis of pre-service and field teachers, the effectiveness of this education case in data science education was analyzed.

• The Journal of Korean Association of Computer Education
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• v.23 no.4
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• pp.49-59
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• 2020

At the beginning of the discussion of AI education in K-12 education, the study was conducted to develop and apply an AI education program based on Design Thinking and analyze the effects of the AI education programs. In the AI education program, students explored and defined the AI problems they were interested in, gathered the necessary data to build an AI model, and then developed a project using scratch. In order to analyze the effectiveness of the AI education program, the change of learner's perception of the value of AI and the change of AI efficacy were analyzed. The overall perception of the AI project was also analyzed. As a result, AI efficacy was significantly increased through the experience of carrying out the project according to the Design Thinking process. In addition, the efficacy of solving problems with AI was influenced by the level of use of programming languages. The learner's overall perception of the AI project was positive, and the perceptions of each stage of the AI project (AI problem understanding and problem exploration, practice, problem definition, problem solving idea implementation, evaluation and presentation) was also positive. This positive perception was higher among students with high level of programming language use. Based on these results, the implications for AI education were suggested.