• Journal of Korean Home Economics Education Association
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• v.16 no.3
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• pp.81-98
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• 2004

This study is to conduct the basic study for the achievement and assessment standards for the subject of 'Human Development' and 'Food and Nutrition', which are the curricula of Vocational Home Economics High Schools. These two subjects were newly adopted in the Vocational study Section of the 2005 College Entrance Examinations. In other words, this study is to provide the basic data for implementing the quality education based on the proper assessment of the curricula. For this purpose. this study analyzed the character & objective of 'Human Development' and 'Food and Nutrition'. Secondly. through the theoretical review for the concept & necessity of absolute evaluation standards. this study ensures the concept of achievement and assessment standards. and also designs the developing measures (including procedures). The achievement standards were developed by the following 5 step procedures. (1) Analyzing the objectives & contents of curricula. (2) Designating the development field of achievement standards (3) Developing the achievement standards. (4) The assessment of achievement standards. (5) Confirming the achievement standards. The assessment standards were developed by the following 5 step procedures. (1) Analyzing the achievement standards, (2) Designating the assessment field (3) Developing the assessment standards (4) Evaluating the assessment standards (5) Confirming the assessment standards Thirdly, this study suggested the exemplary achievement standards and assessment standards for the subject of Human Development, Food and Nutrition. Future study needs some critical review for the method of developing achievement and assessment standards for the subject of Human Development, Food and Nutrition. For example. the properness of 'Contents Element' which was designated as the developing field in the achievement standards, the discussion on validity of Contents Element abstract. the base of evaluating classification in terms of low, middle and high level, and other things should be considered through critical discussion. Especially the follow-up study should include the development of various evaluating methods to enable the clear communication for the achievement and assessment standards based on abstract concept and theory, thereby it could enable the actual interpretation and practical use.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.657-670
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• 2020

The knowledge-information-processing competency is the most essential competency in a knowledge-information-based society and is the most fundamental competency in the new problem-solving ability. Data-driven science inquiry, which emphasizes how to find and solve problems using vast amounts of data and information, is a way to cultivate the problem-solving ability in a knowledge-information-based society. Therefore, this study aims to develop a teaching-learning model and strategy for data-driven science inquiry and to verify the validity of the model in terms of knowledge information processing competency. This study is developmental research. Based on literature, the initial model and strategy were developed, and the final model and teaching strategy were completed by securing external validity through on-site application and internal validity through expert advice. The development principle of the inquiry model is the literature study on science inquiry, data science, and a statistical problem-solving model based on resource-based learning theory, which is known to be effective for the knowledge-information-processing competency and critical thinking. This model is titled "Exploratory Scientific Data Analysis" The model consisted of selecting tools, collecting and analyzing data, finding problems and exploring problems. The teaching strategy is composed of seven principles necessary for each stage of the model, and is divided into instructional strategies and guidelines for environment composition. The development of the ESDA inquiry model and teaching strategy is not easy to generalize to the whole school level because the sample was not large, and research was qualitative. While this study has a limitation that a quantitative study over large number of students could not be carried out, it has significance that practical model and strategy was developed by approaching the knowledge-information-processing competency with respect of science inquiry.

• The Mathematical Education
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• v.63 no.2
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• pp.255-272
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• 2024

This study aims to design mathematics-integrated classes that cultivate artificial intelligence (AI) thinking and to analyze students' AI thinking within these classes. To do this, four classes were designed through the integration of the AI4K12 Initiative's AI Big Ideas with the 2015 revised elementary mathematics curriculum. Implementation of three classes took place with 5th and 6th grade elementary school students. Leveraging the computational thinking taxonomy and the AI thinking components, a comprehensive framework for analyzing of AI thinking was established. Using this framework, analysis of students' AI thinking during these classes was conducted based on classroom discourse and supplementary worksheets. The results of the analysis were peer-reviewed by two researchers. The research findings affirm the potential of mathematics-integrated classes in nurturing students' AI thinking and underscore the viability of AI education for elementary school students. The classes, based on AI Big Ideas, facilitated elementary students' understanding of AI concepts and principles, enhanced their grasp of mathematical content elements, and reinforced mathematical process aspects. Furthermore, through activities that maintain structural consistency with previous problem-solving methods while applying them to new problems, the potential for the transfer of AI thinking was evidenced.