• Education of Primary School Mathematics
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• v.26 no.4
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• pp.333-348
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• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.331-332
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• 2023

최근 ChatGPT, 코딩교육, 디지털교과서 등의 새로운 용어와 산물들이 전국 단위 언론사를 통해, 교육 전문가(교사 등)와 일반 국민들에게 어떤 형태의 보도가 진행되는지 확인하는 것이 중요한 연구 출발점이다. 본 연구는 오늘날 학교교육, 교육방법(매체론) 등에 큰 변화를 줄 '인공지능'에 대한 전국 단위 언론사(일간지-11개사, 방송사-5개사)의 최근(2020-2023년) 보도형태를 분석하고 제시하였다. 본 연구에서는 2020년 1월부터 2023년 5월까지(3년 5개월간) 총 16개 언론사(일간지와 방송사)에서 보도한 '인공지능'와 '학교' 용어가 모두 포함된 관련 뉴스 기사들을 분석하였다. 분석대상 뉴스 빅데이터들을 대상으로 연도별 보도기사 건수 분석, 키워드 트렌드 분석, 연관어 분석(워드클라우드 제시) 등을 진행하였다.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.49-54
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• 2022

Rapid changes in modern society after the COVID-19 have highlighted artificial intelligence talent as a major influencing factor in determining national competitiveness. Accordingly, the Ministry of Education planned a large-scale SW·AI camp education project to develop the digital capabilities of 4th to 6th grade elementary school students and middle and high school students who are in a vacuum in artificial intelligence education. Therefore, this study aims to develop a camp-type SW·AI education program for students in grades 4-6 of elementary school so that students in grades 4-6 of elementary school can acquire basic knowledge in artificial intelligence. For this, the meaning of SW·AI education in elementary school is defined and SW·AI contents to be dealt with in elementary school are: understanding of SW AI, 'principle and application of SW AI', and 'social impact of SW AI' was set. In addition, an attempt was made to link the set elements of elementary school SW AI education and learning with related subjects and units of textbooks currently used in elementary schools. As for the program used for education, entry, a software coding learning tool based on block coding, is designed to strengthen software programming basic competency, and all programs are designed to be operated centered on experience and experience-oriented participants in consideration of the developmental characteristics of elementary school students. In order for SW·AI education to be organized and operated as a member of the regular curriculum, it is suggested that research based on the analysis of regular curriculum contents and in-depth analysis of SW·AI education contents is necessary.

• The Mathematical Education
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• v.62 no.2
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• pp.289-302
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• 2023

In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.