• Title/Summary/Keyword: 인공지능 활용 수학 수업 설계

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Effects of AI Convergence Education Program for Pre-service Teachers using Capstone Design Methods on AI Teaching Efficacy (예비교사를 위한 캡스톤 디자인 방법 활용 인공지능 융합교육 프로그램이 인공지능 교수효능감에 미치는 영향)

  • Yi, Soyul;Lee, Eunkyoung
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.717-718
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    • 2022
  • 본 연구에서는 예비교사의 인공지능 융합교육 역량 강화를 위한 캡스톤 디자인 기법 활용 인공지능 융합교육 프로그램을 개발하고 효과를 검증하였다. 개발된 교육 프로그램은 예비교사들이 스크래치 프로그래밍과 머신러닝포키즈, 캡스톤 디자인의 이해를 바탕으로, 인공지능 활용 융합 수업을 위한 주제 선정, 수업 설계 및 개발 후, 마이크로티칭을 하고 동료 평가 및 피드백을 하도록 조직되었다. 이는 2022년 1학기 K대학의 교양 강좌를 수강하는 예비교사들에게 처치되었다. 그 결과, 실험 대상자들의 인공지능 교수효능감의 사전-사후 t-검정에서 통계적으로 유의한 효과가 있음을 확인되었다.

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Analysis of functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics (개인 맞춤형 수학 학습을 위한 인공지능 교육시스템의 기능과 적용 사례 분석)

  • Sung, Jihyun
    • The Mathematical Education
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    • v.62 no.3
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    • pp.303-326
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    • 2023
  • Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

Study on the Mathematics Teaching and Learning Artificial Intelligence Platform Analysis (수학 교수·학습을 위한 인공지능 플랫폼 분석 연구)

  • Park, Hye Yeon;Son, Bok Eun;Ko, Ho Kyoung
    • Communications of Mathematical Education
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    • v.36 no.1
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    • pp.1-21
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    • 2022
  • The purpose of this study is to analyze the current situation of EduTech, which is proposed as a way to build a flexible learning environment regardless of time and place according to the use of digital technology in mathematics subjects. The process of designing classes to use the EduTech platform, which is still in the development introduction stage, in public education is still difficult, and research to observe its effects and characteristics is also in its early stages. However, in the stage of preparing for future education, it is a meaningful process to grasp the current situation and point out the direction in preparation for the future in which EduTech will be actively applied to education. Accordingly, the current situation and utilization trends of EduTech at home and abroad were confirmed, and the functions and roles of EduTech platforms used in mathematics were analyzed. As a result of the analysis, the EduTech platform was pursuing learners' self-directed learning by constructing its functions so that they could be useful for individual learning of learners in hierarchical mathematics education. In addition, we have confirmed that the platform is evolving to be useful for teachers' work reduction, suitable activities, and evaluations learning management. Therefore, it is necessary to implement instructional design and individual customized learning support measures for students that can efficiently utilize these platforms in the future.

Analysis of Academic Achievement Data Using AI Cluster Algorithms (AI 군집 알고리즘을 활용한 학업 성취도 데이터 분석)

  • Koo, Dukhoi;Jung, Soyeong
    • Journal of The Korean Association of Information Education
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    • v.25 no.6
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    • pp.1005-1013
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    • 2021
  • With the prolonged COVID-19, the existing academic gap is widening. The purpose of this study is to provide homeroom teachers with a visual confirmation of the academic achievement gap in grades and classrooms through academic achievement analysis, and to use this to help them design lessons and explore ways to improve the academic achievement gap. The data of students' Korean and math diagnostic evaluation scores at the beginning of the school year were visualized as clusters using the K-means algorithm, and as a result, it was confirmed that a meaningful clusters were formed. In addition, through the results of the teacher interview, it was confirmed that this system was meaningful in improving the academic achievement gap, such as checking the learning level and academic achievement of students, and designing classes such as individual supplementary instruction and level-specific learning. This means that this academic achievement data analysis system helps to improve the academic gap. This study provides practical help to homeroom teachers in exploring ways to improve the academic gap in grades and classes, and is expected to ultimately contribute to improving the academic gap.