한국과학교육학회지 (Journal of The Korean Association For Science Education)

  • 제44권2호
  • /
  • Pages.141-153
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  • 2024
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  • 1226-5187(pISSN)
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  • 2288-8489(eISSN)
한국과학교육학회 (The Korean Association for Science Education)
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과학중점학교 학생의 블록코딩 플랫폼 KNIME을 활용한 과학-AI 융합 수업 경험 분석

An Analysis of Students' Experiences Using the Block Coding Platform KNIME in a Science-AI Convergence Class at a Science Core High School

  • 투고 : 2024.01.23
  • 심사 : 2024.04.16
  • 발행 : 2024.04.30
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초록

2022 개정 과학과 교육과정은 AI를 활용한 탐구 활동을 경험함으로써 융합적 사고를 바탕으로 일상생활과 사회 속 과학 문제를 해결할 수 있는 능력을 기르는 것을 목표로 한다. 이에 과학 교과와 AI를 융합한 과학-AI 융합교육 프로그램을 개발하고 이를 활용하여 고등학생을 대상으로 융합 수업을 진행하였다. 과학-AI 융합 수업은 감쇠진자의 운동을 정성적으로 이해하고 블록코딩 플랫폼 KNIME을 사용하여 진자의 위치를 예측할 수 있는 AI 모델을 구축하는 것을 목표로 한다. 개별 심층 면담을 통해 학습자의 경험을 이해하고 해석하고자 하였다. Giorgi의 현상학적 연구 방법론을 바탕으로 학습자의 참여 동기, 배움과 변화, 어려움과 수업의 한계를 기술하였다. 학생들은 AI에 대한 관심과 사회적 트렌드에 대한 인식을 바탕으로 수업에 참여하고자 하는 동기를 가지고 있었다. 학생들은 직접 데이터를 수집하고 AI 모델을 구축하는 것을 배웠다. 실험 결과를 바탕으로 주변 현상을 예측할 수 있을 것으로 기대하였으며 융합 수업을 긍정적으로 인식하였다. 한편, 여전히 익숙하지 않은 플랫폼, AI 원리 이해를 어려움으로 인식하였고 따라해야만 하는 수업 방식의 한계와 수업 내용상의 한계를 인식하였다. 융합 수업의 경험은 실생활의 문제를 AI를 통해 해결하고자 하는 학습 동기로 나타났으며, 학생들이 느낀 어려움과 한계는 더 심화되고 확장된 주제를 학습하고 싶은 동기로 이어졌다. 이를 바탕으로 과학-AI 융합 수업을 위한 논의 및 제언을 도출하였다. 본 연구는 과학-AI 융합 수업을 개발하고 이를 현장에 적용할 때 시사점을 제공할 것으로 기대된다.

The 2022 revised science curriculum aims to develop the ability to solve scientific problems arising in daily life and society based on convergent thinking stimulated through participation in research activities using artificial intelligence (AI). Therefore, we developed a science-AI convergence education program that combines the science curriculum with artificial intelligence and employed it in convergence classes for high school students. The aim of the science-AI convergence class was for students to qualitatively understand the movement of a damped pendulum and build an AI model to predict the position of the pendulum using the block coding platform KNIME. Individual in-depth interviews were conducted to understand and interpret the learners' experiences. Based on Giorgi's phenomenological research methodology, we described the learners' learning processes and changes, challenges and limitations of the class. The students collected data and built the AI model. They expected to be able to predict the surrounding phenomena based on their experimental results and perceived the convergence class positively. On the other hand, they still perceived an with the unfamiliarity of platform, difficulty in understanding the principle of AI, and limitations of the teaching method that they had to follow, as well as limitations of the course content. Based on this, we discussed the strengths and limitations of the science-AI convergence class and made suggestions for science-AI convergence education. This study is expected to provide implications for developing science-AI convergence curricula and implementing them in the field.

키워드

과제정보

이 논문은 4단계 두뇌한국 BK21 '인포스피어 과학교육연구단'의 지원을 받아 수행된 연구입니다.

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