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생성형 인공지능 관련 해외대학교 가이드라인 사례 분석을 통한 교원양성기관 음악 교사 교육 제언 방안

Case Analysis of University Guidelines on Generative Artificial Intelligence: Suggestions for Music Teacher Education

신지혜|강주현
한국음악치료교육학회 (Korean Music Therapy Association (KOMTEA))|2024.12|인간행동과 음악연구 (Journal of Music and Human Behavior)|제21권 제3호|pp. 91-112|DOI http://dx.doi.org/10.21187/jmhb.2024.21.3.091

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키워드

생성형 인공지능generative AIAI ethicsmusic education인공지능 윤리음악 교육인공지능 가이드라인음악 교사 교육AI guidelinemusic teacher education
주제분류음악학

초록

본 연구의 목적은 인공지능 윤리에 적극적인 관심과 태도를 보이는 북미 및 유럽의 대학에서제공하고 있는 생성형 인공지능 관련 가이드라인을 살펴보고 이를 음악 교사 양성기관에 적용할 수 있는 방안에 대해서 탐색하는 것이다. 본 연구의 주요 결과는 다음과 같다. 첫째, 해외대학들이 제시한 생성형 인공지능 가이드라인의 교육적 측면은 학생들이 정해진 범위 내에서생성형 인공지능을 적극적으로 연구와 학습에 활용할 수 있도록 권장하며, 교과와 학습에 필요한 도구, 방법, 활용 방안은 교수자가 주도적으로 결정하도록 규정하고 있다. 둘째, 거버넌스측면은 개인정보 보호, 투명성, 공정성, 책임감, 학문적 진실성을 포함하고 있다. 셋째, 운영 측면은 생성형 인공지능의 활용에 대해서 주기적으로 모니터링의 필요성을 강조하고, 각 대학의지침 준수 여부와 나날이 변화하는 인공지능 도구와 환경을 준비하고 탐색하는 데 초점을 맞추고 있다. 생성형 인공지능 지침 분석을 바탕으로 한 음악 교사 교육에 대한 제언 사항으로생성형 인공지능 활용과 그 결과물에 대한 비판적 사고 함양, 생성형 인공지능을 활용한 음악창작 과정에서의 주체성 확보, 인공지능이 생성한 음악 결과물의 저작권 문제, 그리고 생성형인공지능의 급격한 발전이 음악, 음악 활동, 음악 교육의 범위, 과정, 가치에 미치는 영향을 논의할 필요성을 제시하였다.

Abstract

The purpose of this study is to examine the guidelines related to generative AI provided by universities in North America and Europe, which show a proactive interest in and attitude towards AI ethics, and to explore how these guidelines can be applied to teacher training institutions that prepare music educators. The main findings of this study are as follows. First, from an educational perspective, most universities investigated in this study allow instructors to decide on the tools, methods, and extent of AI utilization in teaching and learning, while preemptively preventing students from using generative AI inappropriately. Additionally, they encourage the active use of generative AI in research and learning. Second, the governance guidelines provided by universities include aspects such as privacy protection, transparency, fairness, accountability, and academic integrity. Third, in terms of operational aspects, universities emphasize the importance of periodically monitoring the use of generative AI, ensuring that the guidelines are being actively followed, and exploring processes to adapt to rapidly changing AI tools and environments. Fourth, as recommendations for music teacher education derived from the analysis of generative AI guidelines, the study highlights the importance of critical thinking regarding the use and outputs of generative AI, the development of agency in music creation using AI, the copyright issues related to AI-generated music outputs, and the need for discussions on the scope, process, and value of music, musical activities, and music education in light of the rapid advancements in generative AI.

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