초등교사 대상 생성형 AI의 교수적 활용 사례 탐색: 행위자-네트워크 이론(ANT)을 중심으로
Exploring Instructional Use of Generative AI for Elementary School Teachers: Focusing on Actor-Network Theory(ANT)
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초록
생성형 AI는 학교 현장에서 다양한 용도로 교사의 업무를 보조하며 업무 경감, 효율적인 수업 설계 지원 등의역할을 수행하는 것으로 주목받고 있다. 이러한 현상을 생태학적인 관점으로 바라보자면, 인간 행위자인 교사와비인간 행위자인 생성형 AI 간의 상호작용이 더욱 복잡해지고 있다는 점이 시사된다. 따라서 본 연구에서는 행위자-네트워크 이론을 기반으로 생성형 AI를 활용하는 초등교사의 질적 사례를 탐색하고자 하였다. 이를 위해 초등교사를 유목적으로 표집하여 심층 인터뷰를 진행하였다. 이후 개방 코딩 절차에 따라 개별적으로 교사들의 사례를분석하여 행위자-네트워크 지도로 결과를 시각화하였다. 연구결과, 시각화된 지도를 통해 교사의 생성형 AI 활용맥락에서 다양한 행위의 노드, 매개 행위자를 서로 비교할 수 있었고, 이를 통해 개별적인 교사들의 특성을 시사할 수 있었다. 본 연구는 행위자-네트워크 이론을 기반으로 인간-기술의 관계를 동등하게 바라보며 교사의 생성형AI 활용에 관한 복잡한 관계에 새로운 통찰을 제시한 것에 의의가 있다.
Abstract
Generative AI promises to assist teachers in various school tasks, reducing their workload and supporting effi- cient lesson design. From an ecological perspective, this phenomenon suggests that the interaction between human actors, teachers, and non-human actors, generative AI, is becoming complex. Therefore, this study aims to explore the qualitative case of elementary school teachers using generative AI through actor-network theory(ANT). To achieve this, in-depth interviews were conducted with a purposefully selected sample of elementary school teachers. Thematic analysis was then progressed to examine each case individually using open coding. Finally, the results were visualized through the construction of actor-network maps. In conclusion, the nodes of the different actions that emerged in teachers' use of generative AI were compared, focusing on the mediating actors and sug- gesting the characteristics of individual teachers. This study provide new insights into the relationship between teachers' use of generative AI by looking at the human-technology relationship as equal based on ANT.
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