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Exploring the Design of Artificial Intelligence Convergence Liberal Arts Curriculum Based on Flipped Learning and Maker Education: Focusing on Learner Needs Assessment

플립 러닝과 메이커 교육 기반 인공지능 융합교양교과목 설계 방향 탐색 : 학습자 요구 분석을 중심으로

  • Kim, Sung-ae (Department of Liberal Arts, Duksung Women's University)
  • 김성애 (덕성여자대학교 차미리사교양대학)
  • Received : 2021.07.31
  • Accepted : 2021.08.25
  • Published : 2021.08.31

Abstract

The purpose of this study is to explore the design direction of artificial intelligence convergence liberal arts subjects based on flip learning and maker education through analysis of learner needs in a non-face-to-face classroom environment caused by COVID-19. To this end, we analyzed the priorities of subject content elements by using the Borich needs assessment and The Locus for Focus model along with students' perceptions of flip learning for students who took and did not take maker education-based liberal arts courses. Based on this, it was used as basic data for designing the curriculum. The study results are as follows. First, the content elements of the artificial intelligence liberal arts curriculum based on maker education consisted of a total of 9 areas and were designed as a class using flip learning. Second, the areas with the highest demand for education are 'Artificial Intelligence Theory', 'Artificial Intelligence Programming Practice', 'Physical Computing Theory', 'Physical Computing Practice', followed by 'Convergence Project', '3D Printing Theory', '3D Printing practice' was decided. Third, most of the questionnaires regarding the application of flip learning in maker education-based artificial intelligence liberal arts subjects showed positive responses regardless of whether they took the course, and the satisfaction of the students was very high. Based on this, an artificial intelligence-based convergence liberal arts curriculum using flip learning and maker education was designed. This is meaningful in that it provides an opportunity to cultivate artificial intelligence literacy for college students by preparing the foundation for artificial intelligence convergence education in liberal arts education by reflecting the needs of students.

본 연구는 코로나 19로 인하여 발생한 비대면 수업 환경에서 학습자들의 요구 분석을 토대로 플립 러닝과 메이커 교육 기반 인공지능 융합 교양 교과목의 설계 방향을 탐색하는데 그 목적이 있다. 이를 위해 메이커 교육 기반 인공지능융합 교양 교과목을 수강한 학생들과 수강하지 않은 학생들을 대상으로 플립 러닝에 대한 학생들의 인식과 함께 학습자의 교육 요구도를 조사하였다. 이를 바탕으로 Borich 교육 요구도와 The Locus for Focus Model 모델을 활용하여 교과목 내용 요소에 대한 우선 순위를 분석함으로써 교과목 설계를 위한 기초 자료로 활용하였다. 연구 결과는 다음과 같다. 첫째, 메이커 교육 기반의 인공지능 교양 교과목 내용 요소는 총 9개 영역으로 구성되었으며 플립 러닝을 활용하는 수업으로 설계되었다. 둘째, 교육 요구가 가장 높은 영역은 '인공지능 이론', '인공지능 프로그래밍 실습', '피지컬 컴퓨팅 이론', '피지컬 컴퓨팅 실습'이, 차 순위는 '융합프로젝트', '3D 프린팅 이론', '3D 프린팅 실습'으로 결정되었다. 셋째, 플립 러닝을 활용하여 메이커 교육 기반 인공지능융합 교양 교과목을 운영하는 것은 수강 경험의 유무와 상관없이 대부분 긍정적인 응답이었으며 수강 경험이 있는 학생들의 경우에는 만족도가 매우 높았다. 이를 바탕으로 플립러닝과 메이커교육을 활용한 인공지능 기반의 융합 교양 교과목이 설계되었다. 이는 학생들의 요구를 반영하여 교양 교육에서 인공지능 융합 교육의 기초를 마련하고 대학생의 인공지능 소양 함양의 기회를 제공한다는데 의의가 있다.

Keywords

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