회귀 모델에 대한 해석을 강조한 인공지능 융합 화학 수업의 교육적 영향 분석: 고등학생들의 인공지능 리터러시, 지식정보처리 역량, 수업에 대한 인식 관점에서
An Analysis of the Educational Impacts of an AI-Integrated Chemistry Class Emphasizing the Interpretation of Regression Models: Focusing on High School Students’ AI Literacy, Knowledge-Information Processing Competency, and Perceptions of the Class
- 발행
- 2026
- 소속·발행
- 광양마동중학교
- 출처
- 국내 KCI
- 원문등록
- 2026-04-14
- 원문
- 원문 보기 ↗
개념
키워드
AI-integrated education, Artificial intelligence, AI literacy, knowledge-information processing competency, regression model, AI-integrated education, Artificial intelligence, AI literacy, knowledge-information processing competency, regression model
초록
The rapid advancement of artificial intelligence (AI) technology necessitates a fundamental shift in educational goals—from the simple transmission of standardized knowledge to fostering learners’ abilities to collaborate with AI, solve complex problems, and generate new value. This study implemented an AI-integrated chemistry class that emphasized the interpretation of regression models, targeting general high school students, to examine its impact on students’ AI literacy and knowledge-information processing competency. The class covered two topics—surface tension and gases—each organized into five stages: concept introduction, AI modeling, model interpretation, explanation introduction, and summary. Students’ AI literacy and knowledge-information processing competency were measured through pre- and post-tests and analyzed using the Wilcoxon signed-rank test to examine differences before and after the class. In addition, students’ perceptions of the class were collected through a post-survey and qualitatively categorized to identify response patterns. The results revealed statistically significant improvements in students’ AI literacy and knowledge-information processing competen