AI 기반 피드백 시스템이 초등학생의 통계적 탐구 질문 설정 향상에 미치는 영향 : AI 인식과 피드백 자기 효율성의 조절 효과

The Impact of an AI-based Feedback System on the Improvement of Elementary Students’ Statistical Inquiry Question Posing: The Moderating Effects of AI Perception and Feedback Self-efficacy

With the advent of the digital age, the amount of data has exponentially increased making statistical analysis essential for decision-making and problem-solving. This research examines the impact of an AI-based feedback system (FS) using the GPT-4 model on the ability of sixthgrade students to formulate statistical inquiry questions. Conducted at an elementary school in Gyeonggi-do, the research involved 95 students divided into experimental and control groups, who participated in an eight-session program. The experimental group received feedback from the AI-based FS, while the control group received teacher feedback. Pre- and post-tests measured the improvement in students’ statistical inquiry question levels. Additionally, the study analyzed how students’ self-efficacy regarding feedback and their perception of AI moderated the effectiveness of the FS. Results showed that the AI-based FS significantly improved the students’ ability to pose statistical inquiry questions compared to the control group. The study also found that a positive perception of AI enhanced the effectiveness of the FS, while self-efficacy regarding feedback did not show a significant impact. These findings suggest that AI-based FS can be an effective educational tool, particularly when students have a positive attitude toward AI. Future research should focus on developing fine-tuned AI-based FS capable of providing detailed feedback throughout all stages of statistical inquiry and investigate its effects on students with cognitive challenges in accepting feedback.