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초등교육 현장에서 AI기반 맞춤형 교수·학습을 위한 학습자 특성 진단 및 처방에 대한 요구 분석

Analyzing the needs for learner characteristics diagnosis and prescription through AI-based personalized teaching and learning in primary educational contexts

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초록

본 연구는 초등교육 현장에서 AI기반 맞춤형 교수·학습을 통한 학습자 특성 진단 및 처방에 대한 요구를 분석함으로써, 교사들이 학습자의 다양한 학습 요구를 AI를 활용하여 지원할 수 있는 방안을 모색하는 것을 목적으로 한다. 이를 위해 AI가 데이터를 통해 진단해 줄 중요도가 높은 개인별 및 집단별 학습자 특성과, 이를 기반으로 처방적 측면에서 교수 설계 및 학생 지도를 위한 피드백 전략에 대한 요구 분석 문항을 개발하였다. 개발된 총 83개의 문항을 바탕으로 현직 초등교사를 대상으로 중요도, 실행도를 측정하였고, Borich의 요구도 산출 공식, 초점의 소재 모형을 활용하여 분석하였다. 연구 결과, 교사들은 진단 측면에서 학생들의 강-약점, 관심 키워드, 학습 스타일 등 개별적인 특성뿐만 아니라, 학생들의 다중지능, 쓰기 효능 등 집단별 특성에 대해서도 파악하고자 하는 높은 요구를 보였다. 본 연구에서는 진단에 따른 처방전략에 대한 교사요구도 함께 도출하였다.

Abstract

This study aims to analyze the needs for learner characteristics diagnosis and prescription through AI-based personalized teaching and learning in primary educational contexts, so that teachers can meet the diverse learning needs of students. To this end, a total of 83 needs survey questions on important individual and group characteristics of learners to be identified using AI and feedback and prescription strategies about instructional design and student guidance in terms of prescription were collected and analyzed, using Borich's needs calculation formula and The Locus for Focus model to measure the importance and implementation scales. The results of the study showed that teachers have a strong need to understand not only individual characteristics such as students' merits and weaknesses, keywords of interest, and learning styles, but also group characteristics such as students' multiple intelligences and writing efficacy in terms of diagnosis, deriving the needs for prescription strategies.

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