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The Korean Earth Science Society (한국지구과학회)
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Exploring High School Students' Strategies in Prioritizing Data during a 'Finding a Fine Dust-Free School Location' Model-Eliciting Activity (MEA)

'미세먼지 없는 학교 위치 선정' MEA활동에서 고등학생들의 데이터 우선순위 설정 전략 탐색

  • Eunji Lee (Dalcheon High School) ;
  • Younkyeong Nam (Department of Earth Science Education, Pusan National University)
  • Received : 2023.10.03
  • Accepted : 2023.10.31
  • Published : 2023.10.31
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Abstract

This study examined the problem-solving approaches of high school sophomores during a model eliciting activity (MEA) aimed at determining the best location for a school in a heavily industrialized city where fine dust is a concern. Over five lessons, 79 students engaged in this activity, and their completed worksheets provided the primary source of data. These worksheets contained students' step-by-step problem-solving methods provided in response to open-ended questions. By using inductive and qualitative analyses, we examined which data students prioritized and how they interconnected various data points. A key observation was that most students prioritized data related to fine dust, such as emission levels and the locations of industrial complexes, to identify areas with lower emissions. Surprisingly, the students' problem-solving methods were highly varied. There were 61 unique problem-solving models from 76 students. The largest number of students who approached the problem in a same way was only six. This indicates the vast diversity of student approaches to the task. Although their methods varied, one commonality was that most students first considered fine dust-related data to exclude high-emission areas.

본 연구는 대도시에서 미세먼지 없는 학교 부지를 찾는 Model Eliciting Activity (이하 MEA) 활동을 통해 고등학교 학생들의 문제 해결 특성을 조사하기 위한 것이다. 5차시로 개발된 MEA 활동에 79명의 고등학교 2학년 학생들이 참여 하였으며, MEA 활동지를 주요 데이터로 수집하였다. 학생들이 작성한 활동지의 개방형 질문에 대한 답을 기반으로 학생들의 문제 해결 모델을 귀납적 및 질적 방법으로 분석하였다. 먼저 학생들이 다른 데이터보다 어떤 데이터를 우선적으로 사용했는지 순서를 분석한 후 주어진 데이터 세트를 어떻게 상호 연결하여 순서를 결정하는지 분석하였다. 분석결과 학생들은 미세먼지 배출량이 많은 곳을 기피하기 위해 미세먼지 배출농도, 산업단지 분포 등 미세먼지와 직접적으로 관련된 데이터를 먼저 활용하는 경향이 있음을 알 수 있었다. 흥미롭게도 MEA 활동에서 고등학생의 문제 해결 특성은 매우 다양하여 76명의 학생이 총 61가지 유형의 문제 해결 모델을 제작한 것으로 나타났다. 문제를 해결하기 위해 동일한 순서의 데이터를 사용하는 학생의 최대 수는 6명으로 학생들의 문제 해결 방법은 매우 다양함을 보여준다. 그러나 공통적으로 미세먼지 농도가 높은 곳을 제외하는 방법으로 미세먼지 배출과 직접적으로 관련된 데이터를 먼저 선택하는 특성을 보였다.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2022R1A2C1011366).

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