실천공학교육논문지 (Journal of Practical Engineering Education)

  • 제12권2호
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  • Pages.265-273
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  • 2020
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  • 2288-405X(pISSN)
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  • 2288-4068(eISSN)
한국실천공학교육학회 (Korean Institute for Pratical Engineering Education)
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비전공자 대상 기초 데이터과학 실습 커리큘럼

Curriculum of Basic Data Science Practices for Non-majors

  • 허경 (경인교육대학교 컴퓨터교육과)
  • Hur, Kyeong (Department of Computer Education, Gyeong-In National University of Education)
  • 투고 : 2020.10.29
  • 심사 : 2020.11.30
  • 발행 : 2020.12.01
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초록

본 논문에서는 비전공자들을 위한 교양과목으로 적용할 수 있는 기초 데이터과학 실습 커리큘럼을 제안하고, 엑셀(스프레드시트) 데이터 분석 도구를 활용한 교육 방법을 제안하였다. 데이터 수집, 데이터 가공 및 데이터 분석을 위한 도구에는 엑셀, R, 파이썬, SQL(Structured Query Language) 등이 있다. R, 파이썬 및 SQL은 데이터 과학을 실습하는 데 있어, 프로그래밍 언어와 자료구조를 이해해야 한다. 반면에, 엑셀 도구는 비전공자들에게도 친숙한 데이터 분석도구로서, 프로그래밍 언어에 대한 학습 부담이 없다. 그리고 기초적인 데이터과학 실습을 엑셀로 진행하면, 데이터과학 이론을 습득하는 데 집중할 수 있는 장점이 있다. 본 논문에서는 한 학기 분량의 기초 데이터과학 실습 커리큘럼과 주별 엑셀 실습 내용을 제안하였다. 그리고, 교육 내용 실체를 실증하기위해, 엑셀 데이터분석 도구를 활용하여, 선형 회귀 분석(Linear Regression Analysis) 예제들을 제시하였다.

In this paper, to design a basic data science practice curriculum as a liberal arts subject for non-majors, we proposed an educational method using an Excel(spreadsheet) data analysis tool. Tools for data collection, data processing, and data analysis include Excel, R, Python, and Structured Query Language (SQL). When it comes to practicing data science, R, Python and SQL need to understand programming languages and data structures together. On the other hand, the Excel tool is a data analysis tool familiar to the general public, and it does not have the burden of learning a programming language. And if you practice basic data science practice with Excel, you have the advantage of being able to concentrate on acquiring data science content. In this paper, a basic data science practice curriculum for one semester and weekly Excel practice contents were proposed. And, to demonstrate the substance of the educational content, examples of Linear Regression Analysis were presented using Excel data analysis tools.

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