빅데이터 시대의 데이터 저널리즘 교육에 관한 소고무엇을, 어떻게 할 것인가? (A Note on Data Journalism Education in the Era of Big Data: What to do, and How to do?)

서지정보

· 발행기관 : 한국언론학회
· 수록지 정보 : 한국언론학보 / 63권 / 5호 / 87 ~ 115페이지
· 저자명 : 윤호영

초록

본 연구는 빅데이터 시대에 데이터 저널리즘 교육을 활성화시키기 위한 방안을 고민하는 연구이다. 이를 위해 먼저 데이터 저널리즘의 등장 배경과 개념적 정의를 논하고, 데이터 저널리즘 교육과 관련된 쟁점을 정리하였다. 다음으로, 미국을 중심으로 데이터 저널리즘의 교육 현황을 점검하면서, 데이터 분석의 학습 과정에서 저널리즘적 시각이 추가되는 통계적 추론 능력이 중요하다는 점을 강조하였다. 또한, 데이터 저널리즘 교육의 활성화를 위해서는 대학 교육 뿐만 아니라 현업 환경을 고려한 학습 체계를 구성하는 것이 중요하다는 점을 언급하였다. 마지막으로, 데이터 저널리즘의 활성화를 위해 저널리즘 시각 육성을 위한 학부수업, 현업의 데이터 저널리즘 성과를 모은 학습 교재 데이터베이스, 그리고 대학원의 고급 기술 과정이 필요하다는 점을 제시하였다.

영어초록

The purpose of this paper is to invigorate discussion on data journalism education. The paper begins with an introduction of data journalism, which can be defined as a journalism practice pertaining to presenting data analysis for stories of interest to the public. The data analysis process for journalism practice, like many data analyses in other disciplines, includes collection, pre-processing, and visualization. After the introduction, the paper gives an overview of the debates on data journalism education: is it imperative to teach it; should it be taught at higher education institutions or elsewhere; should it be an independent course in journalism coursework, or can it be taught within disciplines that do not apply a journalism approach? While there is little consensus on how to teach data journalism and on the depth of data analysis required by journalism students, educators in journalism schools mostly agree that both statistical reasoning and coding skills are gaining ground as independent and essential subjects of the journalism curriculum. The issue here is the lack of teaching materials and human resources of a journalism approach, not the need or demand for data journalism. The paper also reviewed current syllabi for data journalism courses offered by several institutions so as to understand the sequence of data journalism coursework. With the exception of a small number of schools, it was observed that many data journalism courses tend to take the form of data analysis courses, making them indistinguishable from general social science courses. As data journalism education is in its initial stages, more systematic efforts need to be placed in the school education system. A few leading schools have already integrated field work and curriculum materials as capstone projects. Finally, the paper suggested tentative solutions for data journalism education that enriches through undergraduate study, industry practices, and graduate study. To summarize, first, it is suggested that a database system for data journalism education will greatly improve the effectiveness and efficiency of data journalism education. The database system will not only help teachers but also students in a way that provides standardized course materials and examples that everybody in the field can share as common ground. Second, it is also suggested that the data journalism education system needs to be aligned with industry practices, relevant institutions and associations, and academic environment. Previous literature has revealed that professionalism and the cultural heritage of journalism practices have led to diverse trajectories of data journalism education. In this respect, we are encouraged to set up our own system that harmonizes current efforts to grow data journalists in our society, both in and outside the academic setting.

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