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An Examination of the Course Syllabi related to Data Science at the ALA-accredited Library and Information Science Programs

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2022, v.39 no.1, pp.119-143
https://doi.org/10.3743/KOSIM.2022.39.1.119
Hyoungjoo Park (Chungnam National University)
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Abstract

This preliminary study examined the status of data science-related course syllabi in the American Library Association (ALA) accredited Library and Information Science (LIS) programs. The purpose of this study was to explore LIS course syllabi related to data science, such as course title, course description, learning outcomes, and weekly topics. LIS programs offer various topics in data science such as the introduction to data science, data mining, database, data analysis, data visualization, data curation and management, machine learning, metadata, and computer programming. This study contributes to helping instructors develop or revise course materials to improve course competencies related to data science in the ALA-accredited LIS programs.

keywords
데이터사이언스, 데이터사이언스 관련 교과, 문헌정보학 교과, 교과목 개발, data science, data science curriculum, LIS curriculum, course development
Submission Date
2022-02-14
Revised Date
2022-03-04
Accepted Date
2022-03-17

Journal of the Korean Society for Information Management