Published in

SAGE Publications, IFLA Journal, 4(47), p. 453-467, 2021

DOI: 10.1177/0340035221989367

Links

Tools

Export citation

Search in Google Scholar

What we talk about when we talk about information literacy

Journal article published in 2021 by Margaret S. Zimmerman, Chaoqun Ni ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Information literacy skills are requisite to fulfilling one’s potential and are highly connected to a good quality of life. However, the ways in which information literacy is discussed within the academic canon are largely unexplored, particularly as these conversations take place through different cultural lenses. The ways in which such cultures are grouped often rely on traditional methods of geographic clustering that are increasingly complicated by the disparate internal nature of societies. Using text analysis of a large bibliometric data set, this research is an attempt to examine how scholars around the world discuss information literacy in their publications. The authors pulled 3658 records with the exact term “information literacy” from the Scopus database. This data was analyzed for the most frequently employed words and phrases, and grouped by country. The authors then further grouped the countries by their levels of literacy, Human Development Index ranking, the average number of citations per article, and a metric created by the authors that assessed each country’s progress in regard to the Sustainable Development Goals and population health. The results include a discussion of the differences in the ways that scholars from different cultures discuss information literacy, and a number of data visualizations to highlight differences in the data.