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Evidence-Based Practice and Qualitative Research: A Primer for Library and Information Professionals
Author(s) -
Lisa M. Given
Publication year - 2007
Publication title -
evidence based library and information practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 14
ISSN - 1715-720X
DOI - 10.18438/b8qc7q
Subject(s) - qualitative research , quality (philosophy) , engineering ethics , best practice , management science , rigour , qualitative property , knowledge management , computer science , sociology , psychology , data science , social science , epistemology , management , engineering , philosophy , machine learning , economics
Objective - This paper discusses the importance of qualitative research in evidence-based library and information practice (EBLIP), with a focus on practical tips for evaluating and implementing effective qualitative research projects. Methods - The paper provides a brief introduction to the nature of qualitative inquiry and its status within current models of evidence assessment. Three problems of excluding qualitative research from the evidence-base in library and information studies (LIS) are identified: 1) ignoring the social sciences and humanities traditions that inform research in the field; 2) privileging of quantitative and experimental methods over others in evidence assessment; and, 3) focusing attention away from the best evidence for LIS research problems. Results - Qualitative approaches commonly used in library and information contexts are discussed, along with strategies for assessing quality in this work and some of the common ethics-related issues that researchers and professionals must consider. Conclusions - LIS professionals are encouraged to: 1) select research methods – including qualitative approaches – that best suit LIS questions; 2) design collaborative projects that combine quantitative and qualitative approaches, that will address research questions in a more complete way; 3) consider qualitative measures of rigor in assessing quality – rather than imposing quantitative expectations; and 4) revise existing models of “evidence” to recognize the value and rigor of qualitative research projects.

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