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A University Program for Faculty-Librarian OER Partnerships: An Activity Systems Analysis
Yao, Zhongrui

Published30 March 2020
Type of workDoctoral dissertation
InstitutionFlorida State University
CountryUnited States, North America

ABSTRACT
The study examines how faculty-librarian partnerships function to support adopting or developing open educational resources for higher education classes. The courses in this study come from four disciplines (Psychology, Mathematics, Education, and Geography) and are at both the undergraduate and graduate level. A multiple-case study approach was employed, with data collected through interviews, observations, and documentation. In each case, librarians partnered with a faculty member. Three faculty members adopted existing OERs in their course, while two faculty members developed their own open text based on their lecture notes. For each case, activity systems analysis was used to explore the nexus of decisions and tensions that rose. In general, the faculty members considered their OER partnerships with librarians helpful and positive. At the beginning of their OER partnerships, librarians and faculty members worked together to delineate their specific responsibilities. During their partnerships, the librarians provided expertise in instructional design and copyright. Across the five cases, two strategies worked well for faculty-librarian OER partnerships: taking a team approach and motivating faculty members to adopt or develop OERs. Time constraints and lack of effective communication were two important tensions that hindered collaborations between faculty and librarians. These findings add to the OER literature focusing how faculty and librarians could work together to adopt, develop, and promote OERs.

Keywords open educational resources · librarian · activity systems analysis · faculty-librarian partnership

LanguageEnglish
RefereedYes
RightsZhongrui Yao
URLhttps://search.proquest.com/openview/28fff3172ab27a39fd0e5cab64891ad7/1
Export optionsBibTex · EndNote · Tagged XML · Google Scholar


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