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TEXAS A&M UNIVERSITY LIBRARIES Describing The Research Library of the 21st Century: The ARL Profiles Colleen Cook, Texas A&M University Martha Kyrillidou, Association of Research Libraries TEXAS A&M UNIVERSITY LIBRARIES • ARL New Measures toolkit, StatsQUAL: LibQUAL+, ClimateQUAL, MINES for Libraries • ARL descriptive statistics 1907 - TEXAS A&M UNIVERSITY LIBRARIES Interviews – ARL Directors • What distinguishes a research library today? TEXAS A&M UNIVERSITY LIBRARIES • • • • Call for qualitative data Too limited by descriptive statistics Profiles Timeframe < 5 years TEXAS A&M UNIVERSITY LIBRARIES Themes from Interviews • • • • Collections and services The special role of Special Collections Collaborations a key means to success Physical spaces for teaching and learning primarily geared for undergraduates • How to describe value to the institution TEXAS A&M UNIVERSITY LIBRARIES Codes with Highest Salience • • • • • Instruction and information literacy Digital collections & institutional repositories Assessment Service quality – listening to users Innovative means of providing access and website issues TEXAS A&M UNIVERSITY LIBRARIES Surprisingly, little mention of: • Open access • Scholarly communication • Google • Copyright TEXAS A&M UNIVERSITY LIBRARIES Identification of Variables for a Multi-factor Index • In addition to “Reference transactions” : Virtual chat sessions, consultations • Move to substitute titles for monographic volume and serial subscription count to reflect depth of content • Interlibrary loan borrowing, lending TEXAS A&M UNIVERSITY LIBRARIES Pros of Profiles are those of Qualitative Data Generally • Ability to describe strengths & contributions signaling value to the institution in an open-ended fashion: To tell a story • Timely, easily changeable • Taken together cover the gamut of ARL services, collections, contributions • Subjective TEXAS A&M UNIVERSITY LIBRARIES Limits of Profiles are those of Qualitative Data Generally • Not numbers (some people, some provosts want them) – can’t rank, discern differences statistically • Are not simple, easily assimilated counts • Not objective • Are not represented easily in numbers and tables – require more intellectual energy to digest, draw conclusions TEXAS A&M UNIVERSITY LIBRARIES Uses of Profiles • As a source of self reported data useful to others for comparisons, best practices and vicarious learning • As a source of mining possible new variables to use in descriptive statistics TEXAS A&M UNIVERSITY LIBRARIES Questions? TEXAS A&M UNIVERSITY LIBRARIES Thank you WOOF Colleen Cook Texas A&M University Libraries eMail: [email protected] library.tamu.edu Martha Kyrillidou Association of Research Libraries eMail: [email protected] www.arl.org