TEXAS A&M UNIVERSITY LIBRARIES Colleen Cook, Texas A&M University Martha Kyrillidou, Association of Research Libraries.

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Presentation transcript:

TEXAS A&M UNIVERSITY LIBRARIES 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

TEXAS A&M UNIVERSITY LIBRARIES 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 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 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 Open access Scholarly communication Google Copyright

TEXAS A&M UNIVERSITY LIBRARIES 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 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 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 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