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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