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LINSCHEID
LIBRARY
Statistics! Librarians Love Them, But
What Do They Mean?
Dana Belcher, Asst Library DirectorEast Central University
iCon 2013August 2, 2013
Why Keep Statistics?LINSCHEID LIBRARY
Assessment• Measurement of services &
resources• Student Learning Outcomes!!!!
Annual Reports• Checkouts• Purchases• Instructions• Use, etc.
Surveys
Types of StatisticsLINSCHEID LIBRARY
Began working with the University Assessment Committee in 2006• All about student learning
outcomes• Struggle for libraries• We don’t see the end results
from our instructions• We don’t grade papers
• ECU focused on reference & instruction services, and high-quality resources.
AssessmentLINSCHEID LIBRARY
High Quality ResourcesLINSCHEID LIBRARY
Access Numbers 2008 2009 2010 2011Difference
from last CY % Change
Database Full-text 79,436 83,230 78,240 84,207 5,967 7.63%
ILL Borrowing Articles 520 793 568 743 175 30.81%
ILL Borrowing Books 407 413 308 527 219 71.1%
ILL Lending Articles 439 384 313 305 -8 -2.56%
ILL Lending Books 575 591 505 410 -95 -18.81%
Circulation Checkouts 8,909 10,212 9,418 10,448 1,030 10.94%
Circulation Renewals 1,101 883 872 765 -107 -12.27%
Reserve Checkouts 2,113 1,301 1,463 3,140 1,677 114.63%
E-reserves 102 282 1,352 1,676 324 23.96%
In-house use monographs 2,281 4,299 6,158* 4,710 -1,448 -23.51%
In-house use periodicals 1,530 1,534 2,020 1,305 -715 -35.4%
Total 97,413 103,922 101,217 108,236 7,019 6.93%
• Numbers made no sense• No trend could be detected• Focus was on big picture• Entire collection numbers• How does that fit into the
university?
Shell GameLINSCHEID LIBRARY
geocaching.com
Moved to total Student Learning Outcomes (SLO)• SAILS – university buy in• UNIV 1001 Freshman Seminar• UNIV 3001 General Ed Seminar
• In-house Assessment tools• SAILS 1.2 Developing
appropriate search terms• SAILS 3.2 Articulating
evaluation criteriahttp://ecok.libguides.com/assessment
Tools
Assessment RefocusedLINSCHEID LIBRARY
Freshman compared to Juniors:• Instruction numbers• Can now help in decision making• What SAILS criteria were weak –
beef up instruction in those skills• What SAILS criteria improved –
did instructions during those two years correlate?
• Provide results by discipline to academic departments – lead-in to future information literacy sessions
ResultsLINSCHEID LIBRARY
• More numbers!• Still big picture with no
correlation to academic departments or the university
• No structure among multiple library departments
• Refocus was needed, desperately
Annual ReportsLINSCHEID LIBRARY
First focus - to create a template• Provost’s requirements• Work plan items• Program data &
accomplishments• Data in context• Departmental Projects
• Personnel• Summation
TemplateLINSCHEID LIBRARY
No more big picture• Break down into academic
departments• Group departments into colleges
& schools
ILS (Innovative)• PCODE2 = Classification• PCODE3 = Major (based on
Admission’s code)• PTYPE = Type of Patron
Data in ContextLINSCHEID LIBRARY
Master file in Excel of P codes & colors:
PCODE3LINSCHEID LIBRARY
The big picture is now in smaller, more digestible chunks.
No longer what the library has done, but who and how it is being used.• Provides the needed connection
to the university & individual academic departments.
Now easier to compare these numbers to external numbers, i.e., enrollment.
ResultsLINSCHEID LIBRARY
Web Access Management (WAM)• Tracks connections to databases
from non-institutional networked computers• Laptops• Smart phones• Home computers
Tracked since 2007-2008• Never used data except to report
number of connects• Does report by PCODE3
Unused DataLINSCHEID LIBRARY
Vendor supplied COUNTER statistics• Proves resources are being used• Doesn’t tell you who uses them• Takes a lot of time gathering
them
Problem: How do connects (WAM) intersect with COUNTER statistics?
Solution: Excel and percentages
Aggregate VendorsLINSCHEID LIBRARY
Number of database connections by major for AY12-13• Majors listed with ‘total’ indicate
more than one degree available• Connects not associated with a
college/school are segregated out• Not included in
totals/percentages used in calculations
• Allows comparison of apples to apples
Handout 1LINSCHEID LIBRARY
Number of connections compared to full-text use• Eliminated any databases not providing
full-text• Inserted two rows between databases• First: divided each major’s total
connects by the total connects of all majors to come up with a percentage of connects
• Second: took the percentage of connects and multiplied by the total full-text (COUNTER) for that database
• The total for the percentage row for all majors = 100%
• The total for the full-text row for all majors = total full-text for that database
Handout 2LINSCHEID LIBRARY
At-a-glance, you can see what databases are being used by each academic department.
Reminder: these statistics only track connections made by non-institutional networked computers.
For AY1213, total connections = 1,115,228 with 249,849, or 22.40% from institution networked computers.
For AY1213, total connections by major = 762,921, or 68.41%. Remaining connections were made by non-academic department entities.
Using the previously mentioned master Excel file of patron codes, I can quickly insert college/ school codes to group academic departments.
Connects all the pieces into one picture• Enrollment numbers provided by
Academic Affairs• All other numbers provided in
annual reports• Findings:• AY1213 – not all library
statistics gathered based on PCODE3, or major
• AY1314 – steps have been implemented to gather as much as possible based on PCODE3
Master TableLINSCHEID LIBRARY
At-a-glance, the correlation between size of college/school and parts of the library.• It’s no longer that the library had 9,000+ checkouts, but that
CEP had 24% of the checkouts and they are 25% of the total enrollment.
• Easier to see where there are strengths and weaknesses.
Master Table Exploded:• Each item is coded to a library department.• All numbers entered come directly from departmental annual
reports.• Highlighted areas weren’t counted by major for AY1213.• All areas are now being counted by major for AY1314 thru use
of other ILS codes or Excel functions.
Other Master Table – designed the same & includes all OTHER statistics
Libraries need to make internal statistics correlate more to the university
• Refocused assessment to true SLOs, providing individual results to academic departments.
• Refocused annual reports to also provide individual results to academic departments.
RecapLINSCHEID LIBRARY
Dana [email protected]
580.559.5564
Any files shown or spoken about are available – just email me.
Follow-upLINSCHEID LIBRARY