Article
A Holistic Look at Reference Statistics: Whither
Librarians?
B. Jane Scales
Reference Team Leader /
E-Projects Librarian
Washington State University
Libraries
Pullman, Washington, United
States of America
Email: [email protected]
Lipi
Turner-Rahman
Faculty
Washington State University
Pullman, Washington, United
States of America
Email: [email protected]
Feng Hao
Visiting Lecturer of
Sociology
University of Richmond
Richmond, Virginia, United
States of America
Email: [email protected]
Received: 22 June 2015 Accepted:
17 Nov. 2015
2015 Scales, Turner-Rahman, and Hao. This
is an Open Access article distributed under the terms of the Creative Commons‐Attribution‐Noncommercial‐Share Alike License 4.0
International (http://creativecommons.org/licenses/by-nc-sa/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly attributed, not used for commercial
purposes, and, if transformed, the resulting work is redistributed under the
same or similar license to this one.
Abstract
Objective
–
Washington State University (WSU) Pullman campus librarians track a diverse set
of reference statistics to gain a “holistic” look at local reference
transaction trends. Our aim was to aggregate virtual, reference desk and office
transaction data over the course of three years to determine staffing levels.
Specifically, we asked “Where should reference librarians be to answer
questions?”
Methods
–
Using Springshare’s LibAnalytics,
we generated longitudinal (2012-2014) statistics and data, to help us assess
the patterns and trends of patron question numbers, types, communication modes,
and locations in the Terrell Library. With this data, we considered current
staffing patterns and how we could best address patron needs.
Results
–
Researchers found that compiling data across modalities of location,
communication, question type, and the READ Scale led to a better understanding
of user behavior trends.
Conclusion
–
Examining and interpreting a more inclusive and richer set of transaction
statistics gives reference managers a better picture of how patrons are seeking
help, and can serve as a basis for making staffing decisions.
Introduction
Washington State University (WSU), a land
grant institution, was established in 1890. Its main campus is located in
Pullman. The largest library on campus, Holland and Terrell, houses the
humanities and social sciences collection as well as the only traditional
reference desk on campus. The library is
contained in two buildings, with the reference desk located in Terrell.
Reference services on the WSU Pullman
campus are coordinated by the Libraries’ Reference Steering Committee. This
group establishes service hours and staffing for desk and online chat services,
and co-ordinates services for the email-based LibAnswers.
With tight budgets and a changing student population, the committee was tasked
with assessing the demand for services. In 2014, the group looked at a
comprehensive set of statistics covering three years of reference services to
get a better picture of the behavior trends of patrons seeking assistance.
We had been aware that our reference
questions had declined in number for several years. Between 2012 and 2014, the
committee made incremental adjustments to the schedule and staffing of the
reference desk, based on a cursory review of data.
We implemented a tiered-reference model, a
term which Massey-Burzio (Huling,
2002) articulated. Tiered or stratified reference models use paraprofessionals
as the first point of contact for patrons needing help. These were, in our
case, a mix of undergraduate and graduate students, who were instructed to
refer patrons on to librarians and subject specialists (the next tier) if their
needs required more expertise to address and answer.
After three years taking this tactic,
however, we lacked a clear picture of how those changes met and fulfilled (or
not) patrons’ needs. To understand what patrons wanted, and where reference was
happening, the committee reviewed a comprehensive set of statistics spanning
several years. The question the committee posed to the data was,
“Where is reference happening in Terrell Library, and at what level of
complexity? In which location(s) are the librarians most needed to answer
reference questions, and how does the data show this?”
Literature Review
There is little debate that academic
library reference services have changed in the last several years. Tyckoson (2012) points out that, while the
concepts of what constitutes reference services have remained stable since the
1870s, the tools and skills used to deliver those services have evolved
dramatically. Our means of communication with patrons, staffing pressures,
assessment practices, and information access have all contributed to a more
complex and nuanced view of reference.
Many have also described the downturn in
the use of traditional academic reference services. Reference transactions have
declined significantly. Martin (2009)
cites statistics from the Association of Research Libraries (ARL) that document
this downturn. Coffman (2012)
describes these changes as a “decline of the library empire.” The result of
this has been dramatic. Some universities have abandoned the reference desk,
and replaced it with other models of patron assistance (Lederer & Feldmann,
2012). Others have tried new models such as combined reference desks and
tiered services, to form new collaborative models (Meserve, Belanger, Bowlby, & Rosenblum, 2009;
Deineh, Middlemas, &
Morrison, 2011; Dinkins & Ryan, 2010).
These changes challenge library managers.
Multiple models of reference mean different methods of collecting transaction
statistics, and require a more intensive and inclusive look at data. King and Christensen-Lee (2014)
prefaced their study by reviewing longitudinal trends of patrons’
question-types, as well as overall trends specific to email and online chat
reference, at the Valley Library at Oregon State University.
Baro, Efe, and Oyeniran (2014) looked at a more expansive set of
possible reference channels used within the universities of Nigeria by
surveying librarians. Specifically, they considered: in-person visits,
Facebook, telephone, short message service (SMS), instant messaging, and email.
The authors’ consideration of so many means of communication is unique, and
necessary in order to discover the preferred method of their patrons to ask
questions.
When the WSU’s Libraries’ Reference
Steering Committee decided to evaluate services provided by the largest, most
used library on the Pullman campus, members looked to the literature for
guidance. The committee found the recommendations in Kern’s 2006 article a good
basis for the study. Kern advises librarians to think “...about your reference
services as a single reference service with many modes of communication.” She asks researchers to delineate a clear and precise question to ask of
their statistics before embarking on surveying the data.
Methodology
In order to understand where questions
were being answered, and the nature and complexity of those questions, the WSU
Libraries’ Reference Steering Committee looked at a multifaceted set of data:
IM (instant messaging), LibAnswers, email, phone,
in-person reference desk, and in-person office visits. Implicit to this
research was an examination of how the tiered reference model was working.
Since 2012, the reference team has used Springshare’s LibAnalytics, a
popular tool reviewed by Dworak (2011).
LibAnalytics facilitates the customization and
consolidation of reference transaction data across communication modes. Both Flatley and Jensen (2012) and Gossett, Stephan, and Marrall
(2012) describe this tool’s flexibility.
After every transaction, library staff
(both librarians and student employees) record their location, type of
question, mode of communication, READ Scale difficulty, length of the
transaction, and whether or not the exchange required the use of government
documents. The interface provides reference workers multiple forms, including
text boxes, check boxes, radio buttons, Likert scale, and multiple column
categories of information to characterize a transaction (see Figure 1).
Table 1 outlines the various data points
that staff record after each reference transaction. Only a few points need to
be further explained. The Contact Type includes the various communication modes
patrons use to request information from us. Currently, there are five options
available.
Figure 1
LibAnalytics Transaction screen as configured by the WSU Pullman
libraries.
Table 1
Data Types Recorded for Reference
Transactions
Contact Type |
Person-to-person, Telephone, Instant
Messaging (IM), Email, LibAnswers (a variation of
email) |
Level of Question Difficulty |
READ Scale (Reference Effort Assessment
Data) – indicates the complexity of the question, and the amount of effort
necessary to answer the question on a scale of 1 to 6 |
Question Type |
Policy, Technology, Directional,
Reference |
Location & Service Points |
Terrell Library was the consistent
“location.” Service points included in
this study included Reference Desk and Office |
READ Scale assessment, devised by Gerlich and Berard (2007), is a
qualitative measurement of the amount of effort and knowledge necessary to
answer a question. Questions deemed a READ level 1 require no specialized
knowledge, so that staff can answer them without consulting a database or our LibGuides. Questions assessed at levels 2 and 3 require
increased knowledge and effort to answer. Student employees, who participate in
our tiered reference model, are trained to recognize the point at which a
question should be passed off or referred to a subject specialist librarian.
These are considered the higher-end level 3 questions.
In addition to tracking the READ Scale
levels of questions, we track a set of locally identified and defined “Question
Types.”
Question Type
Locations used by reference staff for this
study included the Terrell reference desk and the librarians’ offices. Those
options can be seen illustrated in Figure 1 under the Location and Service Points columns (see Table 1).
The authors extracted the data from LibAnalytics, to increase the reliability and correct
interpretation of the information. The charts, tables, and figures were
organized in a single document before our analysis began. Lastly, we reviewed
Terrell Library gate counts between 2012 and 2014.
The committee also combined these
different data points, figuring monthly and semester averages of Terrell
reference transactions. In an effort to account for any other factors that
affect the number and quality of reference transactions, we gathered data on
how our Springshare LibGuides
were accessed. While it is not reasonable to conclude that a reference question
was answered with every access of a LibGuide, the
group saw value in looking at overall usage trends. Similarly, we looked at any
changes in foot traffic into the Terrell Library by gathering gate count data.
Results
Our first interest was documenting the
change in the number of reference transactions from the two most common
Location and Service Points: the Terrell reference desk and librarian offices.
Table 2 contains the monthly average number of questions answered at the
Terrell reference desk over the last several years.
Between 2012 and 2013, the number of
average monthly questions answered at the desk declined by 16%. A more
significant decline in reference desk transactions was recorded in 2014, when
the average number of questions librarians received at the Terrell reference
desk every month dropped to 584: a 35% decline from 2012, and a 22.5% decrease
from 2013.
During the same time period, the average number of
questions librarians answered in their offices declined 33% from 2012 to 2013,
but increased slightly by 4.4% from 2013 to 2014.
Table 2
Monthly average number of office and reference desk
questions by for 2012, 2013, and 2014
Year |
Monthly Average of
Reference Desk Questions Answered |
Monthly Average of Office Questions
Answered |
2012 |
898 |
135 |
2013 |
754 |
90 |
2014 |
584 |
94 |
Table 3
Temporal Look at Communication Modes in Librarian
Offices
Transactions in 2012 |
Transactions in 2013 |
Transactions in 2014 |
|
In-person |
427 (22%) |
71 (7%) |
85 (8%) |
Telephone |
164 (8%) |
148 (14%) |
87 (8%) |
IM |
640 (33%) |
311 (29%) |
87 (8%) |
Email |
323 (17%) |
244 (23%) |
450 (40%) |
LibAnswers |
395 (20%) |
304 (28%) |
415 (37%) |
Using LibAnalytics, the
reference committee then looked for trends in the data points represented in
Table 1. Contact types did not significantly change at the reference desk
between 2012 and 2014. For example, while the number of questions answered at
the desk declined over those years, the percentage occurring “in-person”
changed only 1%, from 93% in 2012 and 2013 to 94% in 2014. Telephone calls
hovered between 4% and 5%. IM reference and email reference at the desk
remained stable around 3% and 0%, respectively.
Reference transactions that took place within
librarian offices, however, changed much more (see Table 3). The
percentage of questions answered via email and LibAnswers
has risen significantly, from a combined 37% in 2012 to 77% in 2014.
Next, we looked for trends in the READ levels recorded
by library staff at the Terrell reference desk and Terrell offices over the
same three year time period. We noted that in 2012, it was more common for
staff to forget to record the READ level, so data for many transactions were
not recorded. Over time, we became better at understanding the use of the READ
Scale, and used it more frequently. For example, in 2012 a monthly average of
53 transactions, which accounts for 33% of the total transactions that took place
in librarian offices, was not assigned a READ number. In 2013, the number of
unassigned transactions fell to 5%. By 2014, the percentage of office
transactions that did not have a READ Scale number assigned was only 3%. The
averages in Table 4 below include only those transactions that were recorded
with a READ Scale number.
READ value 1-3 questions (those which require less
effort to answer) comprise the bulk of questions at the reference desk, while
those READ values 4 and 5 have decreased. This is an inverse of the situation
in the librarian offices. READ value 1 in librarians office fell dramatically,
whilst value 2 remained constant. READ values 3, 4 and 5 increased from 49% in
2012 and 58% in 2013, to 62% in 2014. Temporary employees (TEs) providing
reference service give assistance for questions including some with READ value
3. READ value 3 questions which are out of the TEs’ area of study, and all of
those of READ value 4 and up are transferred or referred to a librarian by the
temporary employees. Referral can happen either by email or by furnishing
contact information for the appropriate subject specialist.
Table 4
Monthly Averages of reference desk questions and
office questions by READ values, 2012-2014
Reference Desk Questions |
|||
READ Values |
Monthly READ Value
Averages for 2012 |
Monthly READ Value
Averages for 2013 |
Monthly READ Value
Averages for 2014 |
1 |
187 (37%) |
287 (40%) |
248 (44%) |
2 |
161 (32%) |
252 (35%) |
179 (31%) |
3 |
125 (25%) |
160 (22%) |
127 (22%) |
4 |
30 (6%) |
24 (3%) |
14 (2%) |
5 |
6 (1%) |
2 (0%) |
1 (0%) |
6 |
0 |
0 |
0 |
Office Questions |
|||
1 |
33 (30%) |
4 (5%) |
5 (5%) |
2 |
27 (25%) |
22 (26%) |
25 (27%) |
3 |
38 (35%) |
43 (51%) |
47 (51%) |
4 |
9 (8%) |
12 (14%) |
12 (13%) |
5 |
2 (2%) |
3 (4%) |
3 (3%) |
6 |
0 |
0 |
0 |
Table 5
Monthly Averages of Question Types at the Terrell
Reference Desk and Librarian Offices January 2012-December 2014
Reference Desk |
|||
Monthly Averages for 2012 |
Monthly Averages for 2013 |
Monthly Averages for 2014 |
|
Policy |
12 (1%) |
32 (4%) |
13 (2%) |
Technology |
125 (14%) |
150 (20%) |
113 (19%) |
Directional |
301 (34%) |
258 (34%) |
186 (32%) |
Reference |
459 (51%) |
313 (42%) |
272 (47%) |
Offices |
|||
Policy |
4 (2%) |
11 (12%) |
15 (16%) |
Technology |
28 (17%) |
22 (24%) |
32 (34%) |
Directional |
49 (30%) |
9 (10%) |
7 (8%) |
Reference |
83 (51%) |
48 (53%) |
39 (42%) |
The next set of tables displays trends in the types of
questions asked. Table 5 shows a slight dip in Reference questions – those
queries related to searching for and finding information. Technology questions
at the desk, on the other hand, have increased by 5%. The greater percentage of
Policy questions in 2013 was partly due to some confusion as to what
constituted that type of question. After some training and discussion, the
group of librarians and staff reached a broader consensus on what constitutes
Policy questions, which changed how those were recorded. Generally, Table 5
shows that the percentages of each of the Question Types have remained
consistent at the Terrell reference desk.
Table 5 demonstrates real changes occurring in the
type of questions librarians are seeing in their offices: increasingly, a higher
percentage concerns Policy and Technology. The percentage of Reference and
Directional questions has dipped.
We examined how reference hours (the number of hours
that the Terrell reference desk offered services) and the staffing level
(number of librarians and staff hours spent at the reference desk) changed over
the three years, comparing numbers by like semester, to track the trends. Table
6 shows that the hours of service have dropped 9% during Spring
and Fall semesters.
Table 7 shows that between 2012 and 2014, the average
number of hours the desk was staffed during the Spring
semester dropped almost 12% (from 223 to 198). Average hours for staffing
during the Fall dropped 13% (239 to 210
Next, we looked at the changes in reference desk
staffing in terms of library staff vs. graduate student worker or temporary
employees (TEs) assigned to the desk. The TEs consisted of primarily graduate
students, as well as a few select undergraduates. Table 8 shows that the role
of TEs at the desk has increased and librarian time has decreased. TEs now
staff the desk at almost the same level as librarians. There are rarely two
librarians on the desk simultaneously. More commonly, one librarian and a TE,
or two TEs, are at the desk at any time.
Table 6
Number of Regularly Scheduled Hours per Week in which
the Terrell Reference Desk Provided Service
Year |
Semester |
Number of Regularly
Scheduled Hours per Week |
2012 |
Spring |
46 |
|
Summer |
20 |
|
Fall |
46 |
2013 |
Spring |
46 |
|
Summer |
20 |
|
Fall |
42 |
2014 |
Spring |
42 |
|
Summer |
20 |
|
Fall |
42 |
Table 7
Terrell Reference Desk Staffing Levels 2012-2014
Spring 2012 |
Spring 2013 |
Spring 2014 |
|
Total hours staffed |
1112 |
1299 |
988 |
Total Questions |
9632 |
6855 |
5729 |
Average hours staffed per
month |
223 |
260 |
198 |
Hours to Question Ration |
.12 |
.19 |
.17 |
Summer 2012 |
Summer 2013 |
Summer 2014 |
|
Total hours staffed |
285 |
302 |
295 |
Total Questions |
4605 |
2870 |
1173 |
Average hours staffed per
month |
95 |
101 |
98 |
Hours to Question Ration |
.06 |
.11 |
.25 |
Fall 2012 |
Fall 2013 |
Fall 2014 |
|
Total hours staffed |
955 |
742 |
843 |
Total Questions |
8203 |
5945 |
2943 |
Average hours staffed per
month |
239 |
186 |
210 |
Hours to Question Ration |
.12 |
.12 |
.29 |
Table 8 also compares staffing levels for librarians
and TEs, and provides an hours-to-questions ratio. The ratios have increased
between 2012 and 2014, meaning that more time was spent per question (including
time between questions).
The researchers also decided to incorporate data not
previously considered in past reference service assessment. By collecting data
on the use of LibGuides, a Springshare
product which facilitates the creation of online content by non-programmers, we
tracked additional patron activity (See Table 9). Over the past five
years, LibGuides have replaced many of the Libraries’
web sites, and serve as informational resources for instruction and research.
Between 2012 and 2014, the use of the WSU Libraries’ LibGuides
increased 6.4%.
Finally, we looked at annual gate counts for the
Terrell Library, to see if there was any possible correlation between
in-library reference traffic and overall traffic. Between 2012 and 2014, foot
traffic in the Terrell Library actually increased by 3.3%. Some part of this
increase stems from the library going to a 24/7 operational schedule in 2014.
See Table 10.
Table 8
Librarian Hours vs. Temporary Employee Hours at the
Terrell Reference Desk for Spring and Fall Semesters
2012-1014
Average Librarian Hours per Week |
Average TE Hours per Week |
Percent of Weekly Staffed Hours by TEs |
|
Spring 2012 |
46.5 |
21 |
31% |
Fall 2012 |
53 |
12 |
18% |
Spring 2013 |
54 |
24 |
31% |
Fall 2013 |
32.5 |
23 |
41% |
Spring 2014 |
33 |
27 |
45% |
Fall 2014 |
33 |
23 |
41% |
Table 9
LibGuide Views 2012-2014
Year |
Views of Published LibGuides
in Thousands |
2012 |
217.4 |
2013 |
242.2 |
2014 |
231.3 |
Table 10
Gate Counts for Terrell Library 2012-2014
Year |
Gate Counts (in the Millions) |
2012 |
1.033 |
2013 |
1.037 |
2014 |
1.067 |
Discussion
The committee took considerable time to understand how
this data informed answers to our research questions: “Where is reference happening, and at what
level of complexity? Where are librarians most needed?”
The university population seems increasingly
comfortable accessing online information from the Libraries. Evidence of this
can be seen in a) the increased use of LibGuides, and
b) the rise in number of email and LibAnswers
transactions. The latter composed 77% of questions answered in librarian
offices in 2014. This indicates that librarians are more needed in their
offices where LibGuide maintenance is more likely to
occur, and where the other online transactions can happen without the
interruption or time constraints one experiences at the desk.
The steep drop of in-person transactions at the
Terrell reference desk seen in the data occurred when building hours actually
expanded, and gate counts were rising. Students are entering the library to use
it as a study space, without seeking research assistance from traditional
services.
It also marks the time we introduced a tiered
reference model at the Terrell desk. Evidence that the tiered reference model
functions as we envisioned can be seen in the decreasing difficulty of the
questions answered at the reference desk, and the increased difficulty of those
addressed from offices. We hypothesize that the increase of READ value 3, 4,
and 5 questions in the library offices is a result of the bifurcation of
reference service.
Staffing changes at the reference desk have also
contributed to this transition. We’ve noted (see Table 8) that more time is
spent per question at the reference desk, which economically, is usually not
optimal. However, with heavier reliance on student workers to field these
questions, this has become less costly, because they do not earn as much per
hour as a librarian.
Staffing changes over the years have been justified,
as they have allowed librarians more time to maintain LibGuides
and address complex questions, and TEs to field simpler ones. The data suggests
that we continue the trend of using graduate students on the desk, and
encourage librarians to provide more specialized assistance from their offices.
By incorporating Kern’s (2006) call for a holistic approach, and articulating a
research question before beginning our analysis, the reference committee was
better able to identify the data that address our research questions, and plan
ahead.
Conclusions
A holistic look at reference statistics means
considering all modes of reference service delivery. Kern (2006) recognized
reference as a system of communication modes, which should be considered as a
whole.
The authors have looked at a comprehensive set of data
from reference transactions over multiple communication modes and staffing
configurations to ask, essentially, “What is happening to reference?” An
analysis of our data has demonstrated the growing significance of online
transactions occurring in librarian offices, despite IM chat reference numbers
being low. The tiered-reference model has largely facilitated this change,
allowing librarians more time to work in their offices creating online guides,
and address more complex questions from patrons.
Many questions remain unanswered. For example, we
cannot say conclusively why reference transactions dropped so quickly during
the study period, but we know that the trend is not unique to WSU. The data
does not necessarily support any cause-and-effect hypothesis, but rather
provides us a few snapshots of our reference services over three years.
There are other factors affecting reference services
that are difficult to quantify, and are outside the realm of this paper: for
example, library instruction sessions, changes in course assignments, and
changing student demographics and skill sets.
We will continue tier-modeled reference, with layered
points of discovery, complexity and specialization. The increased use of email,
LibAnswers, and LibGuides
suggests a developing library user who is very comfortable engaging and
interacting with multiple sites within multiple tiers to discover information.
It indicates that the university community is comfortable finding their
information from the Libraries, but values it being at their fingertips.
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