Article
Linking Library to Student Retention: A Statistical
Analysis
Sidney Eng
Chief Librarian
Randolph Memorial Library
Borough of Manhattan
Community College
New York, NY, USA
Email: SEng@bmcc.cuny.edu
Derek Stadler
Web Services Coordinator
Randolph Memorial Library
Borough of Manhattan
Community College
New NY, USA
Email: DStadler@bmcc.cuny.edu
Received: 15 April 2015 Accepted: 23
June 2015
2015 Eng and Stadler. 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
-
This study analyses both library expenditure and student retention. It seeks to determine if positive correlations
found in a former study endure using more recent data or if alternative
interpretations can be made. It includes
the associate degree-granting colleges and examines whether library instruction
has a greater significance on student retention over expenditure and if library
instruction at the two-year college correlates to retention.
Methods
-
The colleges and universities included in the study grant associate, bachelor,
masters, and doctoral degrees, based on Carnegie Foundation classification. Data was analysed
to determine if a correlation exists between the library and student
persistence. Library statistics were
drawn from the Association of College and Research Libraries (ACRL) Metrics
database which provides reports collected from academic institutions. When aggregated, the ACRL report yielded
total library expenditures, total salaries of professional staff, the
professional staff full-time equivalent (FTE), fall semester student enrolment
and data from a library instruction category of ACRL surveys for associate
degree-granting institutions.
Results
-
After replicating the same mathematical approach, the single category that has
remained constant for all institutions is professional staff. While the former study’s analysis suggested that
a relationship between library expenditure and retention existed in every
Carnegie category, this study asserts that the same argument cannot be made for
master’s degree-granting institutions.
The findings here indicate that total library and professional salary
expenditure had a negative correlation.
Also, while an analysis of instruction at the two-year school level
cannot make the case that expenditure and staffing significantly influence
retention, they can justify that instruction plays a factor in whether a
student persists with their education.
Conclusion
-
The current research posits that there is no longer a relationship between
library expenditure per se and student retention. Further research is needed to resolve the
differences in the results of the study.
Since there is a correlation between library instruction and retention
at the two-year college, high-impact information literacy activities can form a
bond between the student and the institution.
Considering the low retention rates at the two-year school, a customised library instruction approach may be a solution
to improving retention.
Introduction
Recently there has been extensive discussion in the
press regarding free tuition for community colleges. Part of the debate
centered on the question of whether there is an enrolment or retention issue in
higher education. Some have suggested that if we are concerned with
educational policy or resource allocations, we should focus on the retention
part of the equation. Considering that 61.1% of undergraduate students
were retained in 2012 (U.S. Department of Education, National Center for Education Statistics (2012) there are some merits to such a suggestion. When so many students leave before finishing
their studies it poses serious educational and financial problems to the
individual and the institution.
What is the role of the library in student retention?
For the last twenty years the library community has begun to empirically
examine the potential connection of library service and student success.
Early studies suggested that academic difficulty was the most significant cause
of student withdrawal. These research
activities focused on correlating library use and retention (Mezick, 2007). More investigation quickly pointed to
the fact that a student’s integration into the social and academic structure of
the campus played a larger role than library use. In either case, the variety and quality of
library service was essential to student performance and persistence. The
question remained as how to identify what services contributed to whether a
student returned the following semester and how to measure the potential
contribution of such services.
In 2010 the Association of College and Research
Libraries commissioned the Value of Academic Libraries: A Comprehensive
Research Review and Report (VAL) to
identify the value of libraries and establish a research agenda. “Student retention and graduation” is chief
among them (p. 12). In the report, ACRL
conveyed that libraries need to provide analytical evidence that students who
engage in library instruction are more likely to graduate on time. Since 2010, several studies have examined the
potential of library instruction.
Correlations have been made between students’ participation in library
classes and grade point average (GPA) (Wong & Cmor,
2011). Other studies have concluded that
library technology instruction improves student retention. Indeed, the more technologically-prepared
students are, the more likely they will persist (Haddow
& Joseph, 2010). The VAL report also
pointed out the importance of the collegiate experience, which is evident in
the attention placed on a student’s sense of belonging in recent
literature. Often excluding questions
directly related to libraries, experience studies aim attention at the entire
student experience. To facilitate this
campus experience and give students a sense of belonging, librarians can create
institutional environments that foster retention and eventual graduation. Focusing on instruction, librarians can
affect a student’s decision whether to return to the campus the following fall
(Kuh, 2008).
Student retention and graduation is important to
higher education. A returning customer is the raison d’être for all
businesses. In academia, the returning customer is the student whom the
college wishes to retain for the complete duration of his or her academic
career. Former retention studies have shown that both academic library
expenditure and staff-to-student ratio contribute to student perseverance. However, current research suggests that a
student’s adjustment to an institution’s academic setting contributes to a
greater commitment to the college and the goal of graduation. While
qualitative studies provide a context for meaning and interpretation,
quantitative analysis may establish a potential correlation between library
instruction and retention.
Aims
This article re-examines library expenditure research
methods and investigates library instruction class participation. Mezick (2007)
analyzed both ACRL and Association of Research Libraries (ARL) data at academic
institutions, as well as retention information, and asserted that there was a
positive correlation between library expenditure and student retention
percentage. She also advanced the notion
that professional staff-to-student ratio was related to student retention. Reproducing Mezick’s
methodology with more recent data, our study analyzes both library expenditure
and student retention to determine if the positive correlations found by Mezick endure at baccalaureate, master, and doctoral
degree-granting institutions or if alternative interpretations can be
made. Secondly, using the same approach
it will calculate if a relationship exists between these variables at associate
degree-granting colleges. This category
was omitted in the previous study. Using
two fields of supplementary data and bivariate analysis, the study will also
determine whether library instruction had a greater impact on student retention
over expenditure. Lastly, data will be
analyzed to determine if library instruction at the two-year college correlates
to retention.
Literature Review
Studies of academic libraries and retention can be
categorized as either single or cross-sectional. Early retention studies concluded that
students who used the library generally performed better academically than
those that did not and had a higher percentage of persistence. One of the earliest studies was at California
State Polytechnic College, Pomona.
Kramer and Kramer (1968) uncovered a connection between library
circulation and retention. It was determined
that while 73.7% of freshmen students who borrowed books returned the following
fall, only 57% who never checked out books returned (p. 310). In another single institution study four
years later, Breivik (1977) discovered the retention
potential in library instruction at Brooklyn College. Of students who received weekly library
instruction, 77% completed course work the following semester compared with
68.75 percent who did not, with a difference of 8.25% (p. 46).
In the past decade, retention studies and literature suggest
that a student’s level of integration into the social and academic structure of
campus life play a larger role than library use in the determination of
persistence. This approach follows the
theory advocated by Tinto (1993) who argued for the importance of social
integration. Mezick’s
study analyzed library expenditures, student enrolment, and professional staff
data against student retention rates. Academic
Library Trends and Statistics: 2003 (Association of College and Research
Libraries, 2003) provided raw library data and fall-to-fall retention
percentage rates were obtained from the Integrated Postsecondary Educational
Data System (IPEDS). Since retention
data for Canadian post-secondary institutions were not provided by IPEDS,
Canadian libraries were omitted, as well as institutions that did not report
enrolment, expenditures, or retention rates.
In the end, the total study population was 586 or 47% of the population
represented in ARL/ACRL publications (p.563).
The specific expenditure categories were total library
expenditures, total library materials, monographs, serials, and professional
salaries. Data was standardized on a per
student basis to minimize the effect of institutional size but this step was
not performed for professional library staff data. Correlations between expenditure per student
and retention rates were determined by calculating Pearson correlation
coefficients (r) for each category of library expenditure within Carnegie
classification using IBM SPSS. Levels of
significance were also ascertained using the rules of thumb for interpreting
the bivariate correlation. Coefficients
of determination (r²) were calculated
to identify the percentage of variance in student retention rates that is
explained by library expenditures. A
similar method was performed to investigate the relationship between the number
of professional library staff and retentions rates (p.563-564).
Mezick uncovered that positive relationships exist between each independent
variable category of expenditure and the dependent variable of student
retention within every Carnegie category, with the strongest at baccalaureate
colleges. Mezick
also noted that personalized library service, particularly at doctoral granting
institutions, may account for a relationship between library staff salary
expenditures and student persistence.
While data suggested that students continue to demand increased library
hours and quiet study space, it also hinted that a student has a greater chance
to persist if more funds are allocated to library staffing. A larger, experienced staff has more of a
chance to interact with students and guide them in the academic setting
(p.564-565).
Emmons and Wilkinson performed a cross-sectional study
to investigate library instruction. Rather than bivariate, Emmons and Wilkinson
(2011) utilized univariate statistics, developing a
scatterplot in order to perform a regression analysis of each independent and
control variable against each dependent variable. Controlling for socio-economic status (SES)
and gender their conclusion was that the independent variables of
staff-to-student ratio and students receiving instruction had an impact on
student persistence. The more library
staff available per student provided for a greater opportunity at welcoming
interactions. Therefore, students who
were engaged were more likely to persist.
Two other institutions examined SES more closely. A Curtin University study hypothesized that
library data pointed to a relationship among library use, student engagement,
and retention. But more importantly, the
authors wanted to link these variables with student age and SES. Derived from the library’s management system,
the library use data set included number of loans, workstation logins, and
other logins such as catalogue, database, and electronic reserve (Haddow, 2013).
Ultimately, there were higher than expected rates of library workstation
logins by students from low SES backgrounds.
The contention was that low SES students may have less access to
information technology in their homes and rely on campus resources, the library
in particular (Haddow & Joseph, 2010, p. 240).
At California State University, Monterey Bay,
reference librarians initiated an ongoing informal study and focused on non-research-related
questions asked at library service desks.
It was discovered that 47% of questions did not directly relate to
library research. In fact, a majority
was about the use of computer hardware and software since the college served
primarily first-generation students who were at a low SES status and possibly
the first in their families to go to college.
Grallo, Chalmers and Baker (2012) hypothesized
that the academic library could assist in student retention through the
development of programs and services geared to help students become accustomed
to academic life.
Based on ACRL’s
recommendation, studies have examined correlations between library instruction
and GPA. One of the largest was at Hong Kong Baptist University. In the study, student library workshop
attendance and graduation GPA were examined for over 8,000 students. Results suggested that if several workshops
were offered, students had a higher GPA and were more likely to return the
following semester (Wong & Cmor, 2011, p. 464).
Another study at the University of Minnesota – Twin
Cities examined the association between a variety of library services and
GPA. Based on student logins and those
who participated in instruction sessions and reference interactions, results
suggested that freshmen first-semester undergraduate students who used the
library had a higher GPA in their second year and were more likely to return
than non-users. The mean average GPA for
students who used the library was 3.18 compared with 2.98 for those who did not
use the library (Soria, Fransen & Nackerund, 2013, p. 151).
Methods
Culling information from the years 2010 and 2011, the
current study employed methods similar to Mezick but
also extracted data from pre-baccalaureate institutions granting the associate
degree. Raw numbers were drawn from the
ACRL Metrics database which provides reports collected from academic
institutions. The colleges and
universities included in the study based on Carnegie classification grant
associate, bachelor, masters, and doctoral degrees. When aggregated, the ACRL report yielded
total library expenditures, total salaries of professional staff, the
professional staff full-time equivalent (FTE), and the fall semester student
enrolment.
To provide an accurate comparison, some institutions
were omitted or deleted. For example, if
data was erroneous, such as negative numbers for full-time professional staff,
or not included at all, the college was removed. Another criterion for removal was if
institutions reported some fields but not others. The final list yielded full data in all
fields for all colleges and universities.
For 2010 the number of schools was 1,179 and for the year 2011 it was
1,194 (see Table 1). Similar to Mezick’s methodology to minimize the effect of institutional
size, expenditure per student was calculated using fall semester student
enrolment.
Table 1
Number of Institutions by Carnegie Classification
|
2010 |
2011 |
Total |
1,179 |
1,194 |
Associates |
316 |
339 |
Bachelors |
273 |
248 |
Masters/Professional |
351 |
375 |
Doctorate |
239 |
232 |
Data was also selected from a library instruction
category of ACRL surveys for associate degree-granting institutions to seek an
argument for improved instruction at the two-year school. The first set of instruction data analyzed
was the number of instruction presentations to groups. It may also be defined as the total number of
sessions during the academic year in the category of bibliographic instruction
programs and other scheduled class presentations, orientation sessions, and library
tours. Beyond instruction, it may be for
cultural, recreational, or educational purposes, outside of the physical
library as long as it is library-sponsored.
If the library sponsors multi-session or semester credit courses, each
individual session was counted as separate events. However, meetings sponsored by other groups,
using library space, were not included.
Neither was training for library staff.
Some of the counts are based on a full tabulation but sampling was also
acceptable. Libraries are allowed to use
numbers based on a typical week that may be extrapolated to a full year. The other instruction data was previously
used by Emmons and Wilkinson - the number of participants in the instruction
presentations. It does not however
include personal, one-on-one consultation.
For multi-session classes with a constant enrolment, each student was
counted only once. Similar to the previous instruction question, in addition to
the data set, data also included if the number was based on sampling.
The decision to use both 2010 and 2011 was based on
the latest entry in retention study by Crawford (2015). While the study agreed with previous
findings, suggesting that library expenses per student had the highest correlation
with graduation and retention rates, it also pointed out that doctoral
institutions pay the most to provide library instruction. The author noted that his study was limited
by using only one year’s worth of data (p. 16).
While we attempted to replicate Mezick’s
analysis, which is not normally done in library science, we also introduced a
slightly different strategy (see Table 2).
Table 2
Comparison of retention studies
Mezick (2003) |
Eng/Stadler (2010/2011) |
Analyzed total library expenditures, professional
salaries, and staff FTE |
Same method |
Studied institutions that grant the bachelors,
masters, and doctorate degrees |
Same |
Used Carnegie classification |
Same |
Calculated the correlation coefficient (r)
and the coefficient of determination (r²) |
Same |
Used the rules of thumb for interpreting bivariate
correlation coefficients |
Same |
Analyzed data from 2003 |
Data from 2010 and 2011 |
Utilized ARL, ACRL, and IPEDS data |
Relied on the ACRL Metrics since all data is now
available from this database |
Analyzed total library expenditures as well as the
four subcategories that comprise it |
Used total library expenditures |
Analyzed only institutions that grant the bachelors,
masters, and doctorate degrees |
Added the associate degree-granting institution |
Did not analyze library instruction categories |
Examined two instruction variables |
Analysis
For the study, data was analyzed to determine if a
correlation exists between the library and student persistence. The independent variables were library
service and the dependent variable was retention. Using IBM SPSS, a Pearson correlation
coefficient (r) was calculated to
determine any interrelation between each selected category and student
retention, in degree, direction, and significance. In replicating Mezick’s
methodology, a coefficient of determination (r²) was also computed to establish the percentage of variance in
retention that is explained by library independent variables or more simply,
identifies the impact that the independent variable may have on the dependent
variable (Hamilton, 1990, p. 355).
By definition, the value of r is a measure of the covariance of two variables divided by the
product of their standard deviation.
Analysis focuses on how two variables vary in relationship to each
other. Calculation of the correlation
coefficient returns a value between
-1 and +1, with “0” indicating no relationship at all. The closer to 1 or -1 represents a strong
relationship (Prion & Haerling, 2014, p.
535). Similarly, the closer to zero the
coefficient of determination is the less likely there is a relationship between
variables. The coefficient of
determination is the square of the correlation coefficient. Mezick utilized
this to estimate the percentage of variance of the dependent variable explained
by its relationship independent variables (Cheng, Shalabh
& Garg, 2014, p. 137-138).
Results
To replicate the Mezick
study, the value of r was calculated
for the categories of total library expenditure, professional staff FTE, and
professional salaries for the years 2010 and 2011. They are displayed in Table 3. Results were analyzed using the rules of
thumb for interpreting the bivariate correlation coefficient and the coefficient
of determination. While
social and physical scientists interpret values
differently, this study, like Mezick’s, made use of
linear relationships as defined in Hamilton’s (1990) Modern Data Analysis (p. 481).
For the value r, the closer to
zero there is no relationship between variables. Weak positive or negative relationships range
from r=0.2 to r=0.49 while moderate are r=0.5
or greater.
In review, for the bachelor degree-granting
institution the correlation coefficient has remained relatively constant for
total library expenditure, professional salaries, and professional staff
FTE. Mezick’s
calculations for the value of r are listed in Table 4.
A comparison of all three years reveals that the numbers are
similar. Total library expenditure and
retention had a moderate positive relationship in 2003, 2010, and 2011, indicating
that they are directly related. While
the value of r for professional
salaries and professional staff FTE is a weak relationship, it is however
positive. The same cannot be said about
the master degree-granting institution.
In 2003, the total expenditure and professional salary coefficient
revealed a weak positive relationship.
However, the value of r for
the master degree-granting college was negative in 2010 and 2011. In fact, for the year 2011 the coefficient
reveals a weak negative relationship at r=-0.220. The doctoral degree-granting institution
calculations are an oddity. For the
categories of expenditure and salaries the value of r for 2010 was slightly negative while in 2011 it was
positive. Actually, expenditure and
retention had a moderate positive relationship in 2011 at r=+0.500.
On the other hand, the professional staff FTE
correlation is consistent between the years.
For example, in 2003, Mezick calculated the
coefficient to be +0.458, +0.231, and +0.536 for the bachelor, master, and
doctoral degree-granting institutions, respectively, while in 2011, they were
+0.432, +0.297, and +0.513.
Table 3
Values of r
in Retention for 2010 and 2011
|
Bachelors |
Masters/Professional |
Doctorate |
|||
2010 |
2011 |
2010 |
2011 |
2010 |
2011 |
|
Total Library Expenditure |
+ 0.531 |
+ 0.592 |
- 0.002 |
- 0.220 |
- 0.033 |
+ 0.500 |
Professional Salaries |
+ 0.376 |
+ 0.447 |
- 0.046 |
- 0.196 |
- 0.037 |
+ 0.486 |
Professional Staff FTE |
+ 0.447 |
+ 0.432 |
+ 0.311 |
+ 0.297 |
+ 0.242 |
+ 0.513 |
Table 4
Values of r in
Retention from Mezick study (2003)
|
Bachelors |
Masters/Professional |
Doctorate |
Total Library Expenditure |
+ 0.505 |
+ 0.318 |
+ 0.476 |
Professional Salaries |
+ 0.411 |
+ 0.255 |
+ 0.421 |
Professional Staff FTE |
+ 0.458 |
+ 0.231 |
+ 0.536 |
Table 5
Values of r² in Retention for 2010 and 2011
|
Bachelors |
Masters/Professional |
Doctorate |
|||
2010 |
2011 |
2010 |
2011 |
2010 |
2011 |
|
Total Library Expenditure |
0.282 |
0.350 |
0 |
0.049 |
0.001 |
0.0250 |
Professional Salaries |
0.141 |
0.200 |
0.002 |
0.038 |
0.001 |
0.236 |
Professional Staff FTE |
0.200 |
0.187 |
0.097 |
0.088 |
0.059 |
0.263 |
The value of r²
was also calculated and the results appear in Table 5. Using the same rules of thumb, a weak
positive or negative relationship is 0.04 or greater, while moderate is 0.25 or
higher. The figures will be used to
summarize the data in the next section.
In addition to replicating Mezick’s
analysis, this study looked at the associate degree-granting college. The values of r and r² for the years
2010 and 2011 are in Table 6. For total
library expenditure and professional salaries, the value of r indicates there is only slight or no
relationship at all, either positive or negative. In each year, the number was very near zero
and reveals that no correlation exists between them or retention. However, the calculation for professional
staff FTE was positive. For example, in
2010 the value of r was +0.185 nearly
indicating a weak relationship between the number of staff within the two-year
college library and retention.
The supplementary ACRL data examined shows the number
of library instruction classes and participants. The number of participants in instruction
classes and retention are directly related.
Looking at the first year, the value of r for number of participants was +0.207 illustrating that there is
weak positive relationship between the independent and dependent
variables. In the second it was just shy
of weak at +0.132. It can be
hypothesized that the more students enrolled in library instruction in a given
year the greater the student retention percentage the following fall. The value of r for the number of library instructions revealed a very slight
correlation, although positive. In 2010
it was +0.167, nearly weak, but in 2011 it was +0.091.
Similar to the Emmons and Wilkinson study, a case can
be made that library instruction positively impacts retention at the two-year
college. All correlation coefficients
were positive numbers. For both years
the value of r was somewhat greater
for number of participants. While the number
of instructional presentations was important, the number of participants was of
greater significance to retention.
Table 6
Associate Degree-granting Institutions
|
Value of r |
Value of r² |
||
2010 |
2011 |
2010 |
2011 |
|
Total Library Expenditure |
- 0.031 |
+ 0.007 |
0.001 |
0 |
Professional Salaries |
- 0.041 |
- 0.039 |
0.002 |
0.002 |
Professional Staff FTE |
+ 0.185 |
+ 0.102 |
0.034 |
0.010 |
Number of Presentations |
+ 0.167 |
+ 0.091 |
0.028 |
0.008 |
Number of Participants |
+ 0.207 |
+ 0.132 |
0.043 |
0.017 |
Discussion
Mezick made the argument that for 2003 data analysis suggested that a
relationship between library expenditure and retention existed in every
Carnegie classification category. It was
strongest for the baccalaureate college.
Indeed, that argument, along with professional salary expenditure, can
be made for both the years 2010 and 2011.
Using the value of r², total library and professional salary
expenditure in 2010 reveal 28% and 14% of the total variation in student
retention, respectively. In the year
2011 it was 35% for library expenditure and 20% for professional salary.
However, the same argument cannot be made for master’s
degree-granting institutions. The
findings here indicate that total library and professional salary expenditure
had a negative correlation for both years.
While not a significant negative correlation, the case can be made that
neither category affected student persistence.
One possible explanation for the change in correlation is the growth in
online learning. By the fall of 2012, students
taking at least one online class surpassed 7.1 million (Holzweiss,
Joyner, Fuller & Young, 2014, p. 311).
In the same year, the United Stated Department of Education (2012)
estimated that almost 30% of students enrolled in distance learning were at the
graduate level; while only 26% were at the undergraduate level. Currently, the
expenditure of in-house library resources is of less significance for a student
to return the following semester.
Therefore, the validity of Mezick’s 2007
hypothesis is questionable in the present time.
The anomaly of the doctoral calculations makes any
assumptions unjustified. The significant
difference between the years may be attributed to the fact that only 147
institutions reported data to ACRL in 2010 compared with 231 in 2011. Are doctoral students more independent and
self-sufficient in later years? Are more
databases and tools contributing to this independency?
The single category that has remained constant for all
institutions is professional staff FTE. For all years studied the correlation was
positive but for the most part a weak relationship. Mezick noted that
the strongest relationship between professional staff and retention was at the
doctoral-granting institution. The value
of r² for 2003 was a moderate
relationship at +0.287 or 29%. The same
applies to 2011 when 231 institutions reported to ACRL. The value of r² was +0.263 or
26%. While not a comparable positive
relationship for the years 2010 and 2011, the value of r² for professional staff at associate degree-granting institutions
was 0.185 and 0.102 respectively.
Indeed, there was only a 3% (2010) or 1% (2011) variance in student
retention based on professional staff FTE.
Although the percentage is modest, it can be argued that the professional
staff-to-student ratio is directly related to retention.
Analysis of instruction at the two-year school raises
intriguing conversation. While the
associate degree-granting colleges cannot make the case that expenditure and
staffing significantly influence retention, they can justify that instruction
plays a factor in whether a student persists.
When analyzing the year 2010 the number of library instruction classes
given influenced retention by 2%.
Furthermore, the more students enrolled in those instructions shaped the
variance in retention by 4%. Though not
as strong, the values of r² for 2011
were also positive.
Can regression analysis be applied to the variables of
library instruction and retention? In
their study Emmons and Wilkinson argued that there is a positive but weak
relationship between instruction and retention at ninety-nine institutions. In
the current study a case can be made that instruction at the two-year school
plays a minor role in persistence. Our analysis shows that the number of
students enrolled is a stronger correlation than the number of classes given.
Such a hypothesis is important when looking at the two-year school where
persistent rates are comparatively lower than at the baccalaureate institution.
Even though students are already less likely to return, they are more likely to
persist if given library instruction. Further studies will be needed to
understand this phenomenon.
By controlling for the two-year college, this study
echoes current library literature. Recent retention studies focus on single
institutions, controlling for students with a low socio-economic status. In
general, findings indicate that a higher proportion of retained students were
logging into authenticated library resources more often. In the Curtin
University study, it was hypothesized that this was the result of the awareness
of library resources through the instruction program (Haddow, 2013, p. 130). There were also higher rates of logins from
students from low SES backgrounds. The
two-year school is typically attended by students who may be from a low SES.
The contention is that these students may have less access to information
technology in their homes and rely on campus resources and the library in
particular. A City University of New
York (CUNY) library study revealed that while other low SES students may have
access to information and communications technology, whether at home or in the
library, they may not have skills to perform course-related research. Often
students shared home computer resources with other family members thus
constraining access to academic technology. While plentiful resources are
available on campus, students do not have the necessary instruction to research
efficiently (Smale & Regalado, 2014).
In 2010 ACRL called attention to the student
experience and the sense of belonging to an institution. Library instruction serves as a valuable
asset in two ways. Through technology training, library instruction is an
ancillary student experience assisting retention. Also, attention to the
first-year student needs can gear students to become accustomed to academic
life and increase their sense of belonging to the institution. The notion opens
up the possibility of expanding library service to those students who may need
the technology help and thus increase retention. By focusing on the type of
questions asked at reference desks and gearing instruction towards technology,
the library can also adjust a student to academic life and further increase
persistence.
Conclusion
Overall, available information suggests that retention
is aided by a good support network and relationships with faculty,
administrators, and yes librarians. They
provide direct research support and education.
The National Survey of Student Engagement in 2014 indicated that while
an overwhelming majority of instructors emphasized library skills only 37% of
first-year students and 36% of seniors critically evaluated the quality of an
information source (p. 14). High-impact
information literacy activities can support student success and promote
retention by emphasizing the value of creditable information. The library can serve as a bridge between
social and academic engagement to produce learning outcome. Bell (2014) argues that when librarians
become part of a student’s support network a student performs better
academically. The quality of the service
is therefore vital to student persistence.
Also, current retention studies pay particular focus on graduation. In fact, fewer than half of students who
entered college in 2007 finished school where they started. Bell offers the notion of an Alt-Higher Ed,
which is based on the new scenario wherein multiple and more affordable paths
to graduation reduce the significance of single-institution retention. His reasoning is that no single provider
retains a monopoly on a student’s college education but rather what really
counts is if the student graduates.
Under the model, institutions that wish to retain students must create
an “educational ecosystem” that matches students to the type and level of
education that allows them to graduate (p. 12).
Successful transfer and completion should be counted towards
retention.
While related studies differ in sample group, there is
one common theme. It can be best
summarized by a guide for both librarians and libraries: “there’s very strong
evidence to suggest that students tend to be more engaged with learning…if they
engage with library services, interact with library staff, and spend more time
using libraries” (as cited in Haddow & Joseph,
2010, p. 234). Such students are more
likely to persist. Hagel, Horn, Owen and
Currie (2012) provided five worthy recommendations for the library to assist in
student retention. One of these is a
close working relationship between librarian and student, and the introduction
of programs that help students commit to and engage with their library
studies. Another is collaborative
teamwork with other support services across the campus to provide students with
integrated support (p. 221). In looking
to the future, Bell (2014) suggests that academic librarians can emphasize the
delivery of individualized research assistance and focus on building research
skills. They can demonstrate how the
library can contribute to student retention by providing data that links
student persistence and satisfaction to the library’s services, resources, and
people (p. 14). These guidelines advance
the notion that the library is no longer simply bricks and mortar but rather a
place where the constructive interaction of staff and student is a catalyst for
retention.
Contrary to former research, library expenditure is no
longer directly related to student retention at all levels of academia. Regardless of how much is spent on materials
and collection support, student persistence is not a guaranteed reflection of
expenditures. While online learning
could be one of the reasons, higher education’s approach to the acclimation of
a student to college life and society in general is of greater significance. Today, the college or university stresses the
interaction of the faculty and the student body. The trend is apparent considering that
professional staff-to-student ratio is directly related and has remained
constant in the past dozen years. At the
associate degree-granting college, instruction focused on technology training,
or simply providing an academic location for computing, will form a bond
between the student and the institution.
Since the library may no longer be the “heart of the university,” it
must conform to current learning paradigm and make itself marketable
(Association of College and Research Libraries, 2010, p. 11). Lastly, considering the low retention rates
at the two-year school, a customized library instruction approach may be a
solution to retaining students. With a focused program the library can focus on
the basic needs of freshmen students who may be from a low SES. By focusing on common non-library related
questions asked at the reference desk, librarians can make the student more
adapted to the campus and college life, and of course, compel them to return
the following fall. It is high time for the academic library to align its
mission with student success by reconsidering its functions and service. At Borough of Manhattan Community College we
hope to drill deeper into the nexus between library instruction and retention
by tracking a cohort of students who have received library instruction over
their entire career in the college. We
may find certain activities to be conducing to student engagements.
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