Understanding in-library use data lifecycle within Greek and Spanish higher education ecosystems
| Published date | 03 September 2018 |
| Date | 03 September 2018 |
| Pages | 13-17 |
| DOI | https://doi.org/10.1108/LHTN-10-2017-0077 |
| Author | Stavroula Sant-Geronikolou |
| Subject Matter | Library & information science,Librarianship/library management,Library technology,Library & information services |
Understanding in-library use data lifecycle within
Greek and Spanish higher education ecosystems
Stavroula Sant-Geronikolou
Introduction
Libraries are moving away from
professional norms, symbolic artifacts
and traditional structures (Jantz, 2012)
toward a new learning commons
dynamic ecosystem. Experts, in
response to European Higher Education
Area (EHEA) mandates and new job
market demands and following the
changing learning, technological and
informational paradigms suggest that
this is a good time for breakthroughs in
library practices, in terms of:
building accurate knowledge about
user behavior which can be used to
optimize existing or invent new
services;
reshaping in-library data collection
procedures to provide rigorous,
transparent and reliable data to
efficiently and trustworthily evaluate
services; and
investigating innovative ways of
capitalizing these procedures within
the wider educational context.
Seen student activity data within library
physical spaces through a learning and
development lens opens up new
avenues to capitalizing these physical
activity generated non-physical assets
by relating them to wider institutional
success, especially in times of
budgetary constraints. These student
generated data can contribute to
maximizing the present value of the
organization in the eyes of stakeholders
(Roos et al., 2005). Recording user
activities within the physical library
neither explicitly nor implicitly listed
on academic library balance sheets
should be considered a significant part
of the library’s intellectual capital
(Corrall and Sriborisutsakul, 2010) and
with great relevance to the changing
information environment, as it can
prove beneficial to measure library
effectiveness and its strategic alignment
with broader institutional goals.
Research-based evidence indicates
that there is generally a ne ed to redesign
and to readjust and repurpose library
space and practices and reimagine
library operations in tandem with
learning practice reconceptualization in
order to help faculty remodel student
metacognitive skills, further metacognitive
inter-regulatory processes (Riegelman and
Peterson, 2016) and increase student
engagement in higher education (HE)
(Thomas, 2012) within their ongoing
efforts to keep libraries relevant (Willis et
al., 2013). The necessity to systematically
collect data on daily traffic, use of
learning labs and informal learning
virtual spaces (Brown et al., 2009)are
among possible data sources that will
eventually help demonstrate the library’s
impact on institutional goals. Within this
context, academic library’s place in the
learning analytics realm and impact on
student success, innovation and strategic
planning conversation table are becoming
important topics worthy of discussion.
Beyond surveys, circulation, e-reserves,
workstation and database logins, library use
data collection integrated with learning
analytics is considered an excellent way to
demonstrate library impact on student
outcomes, as it could positively impact use
and perception variables of the reflective
explanatory Anglada Law Formula
(Anglada, 2014) thus enhancing library’s
capability to endure over time:
Sustaninability ¼Value
Cost
¼Use Disfuctions þperceptions2
Cost
(1)
Making this type of data available and
interesting to stakeholders will facilitate
academic communities’ understanding
of the library¨s relevance, value and
impact on the research process and
teaching and learning enterprise.
(Oakleaf, 2010).
While library use data and learning
analytics projects are still a blind spot
for the majority of higher education
institutions and major concerns are
being expressed on the usefulness and
applicability of systematic physical
library activity data collection
processes, the fact that traditional
library metrics still fail to capture the
value of the library to the academic
mission (Attis and Koproske, 2013;
Sinclair, 2009), has instigated a growing
interest in library data and analytics as
manifested in conferences and scholarly
publications and an increasing student
support for institutional use of their data
(Brooks, 2016). The recent proliferation
of reports and topic-related research
indicate that library involvement in
campus-wide programs is not just
one more trend but marks a
significant turning point in academic
library functions that are just as crucial
as the advent of ICTs as it is expected
to reweave communication and
collaboration workflows between the
library, the IT department, faculty,
students and student support services.
Study of library analytics and new
critical skills
In this pivotal transitionary time,
where there is a unique opportunity for
the academic librarian to become an
active proponent of the new Higher
Education paradigm, advocating to the
community learning commons’ impact
on the educational process by taking
advantage of the new tech capabilities, we
decided to embark on a study that focuses
on current in-library use data collection
processes, library learning analytics-
oriented conversations, LIS curricula
adequacy to preparing librarians to meet
challenges associated with library
LIBRARY HITECH NEWS Number 7 2018, pp. 13-17, V
CEmerald Publishing Limited, 0741-9058, DOI 10.1108/LHTN-10-2017-0077 13
To continue reading
Request your trial