Edited by Steve Bamlett, Sunday, 12 Jun 2016, 16:06
Do the
exercises in 2 & 3 & then re-shape LA definition, if needed.
List
different types of data collected in HE libraries.
How, if at
all, is each part of that data used – based on:
Jones (2014); Collins
& Stone (2013); Collins & Stone (2014); Stone & Ramsden (2013)
Data
Evidence of use as ‘analytics’ in reading
Entry /
Exit System
Since a
key aim of the data might be resource optimisation (Jones 2014), then the evidenced
use of the library building itself would justify its retention or changes to
its architecture. This might be particularly useful if loans data (especially
ST loans for use within the library) could be correlated against entry.
If there
is automated exit data that duration of visit can be collected.
However,
Stone & Ramsden (2013:554) show that library entry data was the only
example of library data collected in the Lamp Project across 5 UK universities
were there was no correlation or a very small one with degree result. They
argue that this is because entry was often for the use of group study and
discussion rooms (a requisite in some programmes), use of social and / or
meeting places or use as a neutral, if quieter, space for an (unknown)
purpose.
Loans of
Hard Books
Stone
& Ramsden (2013:554) show that data collected in the Lamp Project across 8
UK universities showed a positive correlation with degree result. Of course
loan does not equate necessarily with reading, use or referencing of the
material. In this study there were
possible biases created by the fact that some tutors in some disciplines used
the study as a means of encouraging greater library use amongst their
students for pedagogic or other reasons (creating subject friendly
statistical profiles for instance). We could see a potential Hawthorne effect
moreover as a result but only in disciplines which focused the study.
These
loans vary between some demographic characteristics of learners but only
slightly, and perhaps inconclusively (Stone & Collins 2013) in
Huddersfield – but those results were not necessarily replicated to the same
effect in other universities. However, there is a strong effect of study
discipline, favouring Health & Social Sciences in Huddersfield but the
Arts in other universities (Collins & Stone 2014). It would be difficult
to attribute this to the subject discipline per se and may be an effect of
differentials amongst staffing of subjects
Use of
Short-Term Loans (max. 4 hrs) in the Library
This would
be a useful measure (and is potentially available from Durham University’s
practice) but I found no evidence of its systematic collection in the
studies. Moreover, even in the data collected across universities some did
not submit that data (particularly on entry, which strikes me as odd). If
that is so for data the libraries had been previously asked to collect, it
may be that such data is not yet seen as of value or does not exist.
Online Library
catalogue log-ins (duration)
There is
no relevant data for the 2013 attainment correlation study but this was a
variable tested between study disciplines, showing an effect size only for Arts
compared to other disciplines (p. 4). Is this however, because non-copyright
texts are available for reading free online. However, in fact this is
probably not the reason at Huddersfield since most of the effect for Arts was
created by one subject discipline, Music, with uncertain causation – and possibly
one created by combination with another non-Arts subject.
Online Library
e-resources accessed and /or downloaded
As with
hard books, Stone & Ramsden (2013:554) show that data collected in the
Lamp Project across 5 of the 8 UK universities showed a positive correlation with
degree result (3 did not submit but it is not clear why). In this study there
were possible biases created by the fact that some tutors in some disciplines
used the study as a means of encouraging greater online library use amongst
their students for pedagogic or other reasons (creating subject friendly
statistical profiles for instance). We could see a potential Hawthorne effect
moreover as a result but only in disciplines which focused the study.
Online Library
PDFs downloaded
There is
no relevant data for the 2013 attainment correlation study but this was a
variable tested between study disciplines, showing the largest effect size for
Arts compared to other disciplines (p. 4). Is this however, because
non-copyright texts are available for reading free online.
A process of
analysis which produces actionable insights by the application of analytic
methods appropriate to their contexts.
New definition:
A process of analysis which produces actionable insights related to teaching and learning (TL) by the application of analytic methods appropriate to their contexts. It is applied to a number of issues important to the design of TL, including environmental and other resources, such as libraries. (updated 12/06/2016)
Collins, E. & Stone, G. (2013) ‘Library usage and
demographic characteristics of undergraduate students in a UK university in Performance Measures and Metrics 14 (1) 25
– 35.
Collins, E. & Stone, G. (2014) ‘Understanding
patterns of library use among undergraduate students from different
disciplines’ in Evidence-Based Library
& Information Practice 9 (3) 51 – 67
Stone, G. & Ramsden, B. (2013) ‘Library Impact Data Project:
looking for the link between library usage and student attainment’ in College and Research libraries 74 (6)
546 -559.
Library Use Analytics Activity 10 Block 4
Jones (2014); Collins & Stone (2013); Collins & Stone (2014); Stone & Ramsden (2013)
Data
Evidence of use as ‘analytics’ in reading
Entry / Exit System
Since a key aim of the data might be resource optimisation (Jones 2014), then the evidenced use of the library building itself would justify its retention or changes to its architecture. This might be particularly useful if loans data (especially ST loans for use within the library) could be correlated against entry.
If there is automated exit data that duration of visit can be collected.
However, Stone & Ramsden (2013:554) show that library entry data was the only example of library data collected in the Lamp Project across 5 UK universities were there was no correlation or a very small one with degree result. They argue that this is because entry was often for the use of group study and discussion rooms (a requisite in some programmes), use of social and / or meeting places or use as a neutral, if quieter, space for an (unknown) purpose.
Loans of Hard Books
Stone & Ramsden (2013:554) show that data collected in the Lamp Project across 8 UK universities showed a positive correlation with degree result. Of course loan does not equate necessarily with reading, use or referencing of the material. In this study there were possible biases created by the fact that some tutors in some disciplines used the study as a means of encouraging greater library use amongst their students for pedagogic or other reasons (creating subject friendly statistical profiles for instance). We could see a potential Hawthorne effect moreover as a result but only in disciplines which focused the study.
These loans vary between some demographic characteristics of learners but only slightly, and perhaps inconclusively (Stone & Collins 2013) in Huddersfield – but those results were not necessarily replicated to the same effect in other universities. However, there is a strong effect of study discipline, favouring Health & Social Sciences in Huddersfield but the Arts in other universities (Collins & Stone 2014). It would be difficult to attribute this to the subject discipline per se and may be an effect of differentials amongst staffing of subjects
Use of Short-Term Loans (max. 4 hrs) in the Library
This would be a useful measure (and is potentially available from Durham University’s practice) but I found no evidence of its systematic collection in the studies. Moreover, even in the data collected across universities some did not submit that data (particularly on entry, which strikes me as odd). If that is so for data the libraries had been previously asked to collect, it may be that such data is not yet seen as of value or does not exist.
Online Library catalogue log-ins (duration)
There is no relevant data for the 2013 attainment correlation study but this was a variable tested between study disciplines, showing an effect size only for Arts compared to other disciplines (p. 4). Is this however, because non-copyright texts are available for reading free online. However, in fact this is probably not the reason at Huddersfield since most of the effect for Arts was created by one subject discipline, Music, with uncertain causation – and possibly one created by combination with another non-Arts subject.
Online Library e-resources accessed and /or downloaded
As with hard books, Stone & Ramsden (2013:554) show that data collected in the Lamp Project across 5 of the 8 UK universities showed a positive correlation with degree result (3 did not submit but it is not clear why). In this study there were possible biases created by the fact that some tutors in some disciplines used the study as a means of encouraging greater online library use amongst their students for pedagogic or other reasons (creating subject friendly statistical profiles for instance). We could see a potential Hawthorne effect moreover as a result but only in disciplines which focused the study.
Online Library PDFs downloaded
There is no relevant data for the 2013 attainment correlation study but this was a variable tested between study disciplines, showing the largest effect size for Arts compared to other disciplines (p. 4). Is this however, because non-copyright texts are available for reading free online.
Revised definition of LA
Here is the old definition:
Steve’s definition:
A process of analysis which produces actionable insights by the application of analytic methods appropriate to their contexts.
New definition:
A process of analysis which produces actionable insights related to teaching and learning (TL) by the application of analytic methods appropriate to their contexts. It is applied to a number of issues important to the design of TL, including environmental and other resources, such as libraries. (updated 12/06/2016)
Collins, E. & Stone, G. (2013) ‘Library usage and demographic characteristics of undergraduate students in a UK university in Performance Measures and Metrics 14 (1) 25 – 35.
Collins, E. & Stone, G. (2014) ‘Understanding patterns of library use among undergraduate students from different disciplines’ in Evidence-Based Library & Information Practice 9 (3) 51 – 67
Jones, M. (2014) ‘So what do we mean when we say ‘Analytics’ In LAMP. Available at: http://jisclamp.mimas.ac.uk/2014/01/09/so-what-do-we-mean-when-we-say-analytics/ (Accessed 09/06/2016).
Stone, G. & Ramsden, B. (2013) ‘Library Impact Data Project: looking for the link between library usage and student attainment’ in College and Research libraries 74 (6) 546 -559.