Reflections on Huddersfield’s data

Following on from De Montford’s blog post about the nature of their data submission, we’ve been thinking a bit more about what we could have included (and indeed what we might look at when we finish this project).

We’ve already been thinking about how we could incorporate well established surveys into data consideration (both our own internal data collection, such as our library satisfaction survey, and external surveys).  While our biggest concern is getting enough data to draw conclusions, qualitative data is naturally a problematic area: numerical data ‘just’ needs obtaining and clearing for use, but getting some information from students to find out why they do or don’t use resources and the library can be quite complicated.  Using other surveys outside of the project focus groups could be a way of gathering simple yet informative data to indicate trends and personal preferences.  Additionally, if certain groups of students choose to use the library a little or a lot, existing surveys may give us feedback on why on a basic level.

We also may want to ask (and admittedly I’m biased here given my research background!) what makes students choose the library for studying and just how productive they are when they get here.  Footfall has already clearly demonstrated in the original project that library entries do not necessarily equate to degree results.  Our library spaces have been designed for a variety of uses, for social learning, group study, individual study, specialist subject areas.  However, that doesn’t mean they are used for those purposes.  Footfall can mean checking email and logging on to Facebook (which of course then links back to computer log in data and how that doesn’t necessarily reflect studying), but it can also mean intensive group preparation e.g. law students working on a moot (perhaps without using computers or resources other than hard copy reference editions of law reports).

If we want to take the data even further, we could take it deeper into borrowing in terms of specific collection usage too.  Other research (De Jager, K (2002) has found significant correlations between specific hard copy collections (in De Jager’s case, examples include reference materials and short loan items) and attainment, with similar varying relationships between resource use and academic achievement across different subjects.  If we were to break down collection type in our borrowing analysis (particularly where there may be special collections of materials or large numbers of shorter loan periods), would we find anything that would link up to electronic resource use as a comparison?  We could also consider incorporating reading lists into the data to check whether recommended texts are used heavily in high attainment groups…

De Jager, K. (2002), “Successful students: does the library make a difference?” Performance Measurement and Metrics 3 (3), p.140-144