Personal Blogs

types of data collected by academic (university) libraries:

• demographics: including age, gender, ethnicity, address etc.
• socio-economic status: including family income, loans, bursaries, etc.
• academic level and achievements: year, GPA, credits, etc.
• curricular activities: conferences, projects, exhibits etc.
• social and extracurricular activities: all that involve swiping the same card, faculty store, sports, cultural events, etc.
• previous library activity
• VLE activity.

five ways these may be used to support analytics that could lead to the improvement of learning and/or teaching:

1. identifying at-risk learners (not using the library in some disciplines is an at-risk sign per se) and offering/providing support.
2. identifying the trends in learning/research performed through the library. which topics are in more demand? should we recommend the department chair to establish a section on, say, 'Learning Analytics'?
3. identifying issues with the physical structuring of the library and re-designing the space accordingly. which sections are mostly used? which are not used at all?
4. in connection with #3, using library as a promotion/marketing tool. which tools in library are more relevant for our pedagogy? are we being successful in promoting them? what can be done to this end? would it be ethical?
5. identifying trends in library use. why does it decline? should we try to re-vitalize physical attendance? what other services can we provide? to which target audiences?