Make a list of the types of data collected in university libraries. These range from swipe card data about student visitors to usage figures for specific websites.

As outlined in Library Impact Data Project (LIDP) (2012a)

• Demographics of students (mature/non-mature students)
• Gender of users
• Ethnicity
• Country of Domicile

As outlined in LIDP (2012b)

• Subject studied by user (Science, Health, Arts)
• Number of visits
• Number of PDF Downloads
• Hours logged in to eResources

As listed in LIDP (2012c)

• Overnight usage
• Number of eResources Accessed
• Those accessed 5 or more times
• Those accessed 25 or more times

In LIDP (2012d)

• Dropout rate aligned with usage
• Correlation between overnight use and poor grades

Note in your learning journal or blog five ways in which these datasets might be used to support analytics that could lead to the improvement of learning and/or teaching.

1 Low library usage could be used as a trigger to follow up with a student who may be having difficulty managing their time / learning. They may also have problems utilising IT equipment.

2 The usage of specific documents relating to assessments could be used to create more useful reading lists or suggest alternative research strategies.

3 Where students in a particular subject are not accessing the library resources (perhaps due to placements) perhaps a set of resources could be produced on portable storage which they could carry with them.

4 Those resources which are accessed a lot could be presented in some sort of newsletter or top 10 chart for a subject area.

5 The concentration of users and times of visits to the library could be used to produce a ‘busiest at this time’ chart to allow students to plan when they visit. They may want to be among lots of other students or prefer solitude.

PART 2 (Showers, 2014)

Does this paper include the five uses of data that you noted in your blog/learning journal at the start of this activity?

All of the uses I suggested seem to have been covered in the Showers paper.

Could all these analytics be classified as learning analytics, or just the ones that the table in the blog categorises as ‘T&L’? Or do they belong to some other subset?

I think some of the analytics such as usage data being a trigger for interventions are out-with T&L analytics.

Data literacy problems may be suggested by the data and acted upon but this is not a T&L responsibility.

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References:

Library Impact Data Project (2012a),
FINDINGS post 1: demographic differences (Online). Available at
https://library.hud.ac.uk/archive/projects/lidp/2012/08/08/findings-post-1-demographic-differences/ (Accessed 8th July 2020)

Library Impact Data Project (2012b),
FINDINGS post 2: discipline matters (Online). Available at
https://library.hud.ac.uk/archive/projects/lidp/2012/08/08/findings-post-2-discipline-matters/ (Accessed 8th July 2020)

Library Impact Data Project 2012c,
FINDINGS post 3: Dropping out (Online). Available at
https://library.hud.ac.uk/archive/projects/lidp/2012/08/13/dropping-out/ (Accessed 8th July 2020)

Library Impact Data Project 2012d,
FINIDNGS post 4: Final results and usage. (Online) Available at
https://library.hud.ac.uk/archive/projects/lidp/2012/08/13/finidngs-post-4-final-results-and-usage/ (Accessed 8th July 2020)

Showers, B. (2014) ‘Developing a shared analytics service for academic libraries’, INSIGHTS, vol. 27, no. 2: 139-46 (Online) Available at http://doi.org/10.1629/2048-7754.149 (Accessed 8th July 2020)