Learning analytics uses data to uncover ways to 1) increase student learning and 2) improve institutional contexts and practices associated with student success. Library engagement in learning analytics requires librarians to identify available library data points, investigate the potential utility of each, determine how to access the data that are deemed relevant for understanding library contributions, and discuss any data that raise security or ethical concerns. This process can enable librarians to determine, in a logical and methodical way, whether each library data point should be included or excluded from analysis as well as whether the data is likely to be useful in achieving the goals of learning analytics.(i)
For example, librarians seeking to determine whether students who interact with library reference services attain more learning outcomes (i.e., learn more), earn better assignment or course grades, are more engaged, are retained, transfer successfully, graduate/complete on time, get jobs, and/or earn more money so that they can advocate for more (or more appropriate) reference resources, encourage more faculty and students to interact with reference librarians, and/or improve reference services might wish to review data including physical desk transactions, student/faculty-librarian consultations (spreadsheets), peer research consultations, reference chat/IM/text/SMS participation (transcripts), reference email participation, referrals to librarians from other systems (advising/IPAS/early warning), archives and special collections consultations, etc.(ii)
A detailed list of data for consideration is included in section 3.7 of the LIILA report. The Library Learning Analytics Project (LLAP) also has an example of a data collection case study chart on their website.
Please see the tabs in this section for data related to specific areas of library interactions.
i. Oakleaf, M. “Library Integration in Institutional Learning Analytics” (LIILA, Nov. 15, 2018), available online at https://library.educause.edu/~/media/files/library/2018/11/liila.pdf
ii. Oakleaf, M. “Library Integration in Institutional Learning Analytics” (LIILA, Nov. 15, 2018), available online at https://library.educause.edu/~/media/files/library/2018/11/liila.pdf
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Circulation data sources that might be relevant for learning analytics efforts include:
Source: LIILA report, section 3.7
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Instruction data sources that might be relevant for learning analytics efforts include:
Source: LIILA report, section 3.7
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Reference data sources that might be relevant for learning analytics efforts include:
Source: LIILA report, section 3.7
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Facilities data sources that might be relevant for learning analytics efforts include:
Source: LIILA report, section 3.7
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Please let us know how we can improve the toolkit via this anonymous feedback form.
Share your feedback and suggestions
Please let us know how we can improve the toolkit via this anonymous feedback form.
