NWB2023_Extraction and analysis of citation data from student output in order to improve library instruction.pdf (628.16 kB)

NWB2023_Extraction and analysis of citation data from student output in order to improve library instruction

Download (628.16 kB)
posted on 2023-10-11, 21:21 authored by John Holmberg Runsten, Lars Våge, Daniel Fahlén

At the Mid Sweden University (MiUN) students are expected to cite relevant and domain specific intellectual authorities when writing their papers and theses. To help students achieve this, the University Library at MiUN provides instruction. Here, a proposed approach of improving library instruction is to study the sources which students cite.

Extracting references manually is labour intensive and thus unrealistic to undertake systematically. We therefore present a method, using Open Source software (AnyStyle and R), that parses, extracts, and compiles citation data from theses stored in pdf format on an institutional repository, making it possible to perform source analysis and study co-citation patterns.

Output from researchers affiliated to the same institution and active within the same field of study as the students can act as a baseline by which comparisons can be performed. These researchers are frequently the students’ teachers, and have therefore potentially played a part in assembling their required reading lists.

With this approach we propose that library instruction can be revised and improved using methods frequently employed within research evaluation. Findings can also be forwarded to teachers and course administrators, rendering the library an active partner in course development and assessment. In addition, providing information regarding inter-disciplinary influences that impact students’ as well as revealing differences between research and educational output.


Usage metrics




    Ref. manager