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Extraction and Analysis of Citation Data from Student Output in Order to Improve Library Instruction
Mid Sweden University. University Library.ORCID iD: 0000-0001-9903-0207
Mid Sweden University. University Library.ORCID iD: 0000-0002-8125-7443
Mid Sweden University. University Library.ORCID iD: 0009-0008-5168-2116
2023 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
2023.
Keywords [en]
bibliometrics, R, citation analysis, source analysis, student theses, student output analysis, library instruction, citation extraction
National Category
Information Studies
Identifiers
URN: urn:nbn:se:miun:diva-49921OAI: oai:DiVA.org:miun-49921DiVA, id: diva2:1814301
Conference
Nordic Workshop on Bibliometrics and Research Policy, October 11–13, 2023 in Gothenburg, Sweden.
Available from: 2023-11-24 Created: 2023-11-24 Last updated: 2023-11-24Bibliographically approved

Open Access in DiVA

Poster(628 kB)111 downloads
File information
File name FULLTEXT01.pdfFile size 628 kBChecksum SHA-512
2194338c6bd23e75c5d6de0c30a984f46df28bf517b7c02a5f218b2cbb452e9cd8ec55f7a322f69f681b14fe1d3fb8412a6638ac01e28b1e7a50938ff2123415
Type fulltextMimetype application/pdf

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Holmberg Runsten, JohnVåge, LarsFahlén, Daniel

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf