Understanding Patterns of Library Use Among Undergraduate Students from Different Disciplines
Notice bibliographique
Résumé
Abstract Objective – To test whether routinely-generated library usage data could be linked with information about students to understand patterns of library use among students from different disciplines at the University of Huddersfield. This information is important for librarians seeking to demonstrate the value of the library, and to ensure that they are providing services which meet user needs. The study seeks to join two strands of library user research which until now have been kept rather separate – an interest in disciplinary differences in usage, and a methodology which involves large-scale routinely-generated data. Methods – The study uses anonymized data about individual students derived from two sources: routinely-generated data on various dimensions of physical and electronic library resource usage, and information from the student registry on the course studied by each student. Courses were aggregated at a subject and then disciplinary level. Kruskal-Wallis and Mann Whitney tests were used to identify statistically significant differences between the high-level disciplinary groups, and within each disciplinary group at the subject level. Results – The study identifies a number of statistically significant differences on various dimensions of usage between both high-level disciplinary groupings and lower subject-level groupings. In some cases, differences are not the same as those observed in earlier studies, reflecting distinctive usage patterns and differences in the way that disciplines or subjects are defined and organised. While music students at Huddersfield are heavy library users within the arts subject-level grouping arts students use library resources less than those in social science disciplines, contradicting findings from studies at other institutions, Computing and engineering students were relatively similar, although computing students were more likely to download PDFs, and engineering students were more likely to use the physical library. Conclusion – The technique introduced in this study represents an effective way of understanding distinctive usage patterns at an individual institution. There may be potential to aggregate findings across several institutions to help universities benchmark their own performance and usage; this would require a degree of collaboration and standardisation. This study found that students in certain disciplines at Huddersfield use the library in different ways to students in those same disciplines at other institutions. Further investigation is needed to understand exactly why these differences exist, but some hypotheses are offered.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».