Students Use Library Resources but are Unlikely to Consult with Librarians during the Early Research Process
Notice bibliographique
Résumé
A Review of: Thomas, S., Tewell, E., & Wilson, G. (2017). Where students start and what they do when they get stuck: A qualitative inquiry into academic information-seeking and help-seeking practices. Journal of Academic Librarianship, 43(3), 224-231. http://dx.doi.org/10.1016/j.acalib.2017.02.016 Abstract Objective – To investigate where students start their research, what resources they use, and when they may consult with a librarian. Design – Ethnographic, semi-structured interviews. Setting – A mid-sized, private university located in the northeastern United States of America. Subjects – 15 students; 7 undergraduate students and 8 graduate students. Methods – Researchers gathered data as part of a larger ethnographic study conducted at the university. Interview participants were selected from among respondents to an email survey sent to all university students. Interview participants were purposefully selected to represent the student population with regards to their status (undergraduate or graduate), progress through their programs, and their majors. The semi-structured interviews focused primarily on how students approached the beginning stages of research and the types of resources used. The authors read each interview transcript to identify possible research questions, then re-read transcripts to identify codes and potential themes related to the selected research questions. Finally, they analyzed the transcripts to determine where essential themes and keywords appeared, while highlighting relevant passages and finalizing themes. Main Results – Students were more likely to seek research help from faculty members and their peers than from librarians. Graduate student interviewees were more likely to report consulting with librarians than undergraduate students. Interview themes suggest that students may not consult with librarians because they do not perceive librarians as having the subject knowledge or “insider” status (p. 227) of their professors and peers. Few students articulated an understanding of the expertise librarians could bring to a research project. When starting a research project, students were more likely to report beginning with library databases than they were Google or other open web sources. While many students also shared that they used multiple different resources in their initial stages, most also reported that they ultimately narrowed their search focus to a specific database. Students also discussed struggling with their database searching. Conclusion – The authors suggest that future research should focus on understanding the types of resources that faculty members recommend to their students, which could inform how librarians approach their work with students. Additional research related to how faculty members and students perceive librarians may also clarify the role these groups expect librarians to fill during the research process. Although results cannot be generalized to all student populations, the authors call for librarians to further explore assumptions about how students begin their research and the work academic librarians do to support students’ natural behaviours and preferences.
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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 | 0,011 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,008 | 0,004 |
| Communication savante | 0,013 | 0,008 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,016 |
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 ».