Model Correlates Many Factors to Undergraduates’ Perceived Importance of Library and Research Activities, but Low Explanation Power Suggests More Research Needed
Notice bibliographique
Résumé
A Review of:
 Soria, K. M. (2013). Factors predicting the importance of libraries and research activities for undergraduates. Journal of Academic Librarianship, 39(6), 464-470.
 
 Objective – The purpose is to analyze characteristics and perceptions of undergraduate students to determine factors that predict the importance of library and research activities for the students. 
 
 Design – Student Experience in the Research University (SERU) survey questionnaire.
 
 Setting – Nine large, public, research universities in the United States of America.
 
 Subjects – 16,778 undergraduates who completed the form of the survey that included the academic engagement module questions. 
 
 Methods – The researcher used descriptive and inferential statistics to analyze student responses. Descriptive statistics included coding demographic, collegiate, and academic variables, as well as student perceptions of the importance of library and research activities. These were used in the inferential statistical analyses. Ordinary least squares regression and factor analysis were used to determine variables and factors that correlated to students’ perceptions of the importance of libraries and research activities. 
 
 Main Results – The response rate for the overall SERU survey was 38.1%. The results showed that the majority of students considered having access to a “world-class library collection,” learning research methods, and attending a university with “world-class researchers” to be important. The regression model explained 22.7% of variance in the importance students placed on libraries and research activities; factors important to the model covered demographics, collegiate, and academic variables. Four variables created in factor analysis (academic engagement, library skills, satisfaction with libraries and research, and faculty interactions) were significantly correlated with the importance students placed on libraries and research activities. The most important predictors in the model were: student satisfaction, interest in a research or science profession, interest in medical or health-related profession, academic engagement, and academic level. 
 
 Conclusion – Based on the results of this study, librarians should be able to tailor their marketing to specific student groups to increase the perception of importance of libraries by undergraduates. For example, more success may be had marketing to students who are Hispanic, Asian, international, interested in law, psychology or research professions as the study found these students place more importance on libraries and research activities than other groups. These students may be targeted for being peer advocates for the libraries. Further research is suggested to more fully understand factors that influence the value undergraduate students place on libraries and find ways to increase the value of libraries and research activities for those demographic groups who currently rate the importance lower.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,584 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».