MétaCan
Menu
Retour à la cohorte
Enregistrement W2890132376 · doi:10.18438/eblip29412

LIS Students at a Japanese University Use Smartphones for Social Communication more often than for Educational Purposes

2018· article· en· W2890132376 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

venuePublié dans une revue dont le pays d'attache est le Canada.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2018
Typearticle
Langueen
DomaineComputer Science
ThématiqueWeb and Library Services
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSocial mediaMedical educationPsychologyGraduate studentsThe InternetMedicineLibrary scienceComputer scienceWorld Wide Web

Résumé

récupéré en direct d'OpenAlex

A Review of:
 Lau, K. P., Chiu, D. K. W., Ho, K. K. W., Lo, P., & See-To, E. W. K. (2017). Educational usage of mobile devices: Differences between postgraduate and undergraduate students. The Journal of Academic Librarianship, 43(3), 201-208. https://doi.org/10.1016/j.acalib.2017.03.004
 Abstract
 Objective – To discover how undergraduate (UG) and graduate (G; “postgraduate” [PG] in the original article) students of library and information science (LIS) use mobile devices and to understand preferences and perceived barriers to educational use.
 Design – Survey questionnaire.
 Setting – University in Japan.
 Subjects – Ninety undergraduate students (30 male, 60 female) and 30 graduate students (13 male, 17 female). Nineteen additional recruits were excluded from the study due to incomplete surveys. Almost all subjects (>98%) were born between 1982 and 2002.
 Methods – Subjects were recruited without incentives from one LIS department. An online survey was conducted with the purpose of gathering information on how often devices were used for various activities, perceived barriers to mobile learning (m-learning), and demographic data. The survey was modeled on a 2015 study of LIS students in Hong Kong, Japan, and Taiwan (Ko, Chiu, Lo, & Ho, 2015). The Mann-Whitley U test was used to investigate possible significant differences between UG and G responses.
 Main Results – 94.2% of participants had smartphones with Internet access; both UG and G subjects reported weekly to daily use for social communications (email, short message service [SMS], chat, and social media) and for querying search engines. Both UG and G subjects reported using finance and banking services less than once a month. Other activities (shopping, finding locations, entertainment, sports, tools and productivity software, casual reading, academic reading, accessing reference materials, accessing libraries) for both groups fell within the range of less than once per month to weekly use. Unlike G subjects, UG subjects reported significant (p < 0.05) engagement with social media and marginal (p < 0.10) engagement with accessing libraries, and productivity tools.
 In terms of educational use, neither UG nor G subjects reported daily m-learning behaviors, instead reporting monthly to weekly browsing of online information and social networking sites, with far less (i.e., less than once a month) engagement with professional articles, e-books, learning management platforms, and several other activities (listening to podcasts, viewing videos, “other”). UG subjects reported significant marginal (p < 0.10) engagement with “other” materials, unlike G subjects. Library catalogs and databases were less likely to be used when compared to reference sources, with UG and G subjects reporting monthly or less use for these. When asked if they would use mobile library services, respondents answered “maybe interested if available”, with UG subject reporting significant marginal (p < 0.10) engagement vs. G subjects for several of these services. Regarding productivity activities, both UG and G subjects reported monthly or less use of note taking, word processing, and scheduling tools. For communication and sharing activities, subjects reported monthly or less activity for communicating with classmates, using email for study-related issues, posting to discussions on learning management platforms, posting or commenting about their studies on social networking sites, sending photos or videos to social media, moving document files, and scanning Quick Response (QR) codes. UG subjects were marginally (p < 0.10) more engaged in communicating with classmates than G subjects.
 Barriers to m-learning were not considered “high” barriers, with “low” to “medium” barriers for both UG and G subjects being small screen size, non-mobile format, difficulty typing, challenges with authentication, no Wi-Fi, difficulty reading, lack of specialized apps, and slow loading times.
 Conclusion – This study provides a snapshot of how participants used mobile devices at the time the survey was conducted. Both UG and G subjects used their devices for social communication more than for educational purposes.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,844
Score d'incertitude au seuil0,901

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,282
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,025
Tête enseignante GPT0,283
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle