Social Networking Tools for Informal Scholarly Communication Prove Popular for Academics at Two Universities
Notice bibliographique
Résumé
Objective – To investigate the adoption, use, perceived impact of, and barriers to using social networking tools for scholarly communication at two universities. Design – Cross-institutional quantitative study using an online survey. Setting – Academics working in the disciplines of the humanities and social sciences at two universities: one in Europe and one in the Middle East. Methods – An online survey was devised based on a previous survey (Al-Aufi, 2007) and informed by relevant research. The survey was piloted by 10 academics at the 2 participating universities. Post pilot it was revised and then circulated to all academics from similar faculties at two universities. Three follow up emails were sent to both sets of academics. The data was analyzed using Statistical Package for the Social Sciences (SPSS) software. Descriptive and inferential statistics were analyzed using ANOVA tests. Main Results – The survey achieved a 34% response rate (n=130). The majority of participants were from the university based in the Middle East and were male (70.8%). Most of the responses were from academics under 40 years of age. The use of notebooks was prevalent at both universities. “Notebooks” is used as a term to describe laptops, netbooks, or ultra-book computers. The majority reported use of social networking tools for informal scholarly communication (70.1%), valuing this type of use. 29.9% of respondents reported they do not use social networking tools for this purpose. Barriers were identified as lack of incentive, digital literacy, training, and concerns over Internet security. Among the non-users, barriers included low interest in their use and a perceived lack of relevancy of such tools for scholarly communication. The types of tools used the most were those with social connection functions, such as Facebook and Twitter. The tools used the least were social bookmarking tools. A one-way analysis of variance (ANOVA) test indicated that there was no significant difference at the 0.05 level between the use of social networking tools at both universities, with the exception of using tools to communicate with researchers locally and with publishers at one of the universities. Both universities use tools for communication with peers and academics internationally. The responses were mainly positive towards the perceived usefulness of social networking tools for informal scholarly communication. Conclusion – The authors conclude that despite the small sample of the community of academics investigated, there is a general trend towards increasing use and popularity of social networking tools amongst academics in the humanities and social sciences disciplines. As technology advances, the use of such tools is likely to increase and advance among academics. The authors point to pathways for future research including expanding the methods to include interviews, focus groups, and case studies. Another angle for research of interest is interdisciplinary differences in the use of prevalent tools such as Facebook and Twitter.
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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 | 0,007 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».