Click Click: Over 1,000 International College Students Detail Traditional Computer Usage
Notice bibliographique
Résumé
ABSTRACT This article investigates the availability of computers and the tasks for which computers are used by undergraduate students enrolled in business classes at 12 selected universities in 7 countries. This research will expand the literature related to traditional computer usage in the countries represented. Students were surveyed to determine similarities and differences in the use of computer technology at the universities. Countries included in the survey are: Canada, Mexico, United States (US), Belgium, France, Finland, and Spain. While there were significant differences in responses at the .001 level among students at the 12 universities, most students owned their own computers (85.6% and above), and most (86.0% and above) had Internet access outside of their university. There are some differences in computer usage between the various countries. Overall, study results indicate that all students in all countries use the computer for a significant part of their education. The findings generally support previous research on computer use by university students. INTRODUCTION In a YouTube video, Social Media Revolution, Erik Qualman (2009a) reported how quickly technology is changing. Qualman (2009a) is already at work on an updated version of this video which was posted in August 2009. Indeed, social media has now overtaken pornography as the number one activity on the web (Huffington Post, cited by Qualman, 2009a). The following timeline was among the statistics he cited: it took radio 38 years to reach 50 million users; television took 13 years; the Internet took four years; and the iPod took three years (United Nations Cyberschoolbus Document, cited in Qualman, 2009a). Then technology began to move even faster: Facebook added 100 million users in less than nine months (Mashable, cited in Qualman, 2009a) and iPhone applications had been used one billion times in nine months (Apple, cited in Qualman, 2009a). At one time, using technology may have been regarded as a way for colleges to promote independent learning and cut costs by reducing the amount of direct teaching time by staff (Nash & Maxwell, 1994). Today, however, technology and education are synonymous. College professors and IT departments are hard-pressed to keep up with new trends in technology. Indeed, when the music-sharing site, Napster, appeared, students caused college networks to collapse with their intense swapping of music and video clips. Buffalo University had to limit the data packets available to residence halls during the day, when faculty and staff were still on campus (CNN.com, non-retrievable web site, accessed Sept. 22, 2006). A University of Florida student said, My computer is turned on all day long, and I'm connected to the Internet 24 hours a day.(S. Coopersmith, non-retrievable YoungMoney.com web site, accessed Sept 22, 2006.) Twitter became the word of the year in 2009 topping Obama, H1N1, Stimulus, and Vampire(Global Language Monitor, cited in Parr 2009). Indeed, computer/Internet usage changes daily and it would be difficult to project how college students might be using it in only a few months. The latest rage is Chatroulette, which debuted in December of 2009 with 300 users. If you should log on today you would likely find 50,000 users at any one time. Invented by a 17-year old Russian, Audrey Temovskiy, it is a web camera-based chat room. A user logs on and becomes instantly connected to another random person around the world via camera. One can chat, or one can next a person and go on to another stranger (Braiker, 2010). REVIEW OF LITERATURE Technology Use in Universities Statistics are equally staggering: 35% of male college Internet users in the U.S. spend 21 or more hours online per week (EDUCAUSE survey, cited in eMarketer newletter, nonretrievable, accessed Oct. 14, 2008). In another study for Break Media, 7 out of 10 of young men aged 1 8 to 34 said they could not live without the Internet, while only three out of ten said they could not live without television. …
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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; un appel candidat d’une seule tête enseignante, 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 ».