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Enregistrement W1842025785

Online Behavior and Cognitive Development

2007· article· en· W1842025785 sur OpenAlexaffabout
Genevieve Johnson, Jillianne Code, Nicholas E. Zaparyniuk

Notice bibliographique

RevueEdMedia: World Conference on Educational Media and Technology · 2007
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueChild Development and Digital Technology
Établissements canadiensSimon Fraser UniversityMacEwan University
Organismes subventionnairesnon disponible
Mots-clésThe InternetPsychologyCognitionWorld Wide WebComputer science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Parents of 128 children in a rural elementary school provided information on home Internet access and children’s online activities. Children were individually administered four measures of cognitive development (expressive language, metacognition, visual perception, and auditory memory) and were asked to define ten Internet terms (e.g., email, chat, website). Ability to define an Internet term was assumed indicative of experience with that application. Parent response to the open-ended item what does your child do when he/she uses the Internet at home was thematically organized into four types of Internet behavior: learn, play, browse, and communicate. Children’s ability to correctly define Internet terms as well as parent reported online learning and communicating (but not playing and browsing) were associated with increased cognitive scores. Focused and goal-directed online activities (e.g., learning and communicating) are recommended for children 6 to 12 years of age. When asked about their activities the previous day, 22% of American 8 to 10 year old children indicated that they had visited websites (Roberts, Foehr, & Rideout, 2005). Approximately 20% of Canadian 9 year-olds access the Internet through their own personal computer (Media Awareness Network, 2006). Forty per cent of Australian children aged 4 to 6 years have been online for at least two years (Nielsen//NetRatings Internet and Technology Report, 2005). All trends indicate that the number of children accessing the Internet and the amount of time they spend online are steadily increasing (DeBell & Chapman, 2006; Livingston & Bober, 2005; Statistics Canada, 2004; U.S. Census Bureau, 2005). Greenfield and Yan (2006) conceptualize “the Internet as a new object of cognition, neither a concrete artifact nor a visible social partner” (p. 393). From a developmental perspective, “the Internet is a cultural tool that influences cognitive processes and an environmental stimulus that contributes to the formation of specific cognitive architecture” (Johnson, 2006, p. 565). The Internet and Cognitive Development As children develop, their cognitive processes and abilities (e.g., language, metacognition, perception, and memory) mature in response to genetic and environmental forces (Garcia, Bearer, & Lerner, 2004). Environmental forces include parents, peers, schooling, and media (Gentile & Walsh, 2002). The Internet is not like other media “in the sense that it is used primarily for communication, information gathering, and games rather than for passively experiencing narrative stories” (Tarpley, 2001, p. 551). Further, different sites support (Dix, 2005), and different users require (Johnson, in press; LaRose & Eastin, 2004), variation in sensory stimulation and active involvement. In this regard, Internet use during the developmental years may have a greater cognitive impact than previous technological innovations (Johnson, 2006). While video games are not dependent on the Internet, the Internet provides access to many gaming experiences. Approximately one-third of the time that children are online, they report playing games (Roberts et al., 2004). DeBell and Chapman (2006) concluded that Internet use promotes cognitive development in children, “specifically in the area of visual intelligence, where certain computer activities -particularly games -may enhance the ability to monitor several visual stimuli at once, to read diagrams, recognize icons, and visualize spatial relationships” (p. 3). Greene and Bavelier (2003) noted that on a range of visual attention skills, video game players out-performed those not exposed to video games. They concluded that “although video-game playing may seem to be rather mindless, it is capable of radically altering visual attention processing” (p. 536). Reportedly, visual-spatial skills such as mental rotation of shapes are superior in those who play video games (Sims & Mayer, 2002). In a comprehensive review of the literature, Subrahmanyam, Kraut, Greenfield, and Gross (2001) concluded that cognitive processes improve by playing video games. According to early childhood educators, the Internet supports emergent literacy, builds problem-solving skills, and facilitates concept development (Lynch & Warner, 2004; Parette, Hourcade, & Heiple, 2000). Clements and Samara (2003) recommended Internet technology as a tool for improving children's learning through exploration, creative problem solving, and self-guided instruction. Fuchs and Wosmann (2005) claimed that the Internet helps children “exploit enormous information possibilities for schooling purposes and increase learning through communication” (p. 4). Jackson and colleagues (2006) provided low income children home-based Internet access and continuously recorded online behavior. “Findings indicated that children who used the Internet more had higher scores on standardized tests of reading achievement and higher grade point averages 6 months, 1 year, and 16 months later than did children who used the Internet less” (p. 429). Johnson (2006) cautioned that “current anxiety surrounding children’s Internet use should be for those whose cognitive processes are not influenced by the cultural tool” (p. 570).

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.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,054

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,043
Tête enseignante GPT0,327
Écart entre enseignants0,284 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2007
Routes d'admission2
Résumé présentoui

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