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Enregistrement W4321844879 · doi:10.12753/2066-026x-12-047

DIGITAL LEARNERS AT THE OPEN UNIVERSITY OF CATALONIA: A SKEPTICAL VIEW OF THE PHENOMENON OF THE NET GENERATION

2012· article· en· W4321844879 sur OpenAlexaboutno aff
Marc Romero Carbonell, Montse Guitert catasús, Albert Sangrà, Mark Bullen

Notice bibliographique

RevueeLearning and Software for Education · 2012
Typearticle
Langueen
DomaineComputer Science
ThématiqueDigital literacy in education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésImmediacyPhenomenonContext (archaeology)SkepticismDigital nativeInformation and Communications TechnologyExperiential learningHigher educationPedagogySociologyMathematics educationComputer scienceMedia studiesPolitical sciencePsychologyWorld Wide WebEpistemologyGeography

Résumé

récupéré en direct d'OpenAlex

Some authors, most of them from the United States, have stated that university students born after 1982 have been profoundly influenced by the advent of digital technologies, showing different characteristics when compared to previous generations. These students, called the \\\\\\\"Net Generation\\\\\\\", are supposed to be digitally literate, continuously connected, showing a need for immediacy in receiving information, preference for social activities, being active experiential learners, showing a capacity to carry out several tasks simultaneously and being involved in the community (Oblinger & Oblinger, 2005; Prensky, 2005; Palfrey & Gasser, 2008). However, it is worth asking if that is a current observable phenomenon. Are those students at the UOC born after the 80s really more familiar with ICT tools than those born in previous generations? Do they show different study habits and learning paths? Different research lines (Kennedy et al., 2008, Bennett, et al, 2008; Guo et al, 2008, Selwyn, 2009, Bullen et al, in press) highlight that scientific data or statistics are rarely used when discussing this generation’s characteristics. The international research project, Digital Learners in Higher Education seeks to develop a sophisticated and evidence-based understanding of university learners in different institutional contexts and the perception of cultures in their use of technology in a social and educational context. This project endeavours to understand the problem in depth and to observe what the growing use of new digital technologies means for teaching and learning in higher education. This research project is led by the British Columbia Institute of Technology and includes the University of Regina and the Open University of Catalonia (UOC). The research questions of this study are: • Do postsecondary students distinguish their social and educational use of ICTs? • What impact does student social use of ICTs have on postsecondary learning environments? • What is the relationship between social and educational uses of ICTs in postsecondary education? In order to find out students’ social and educational use of ICTs in three different contexts, we use a multi-case study embedded design (Yin, 2009). The cases consist of three distinct postsecondary institutional contexts: a Canadian polytechnic teaching institution (BCIT), a Canadian research-intensive university (University of Regina) and a European fully online university (Open University of Catalonia). In the first phase of the study, BCIT partners reviewed the literature and checked some of the claims about Net Gen students. Specifically, the aims of this phase were to determine whether or not students at the BC Institute of Technology (BCIT) fit the Net Generation’s profile as portrayed in the previously revised literature, and to try to understand how BCIT learners use various information and communication technologies. The review of the literature suggests that the discourse about the impact of new digital technologies on postsecondary education has been dictated by speculation, anecdotal observations and proprietary research that is difficult to assess. We found that there is no empirical basis for most of the arguments that have been made (Bullen et al., 2009a). In the second phase of the study, a survey was designed by BCIT partners in order to gather information about students’ communication and study habits. Later, the UOC partners adapted the survey to the characteristics of their cross-over “ICT Competences” course, in which students developed a research project in groups; taking into account that this is a course studied by approximately 3,000 students per semester. In this paper, the 1,036 student responses to the survey are deeply analysed in order to demonstrate that there is no statistically significant relationship between our student’s age and the Net Generation’s characteristics. In order to go beyond our analysis and considering the features of the ICT competences’ course, the relationship between student age and their perception about the time dimension of studying online and collaborative online learning will also be deeply analysed.

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)0,005
score de la tête « metaresearch » (Gemma)0,005
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,035
Score d'incertitude au seuil0,070

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0040,007
Communication savante0,0090,004
Science ouverte0,0010,005
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,016
Tête enseignante GPT0,253
Écart entre enseignants0,237 · 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

Citations3
Publié2012
Routes d'admission1
Résumé présentoui

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