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Enregistrement W2281890736 · doi:10.14288/1.0098718

The use of hypermedia in cooperative learning groups composed of students with heterogeneous learning styles

2010· article· en· W2281890736 sur OpenAlexaboutno aff
S. Collins

Notice bibliographique

RevuecIRcle (University of British Columbia) · 2010
Typearticle
Langueen
DomaineComputer Science
ThématiqueOpen Education and E-Learning
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHypermediaComputer scienceCollaborative learningExperiential learningLearning stylesEducational technologyCooperative learningMathematics educationKnowledge managementPsychologyHuman–computer interactionMultimediaTeaching method

Résumé

récupéré en direct d'OpenAlex

This study compared two methods of using a computer with cooperative learning groups. Hypermedia (HyperCard) and word processing (Microsoft Works) were used on a Macintosh computer by primary aged students to compile information based on a video presentation. Measures of achievement, retention and participation were made. Additionally, an attempt was made to assess learning preferences and compare performance for each of these computer methods with consideration for learning preference. Four main questions were posed: • Does the computer used interactively and non-linearly, as in hypermedia, promote better assimilation of information than using the computer linearly, as in word processing? • Does the computer used interactively and non-linearly, as in hypermedia, promote better retention of information than using the computer linearly, as in word processing? • Does the use of hypermedia in cooperative learning with groups composed of members with heterogeneous learning preferences promote participation more than word processing activities? • Does interactive hypermedia better meet the learning needs of more students than word processing regardless of learning preferences? Data were collected from sixty three primary-aged students from four schools in the Vancouver Lower Mainland area. The same computer-based test was used on students as a pre-test, post-test and retention test. Teachers assessed participation by observing individual students for one minute at random intervals. Participation was reported as an average of the number of seconds out of sixty that students exhibited on-task behavior. A computer-based learning preferences assessment was devised to measure two broad categories of learning preferences based on Howard Gardner's Seven Intelligences. The same assessment was made directly by teachers and alternate classroom workers by dividing students into the two categories of learning preferences based on their observations. Teachers also reported observations of the activities pertaining to quality of interactions, teaching demands and predictions of future learning outcomes after long term use of each method. The major conclusions of this study were: • No significant differences in achievement or retention were found between the word processing and hypermedia groups. • The HyperCard groups participated more than the word processing groups as measured by teacher ratings during the activities and as reported in the post-study teacher comments. • More time for the activities is needed to yield clearer results. • The tools used to assess learning preferences were not statistically reliable. • Learning preferences for some students are likely fluid and changing and therefore difficult to assess. • Increased participation scores for HyperCard are due to more students participating as opposed to the same participating students getting higher scores. This suggests that HyperCard involves more students regardless of learning preference. Considering these conclusions, these hypotheses were suggested: • Students use their whole minds in learning which requires an integration of dominant learning strengths. Categorizing students into groups based on discrete learning attributes has little meaning and could be harmful as a teaching practise. • It is necessary to find tools that can address the needs of divergent learning styles simultaneously. Hypermedia may be such a tool but more research is required to support this conjecture. • HyperCard has more features and is more complicated to use. Therefore more training is required to adequately use HyperCard than is required to adequately use word processing. Equivalent levels of training are required to yield clearer results. Additionally a discussion of the changing definition of literacy due to the increasing accessibility of information due to technology, stressed the importance of developing multimedia skills for students and teachers. It was suggested that the combination of hypermedia with cooperative learning will enhance communication and learning. This, in, turn,will advance the new, technology-based literacy.

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 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 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 enseignants0,155
Score d'incertitude au seuil0,991

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 technologies0,0000,000
Communication savante0,0000,001
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 Opus0,012
Tête enseignante GPT0,200
Écart entre enseignants0,188 · 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 tête enseignante, 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

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

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