Teaching styles and faculty attitudes towards computer technology in teaching and learning at a college in Ontario
Notice bibliographique
Résumé
This study examined faculty teaching styles and attitudes towards the cognitive effects of computers in instruction. A survey instrument (demographic questions, a teaching style inventory (TSI), three computer attitude scales, a behavioral control, and an instructional computer use scale) was administered to full-time post-secondary faculty. The response rate was 40% with 158 useable surveys received. The demographic data analysis showed that the sample was highly representative of the population. Significant evidence (problematic reliability values and clustering results for the teaching styles) suggested that the TSI was of questionable value for this population. Faculty had significantly higher mean scores on every teaching style than the norming population. Faculty had positive attitudes towards the cognitive effects of computers in instruction but were more positive about the cognitive effects of computer technology on themselves and their students than the learning environment. Faculty felt confident about using computers and were using computers in instruction in significant numbers; however advanced users of computers in teaching were still the exception with faculty practicing ‘just enough’ learning of instructional computer use. Significant relationships were discovered among the various scales and the demographics. Women were more learner-centered but less likely to believe that instructional computer use affected them positively, and were less confident than men. Technical program faculty were more teacher-centered and confident while arts, music and theater faculty were more learner-centered. Faculty with significant computer experience but fewer years of teaching experience were more confident and faculty with significant computer experience in technical programs were more advanced users of computers in instruction. Support for the conceptual framework (the Theory of Planned Behavior) was not found as expected in the relationships between teaching style and computer attitudes. However relationships, supporting the framework, were found between instructional computer use and the computer attitude and behavior control scales. It is theorized that traditional teaching style inventories are lacking and a new conceptualization of teaching behaviors related to the use of computers in instruction is needed. In a predictive model, the learning environment and the behavioral control scales accounted for 36% of the variation in the use of computers in instruction.
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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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».