Attitude Toward Instructional Technology Following Required Versus Optional WebCT Usage
Notice bibliographique
Résumé
The current study sought understand the mechanisms that facilitate improvement in preservice teacher attitude toward instructional applications of computer technology. Participants comprised two groups: education students whose use of WebCT was required for completion of course assignments (n = 42) and education students whose use of WebCT was entirely optional (n = 82). All students made pre- and postcourse ratings of the perceived value of instructional technology. Across groups, positive changes from pre postcourse occurred on seven of the ten items that evaluated attitude toward instructional technology. Additionally, students required use WebCT showed a greater overall change in attitude from pre postcourse and made greater use of optional online course material relative those whose use of WebCT was optional. Requiring the use of technology in course work may generate favorable attitudes toward technology and thereby foster greater utilization of other available computer-based applications. ********** Teacher preparation programs are frequently criticized for their inability to fully prepare new teachers use technology effectively in their professional practice (Milken Exchange on Education Technology, 1999, p. i). Most teacher preparation programs reportedly offer one course in which preservice teachers are develop basic computer technology skills (Hsu & Hargrave, 2000). Cherup and Snyder (2003) proposed a more integrated approach technology in teacher education, one that includes a curriculum of technology operations, planning and designing learning environments, assessment and evaluation, professional practice, and social, ethical, and legal issues. Despite concerted and evolving postsecondary effort equip novice teachers with technological competencies, relatively few teachers routinely use computer-based technologies for instructional and when computers are used, are generally used for low-level tasks such as drills and word processing (Abdal-Haqq, 1995, p. 1). While there are numerous explanations for such limited instructional applications of technology in public education, not the least of which is lack of access equipment and inadequate training (Bosch & Cardinale, 1993; Moersch, 1999), teacher beliefs and attitudes emerge as particularly critical variables (Zhao & Cziko, 2001). Whetstone and Carr-Chellman (2001) conducted a comprehensive survey of preservice teachers' perceptions of technology and their future plans implement instructional technology. Seventy-six percent (76%) of those surveyed claimed that computers have a substantial role in school reform. When asked indicate the computer applications they felt competent apply as future teachers, 94% felt prepared use word processors, 75% felt prepared use e-mail, and 65% felt prepared use content area software. However, only 57% felt prepared use spreadsheets and only 41% and 33% felt prepared use internet applications and databases, respectively. Such survey results suggest diminishing preparation for more advanced applications of computer technology. Moreover, there is an absence of survey results for sophisticated school-based applications of instructional technology such as those supported by WebCT. WebCT is a set of web-based course tools that provide instructors and students with a range of applications such as calculating and accessing grades, posting and accessing course material, developing and publishing presentations online, posting and taking tests and surveys, accessing course syllabi, and participating in online discussion (WebCT, 2003). The Homepage is the first page appear following WebCT log in and is the page that allows users link all available WebCT tools. The WebCT Discussions tool enables the instructor place students in groups for purposes of online discussion. Instructors use the WebCT Content Module put course material online. …
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 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 | 0,001 | 0,009 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».