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Enregistrement W4200193181 · doi:10.5539/jel.v11n1p112

The Effect of the Computer Anxiety Levels of Physical Education Teachers on Distance Education Competence: Structural Equation Model Analysis

2021· article· en· W4200193181 sur OpenAlexvenueno aff
Hacer Ozge Baydar Arican

Notice bibliographique

RevueJournal of Education and Learning · 2021
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueEducation Practices and Challenges
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCronbach's alphaLikert scaleStructural equation modelingPsychologyCompetence (human resources)Physical educationScale (ratio)Distance educationAnxietyMathematics educationSocial psychologyApplied psychologyPsychometricsMathematicsStatisticsClinical psychologyDevelopmental psychologyGeography

Résumé

récupéré en direct d'OpenAlex

The aim of the present study was to examine the effects of the computer anxiety levels of physical education teachers on distance education competencies during the Covid-19 pandemic process with a structural equation model. The study group consisted of a total of 141 physical education teachers, 60 of whom were female (42.6%) and 81 male (57.4%), who worked in private or public schools in Ankara, and who were selected with the convenient sampling method. In the study, the Distance Education Competencies Scale of Physical Education Teachers”, “Computer Anxiety Scale” and the Individual Information Form were utilized as the measurement tool. The “Distance Education Competencies Scale of Physical Education Teachers” that consisted of two sub-dimensions of “Planning and Technology Use” and “Implementation and Evaluation” consisting of 18 items in a 5-point Likert structure. In addition, the “Computer Anxiety Scale” that consisted of 10 items, 5 positive and 5 negative, as well as the Individual Information Form, which was prepared by the researcher to collect data in the study. Frequency Analysis, Kolmogorov Smirnov Test, Independent Groups t-test and One-Way Analysis of Variance were used in the analysis of the data, regression and structural equation modeling were used to analyze the effects of computer anxiety on distance education competencies. Also, Cronbach’s Alpha Coefficients were obtained to determine the reliability levels of the scale and its sub-dimensions; and it was found that the reliability of the scale and its sub-dimensions was at a sufficient level. Analyzes were performed by using the SPSS 20.0 and Amos 16.00 Software at a 95% Confidence Interval level. When the study findings were evaluated, no significant differences were detected between computer anxiety levels and distance education competencies in different age groups, education levels and institution types. According to the gender variable, the computer anxiety levels of male teachers were found to be at significant levels higher than those of female teachers. When the comparisons according to the branches were examined, the computer anxiety levels differed at significant levels according to the branch types (p<0.05) and the sub-dimensions of the distance education competency scale did not differ at significant levels according to the branch types (p>0.05). When the other variables were examined, the sub-dimensions of the distance education competency scale differed at significant levels according to school levels and professional seniority years (p<0.05) and the computer anxiety scale scores did not differ at significant levels according to school levels and professional seniority years (p>0.05). According to the regression model that was created to determine the effects of computer anxiety levels on distance education qualifications, it was found that computer anxiety did not have any significant impacts on planning and technology use, implementation and evaluation sub-dimensions (p>0.05).

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: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,437
Score d'incertitude au seuil0,298

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 savante0,0000,000
Science ouverte0,0000,000
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 Opus0,027
Tête enseignante GPT0,313
Écart entre enseignants0,286 · 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'étudeQualitatif
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
Publié2021
Routes d'admission1
Résumé présentoui

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