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Record W2041041925 · doi:10.1080/09523980903387506

Preservice teachers’ acceptance of ICT integration in the classroom: applying the UTAUT model

2009· article· en· W2041041925 on OpenAlexaffabout
Amanda Birch, Valerie Irvine

Bibliographic record

VenueEducational Media International · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsUnified theory of acceptance and use of technologyExpectancy theoryPsychologyVariance (accounting)Social psychologyBusinessAccounting

Abstract

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In this study, the researchers explore the factors that influence preservice teachers’ acceptance of information and communication technology (ICT) integration in the classroom. The Unified Theory of Acceptance and Use of Technology (UTAUT) was developed by Venkatesh et al. [MIS Quarterly, 27(3), 425–478] in 2003 and shown to outperform eight preceding models, explaining 70% of the variance in user intentions. The role of the UTAUT variables (performance expectancy, effort expectancy, social influence, and facilitating conditions) are examined and the resulting regression model accounts for 27% of the variance in user intentions with effort expectancy surfacing as the only significant predictor of behavior intention. Results and recommendations for future research in the application of UTAUT are discussed. Die Akzeptanz von IKT Integration im Unterricht von Lehramtsstudenten: Anwendung des UTAUT Modells In dieser Studie erkunden die Forscher die Faktoren, die die Akzeptanz der Informations‐ und Kommunikationstechnik‐ (ICT) Integration in den Unterricht der auszubildenden Lehrer beeinflussen. Die vereinheitlichte Theorie von Annahme und Verwendung von Technik (UTAUT) wurde von Venkatesh et al. [MIS Quarterly, 27(3), 425–478] in 2003 entwickelt. und hat acht vorhergehende Modelle übertroffen und dabei 70% des Unterschieds durch Benutzerabsichten erklärt. Die Rolle der UTAUT‐Variablen (Leistungserwartung, Bemühungserwartung, sozialen Einfluss und dem Erleichtern von Bedingungen) sind geprüft und entstehende “Zurückentwicklungs” Modellkonten zu 27% des Unterschieds in Benutzerabsichten bei der Bemühungserwartung erklärt, als die Einzige bedeutsame Vorhersage. Ergebnisse und Empfehlungen für zukünftige Forschung in der Bewerbung von UTAUT werden erörtert. L'acceptation chez les élèves‐professeurs de l'intégration des TICE dans la classe: une application du modèle TUAUT Dans la présente étude, les chercheurs examinent les facteurs qui influencent l’acceptation de l’intégration des TICE de la part des enseignants en formation initiale. La Théorie Unifiée de l’Acceptation et de l’Usage de la Technologie (TUAUT) a été mise au point par Venkatesh et al. [MIS Quarterly, 27(3), 425–478] en 2003 et s’est révélée plus performante que huit autres modèles précédents,pouvant expliquer 70% de la variance dans les intentions des utilisateurs. Le rôle des variables TUAUT (performances attendues, effort attendu, influence sociale et conditions facilitantes) est examiné et le modèle régressif explique 27% de la variance dans les intentions des utilisateurs, l’expectative d’effort apparaissant comme le seul indicateur significatif des intentions de comportement. On examine les résultats et les recommandations pour les recherches futures sur l’application de TUAUT. La aceptación de la integración de las TICs en aulas por parte de los profesores en formación inicial: una aplicación del modelo TUAUT En el presente estudio, los investigadores examinan los factores que influyen sobre la aceptación de las TICs por parte de los docentes en formación inicial. La Teoría Unificada de la Aceptación y del uso de la Tecnología (TUAUT)fue desarrollada por Venkatesh et al. in 2003 y salió con mejores resultados que ocho modelos anteriores, siendo capaz de explicar el 70% de las variaciones en las intenciones de los usuarios. Se examina el papel de las variables TUAUT (expectaciones de rendimiento, expectaciones de esfuerzo, la influencia social, y la condiciones facilitantes) y el modelo regresivo explica el 27% de las variaciones en las intenciones de los usuarios, la expectación de esfuerzo apareciendo como el único indicador significativo de las intenciones de comportamiento. Los autores discuten también los resultados y las recomendaciones para futuras investigaciones sobre la aplicación de TUAUT.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.130
GPT teacher head0.419
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations224
Published2009
Admission routes2
Has abstractyes

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