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Education Sciences
Article . 2024 . Peer-reviewed
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Education Sciences
Article . 2024
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Acceptance of Educational Artificial Intelligence by Teachers and Its Relationship with Some Variables and Pedagogical Beliefs

Authors: Julio Cabero-Almenara; Antonio Palacios-Rodríguez; María Isabel Loaiza-Aguirre; María del Rosario de Rivas-Manzano;

Acceptance of Educational Artificial Intelligence by Teachers and Its Relationship with Some Variables and Pedagogical Beliefs

Abstract

This study explores teachers’ acceptance of artificial intelligence in education (AIEd) and its relationship with various variables and pedagogical beliefs. Conducted at the Universidad Técnica Particular de Loja (UTPL, Ecuador), the research surveyed 425 teachers across different disciplines and teaching modalities. The UTAUT2 model analyzed dimensions like performance expectations, effort expectations, social influence, facilitating conditions, hedonic motivation, usage behavior, and intention to use AIEd. Results showed a high level of acceptance among teachers, influenced by factors like age, gender, and teaching modality. Additionally, it was found that constructivist pedagogical beliefs correlated positively with AIEd adoption. These insights are valuable for understanding AIEd integration in educational settings.

Country
Spain
Keywords

Artificial intelligence, pedagogy, Teacher, Pedagogy, artificial intelligence, L, Education, higher education, Higher education, teacher

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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
46
Top 1%
Top 10%
Top 1%
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gold