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2026 article

AI literacy and AI-supported chatbot adoption for educators’ professional performance

0Citations signalées — pas une note de qualité
6Institutions déclarées
5Pays d’affiliation déclarés

Résumé fourni par la source

Purpose As artificial intelligence (AI)–supported chatbots are increasingly deployed in higher education worldwide, identifying the factors that shape educators’ adoption of these tools for professional performance has become a globally relevant issue. This study investigates the key factors influencing educators’ adoption of AI-supported chatbots, with a particular focus on their perceived impact on professional performance. Design/methodology/approach We analyzed two-wave survey data collected from 535 educators employed at Chinese higher vocational and professional tertiary education to examine the relationships among key determinants, educators’ attitudes and intentions, and their adoption behavior of AI-supported chatbots for performance. Findings The results reveal that perceived usefulness, effort expectancy, AI literacy and social influence significantly affect educators’ attitudes and intentions, which in turn predict the adoption behavior of AI-supported chatbots for performance. Moreover, attitude and intention were identified as key mediators in the adoption process. Interestingly, performance expectancy and facilitating conditions exerted only limited impacts, challenging conventional assumptions of the UTAUT model in digital education contexts. Research limitations/implications By underscoring digital literacy as a critical determinant of adoption behavior, the study offers practical guidance for educational administrators and policymakers on how to reinforce institutional support and develop educators’ digital competence to enable the effective deployment of AI tools. Practical implications This study offers practical guidance for institutions and systems worldwide seeking to integrate AI-supported chatbots into vocational education. Institutional leaders should treat educators' digital literacy as a strategic priority, embedding cognitive, ethical and pedagogical dimensions of digital competence in faculty development and promotion. Policymakers can foster cross-institutional knowledge sharing and supportive infrastructures for responsible AI use. Ed-tech developers should co-design chatbot functions with teachers, while educators are encouraged to engage with AI tools critically and creatively to augment, rather than replace, professional judgment. Social implications The findings highlight both opportunities and risks for social equity in AI-enhanced vocational education. Widespread adoption of chatbots could expand access to timely support, personalized feedback and flexible learning, particularly for students with weaker academic backgrounds or limited teacher contact. However, uneven digital literacy among educators and institutions may widen existing inequalities between well-resourced and under-resourced settings. Strengthening teachers’ digital competence and providing inclusive infrastructural support are therefore essential to ensure that AI-supported tools promote, rather than undermine, fair and empowering educational outcomes. Originality/value By underscoring AI literacy as a critical determinant of adoption behavior, the study offers practical guidance for educational administrators and policymakers on how to reinforce institutional support and develop educators’ digital competence to enable the effective deployment of AI tools.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
AI literacy and AI-supported chatbot adoption for educators’ professional performance
Date Crossref
28/08/2026
Éditeur
Emerald
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Institutions déclarées

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Sujets associés

AI in Service InteractionsArtificial Intelligence in Healthcare and EducationOnline Learning and Analytics

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