ArticleBMC psychology2025
The mediating role of work stress and the performance expectations in the effect of academic overload on the use of AI models among preservice teachers: a cross-sectional study.
Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Artificial Intelligence Literacy and the Responsible Use of Generative AI Among University Students in Peru: The Mediating Role of Self-Regulated Learning and the Moderating Effect of Technostress.European journal of investigation in health, psychology and education · 2026Article
- Human-Machine Collaboration Depth and Teacher Burnout: A Dual-Path Moderated Mediation Model of Empowerment and Depletion.Behavioral sciences (Basel, Switzerland) · 2026Article
- Mechanisms underlying university students' perceived AI threat: the mediating roles of perceived controllability and perceived effort-reward imbalance.Frontiers in psychology · 2026Article
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Authors and funding
7 authors.
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Abstract
backgroundThe integration of artificial intelligence (AI) in higher education presents complex challenges for preservice teachers facing significant academic pressures. This study examines how academic workload affects AI adoption among preservice teachers in Peru and investigates the mediating roles of work stress and performance expectations in this relationship. AI models in this context encompass generative tools for content creation, automated assessment systems, and personalized learning platforms commonly utilized in educational settings.
methodsA cross-sectional study was conducted with 876 preservice teachers from 12 Peruvian universities. Data were collected through online questionnaires measuring workload, work stress, performance expectations, and AI usage patterns. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the hypothesized relationships.
resultsThe findings confirmed that workload has a significant direct positive effect on AI model usage. Work stress significantly mediated the relationship between workload and AI usage. Additionally, work stress and performance expectations operate as serial mediators between workload and AI adoption, demonstrating how psychological mechanisms connect academic pressures to technological behaviors. STUDY IMPLICATIONS: This study provides novel insights into AI adoption among Peruvian preservice teachers, an underexplored population in educational technology research. The findings reveal the multifaceted relationship between academic workload and AI integration in teacher preparation. Educational institutions should implement stress management interventions including mindfulness training and time management workshops, while establishing realistic performance expectations through hands-on AI literacy programs that address both technical competencies and ethical considerations in technology adoption.
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