Examining the relationships between artificial intelligence literacy, AI-TPACK, job satisfaction, and well-being among teachers through structural equation modeling
Bibliographic Data
| ID | 21283458 |
|---|---|
| Authors | Bünyami Kayalı (0000-0001-6419-9088, Bayburt University, corresponding author), Şener Balat (0000-0002-9683-1778, Bingöl University), Mehmet Yavuz (0000-0001-9870-0694, Bingöl University) |
| Year | 2026 |
| Volume | 268 |
| Pages | 107297 |
| Publication date | 2026-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Acta Psychologica (JOURNAL) |
| Journal identifiers | ISSN: 0001-6918 • E-ISSN: 1873-6297 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.actpsy.2026.107297 |
| PMID | 42341558 |
| OpenAlex | W7165786563 |
| Language | EN |
| References cited | 45 |
This study explores the relationships between teachers' artificial intelligence literacy (AIL), AI-TPACK competencies, job satisfaction, and well-being. Survey data from 350 in-service teachers were analyzed using PLS-SEM to examine how AI-related competencies are associated with professional and psychological outcomes. The findings reveal that AIL strongly predicts AI-specific knowledge, especially AI-TCK, AI-TK, AI-TPCK, and AI-TPK, with a moderate influence on traditional pedagogical knowledge. At the job satisfaction level, AI-TCK and general pedagogical knowledge are positively associated with satisfaction, while AI-TK has a negative relationship. Mediation analyses show that AI competencies influence well-being through job satisfaction. AI-TCK and pedagogical knowledge are positively associated with well-being indirectly through job satisfaction, whereas AI-TK shows a negative indirect association along the same pathway. The study suggests that AI-related competencies are linked to teachers' work-life outcomes, and highlights job satisfaction as the key mediator between AI competence and well-being. Because the design is cross-sectional and self-reported, these relationships are interpreted as associations rather than causal effects. The study advocates for integrating AI in ways that support pedagogical development rather than just technical skills
Association (psychology) · Competence (human resources) · Emotional intelligence · Job attitude · Job satisfaction · Mediation · Structural equation modeling · Digital literacy in education · Online Learning and Analytics · Technostress in Professional Settings
Teachers’ professional competence and wellbeing
Technological Pedagogical Content Knowledge (TPACK)
A Review of Self-Determination Theory’s Basic Psychological Needs at Work
Dispositional effects on job and life satisfaction
Impact of Educational Technology on Teacher Stress and Anxiety
An index of job satisfaction.
Modelagem de Equações Estruturais com Utilização do Smartpls
On the outcomes of teacher wellbeing
Teachers’ AI-TPACK
In search of artificial intelligence (AI) literacy in teacher education
Impact of Technostress on End-User Satisfaction and Performance
Conceptualizing AI literacy
Leader autonomy support in the workplace
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Job demands–resources theory
When to use and how to report the results of PLS-SEM
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
PLS-SEM or CB-SEM
Common Method Bias in PLS-SEM
Technological Pedagogical Content Knowledge
Distributed Leadership as a Catalyst for Change
Teacher burnout
Towards Intelligent-TPACK
A comparative study of expert, AI, and no external feedback on mathematics teacher learning outcomes in reflective practice
Measuring user competence in using artificial intelligence
Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being
From digital disruption to mental health
Teacher Self-Efficacy and Perceived Autonomy
Systematic review of research on artificial intelligence applications in higher education – where are the educators
Shared goals and values in the teaching profession, job satisfaction and motivation to leave the teaching profession
Examining Teaching Competencies and Challenges While Integrating Artificial Intelligence in Higher Education
Teaching quality as a dynamic system
AI Literacy in Teacher Education
| Citation velocity | historical |
|---|---|
| Highly cited | No |