Teachers Behavior in the AI Assessment Tools Adoption in Morocco: A Diffusion of Innovation and Technology Using PLS-SEM

Abstract

Artificial Intelligence (AI) is increasingly shaping educational practices and assessment systems worldwide. However, the mechanisms through which AI-based assessment tools diffuse among teachers remain insufficiently understood, particularly in developing-country contexts. Drawing on both the Technology Acceptance Model (TAM) and the Diffusion of Innovation perspective, this study examines the factors influencing teachers’ adoption of AI tools for Life and Earth Sciences (LES) assessment in Moroccan public secondary schools. In this framework, diffusion is operationalized through teachers’ exposure to AI tools, training and digital literacy, and perceived institutional and pedagogical constraints that shape the spread of AI-supported assessment practices. A quantitative survey was conducted among secondary school teachers in the Rabat-Sale-Kenitra region of Morocco. The proposed conceptual model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The measurement model demonstrated acceptable internal consistency and construct reliability, while the structural model exhibited substantial explanatory power for the key endogenous constructs. The findings indicate that teachers’ attitudes toward AI play a central mediating role in the adoption process. Attitude is primarily influenced by the perceived impact of AI on learning outcomes, followed by perceived usefulness and perceived ease of use. Consistent with TAM assumptions, attitude significantly influences behavioral intention, which in turn emerges as the strongest predictor of actual AI use in assessment practices. Despite generally favorable perceptions of AI, the results reveal a substantial intention-use gap, as most teachers report rarely or never using AI tools in classroom assessment. Overall, the study contributes to the literature on AI adoption in education by integrating diffusion-related factors with technology acceptance mechanisms in a developing-country context. The findings highlight the importance of teacher training, digital competence development, and supportive institutional environments for facilitating the sustainable diffusion of AI-supported assessment practices.