Advancements in smart, mobile, and wearable technologies are redefining how individuals interact and compute, leading to the emergence of smart learning environments (SLEs) that support personalized and inclusive educational experiences. While several evaluation frameworks exist for learning environments, few adequately address the unique characteristics of smart learning contexts. This study proposes and validates an integrated evaluation model specifically tailored for SLEs, drawing on the strengths and addressing the limitations of the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). The validation process involved focused group discussions comprising students, lecturers from the Faculty of Science, and e-learning experts at Adamawa State University, Mubi, Nigeria. Data were analyzed thematically to uncover contextual factors influencing the acceptance and use of smart learning technologies. The findings revealed three additional constructs—perceived quality, perceived support, and perceived technology resources—which enhance the explanatory power of the combined TAM-TPB framework in smart learning environments. The integrated model offers a comprehensive lens for examining both the intention and actual usage of smart learning systems. It serves as a practical tool for educational institutions, policymakers, and technology developers to guide the design, implementation, and evaluation of inclusive smart learning strategies. By contextualizing technology acceptance within the dynamics of resource availability and support systems, the model ensures relevance and applicability in real-world educational settings.