Teacher Readiness and Student Perception Toward AI and ICT-Based Learning Environments: A Case Study of Digital Pedagogy Adoption

The accelerated integration of artificial intelligence (AI) and information and communication technologies (ICT) in education has shifted scholarly attention toward understanding how teacher readiness and student perception jointly determine the success of digital pedagogy adoption, particularly in resource-diverse contexts. Teacher readiness defined by technological self-efficacy, pedagogical competence, institutional support, and ethical awareness has been consistently shown to act as the critical foundation for classroom innovation, as studies highlight that without adequately prepared teachers, ICT and AI tools often remain underutilized or misaligned with pedagogy (Ng et al., 2023; Yue et al., 2024). Student perception, meanwhile, strongly influences the degree of engagement, trust, and long-term acceptance of AI/ICT-enabled learning; research demonstrates that students’ judgments of usefulness, fairness, and ethical transparency rise sharply when teachers display confidence, clear guidance, and contextualized use of digital tools (Kim et al., 2025; Sanusi et al., 2024). Systematic reviews (Garzón et al., 2025) emphasize that the relationship between readiness and perception is not linear but mediated by institutional infrastructure, professional development opportunities, and ethical frameworks addressing privacy and bias. Case-based and experimental studies, including AI-supported flipped classrooms (Yavuz et al., 2025), further show that positive student outcomes are contingent on high teacher preparedness and scaffolded design. However, limitations persist in the form of cross-sectional methodologies, self-report biases, and insufficient attention to under-resourced educational settings, raising concerns about external validity (Filiz et al., 2025). This study contributes to this growing discourse by adopting a case-study approach to explore how teacher readiness shapes, and is in turn reinforced by, student perception in AI/ICT-based environments, offering insights that inform policy, professional development, and sustainable models of digital pedagogy adoption in diverse educational contexts.