An Ecological Model of Technology-Enhanced Teaching Competence Development: Multi-Dimensional Insights from Exemplary University English Teachers in Blended Teaching Contexts

The digital transformation has intensified demands for university teachers to develop technology-enhanced teaching competence, especially under China’s High-Quality Course initiative for blended learning excellence. While existing well-recognized frameworks (e.g., TPACK, DigCompEdu) provide valuable foundational guidance, they inadequately capture the dynamic, ecological processes through which teachers systematically reconstruct curricula and professional identities in blended contexts. This study addresses this gap by proposing an ecological model of competence development, building on the strengths of existing frameworks while capturing the dynamic interplay between teachers, technology, and blended environments. Using a qualitative multiple-case design, we conducted semi-structured interviews with six national recognized exemplary university English teachers. Data were analyzed via Braun & Clarke’s six-phase thematic analysis in MaxQDA. Findings reveal that technology-enhanced teaching competence comprises five co-evolving dimensions: Curriculum Empowerment (systematic course redesign), Role Transformation (shifting from lecturer to learning designer), Environment Integration (orchestrating online-offline spaces), Technology Application (selective tool use), and Competence Spanning (transferring expertise across contexts). These dimensions form an ecological system: when teachers redesign curricula, they simultaneously rethink their professional identities; when they adopt technologies, they reshape classroom environments; and when all four dimensions align, higher-order spanning competence emerges naturally. Theoretically, this ecological model advances beyond technology addition by illuminating relational mechanisms and emergent properties of competence. Practically, it informs a shift from fragmented tool-training to systemic faculty support architectures that honor the complexity of blended teaching transformation.