This study aimed to develop and validate a novel Technology Acceptance Model (TAM)-based instrument and empirically test a framework integrating core TAM constructs (Perceived Usefulness, Perceived Ease of Use, Attitude, Behavioral Intention to Use, and Actual System Use) with external variables—Online Content Management (OCM), Infrastructure Accessibility (IA), and Technology-Enhanced Teaching and Learning (TETL)—to explain technology acceptance among EFL lecturers in Iranian higher education. A rigorous process of construct definition, item development, and validation was employed, with a pilot study (10% of the sample) confirming strong reliability (Cronbach's alpha > 0.8) and content validity through expert review. Data from 477 EFL lecturers were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS and SPSS. Findings revealed that OCM, IA, TETL, PU, PEU, and BIU emerged as significant direct or indirect predictors of technology acceptance. Notably, lecturers' lived experiences during the COVID-19 pandemic profoundly shaped their attitudes, while hypothesized moderating effects of gender and teaching experience were not supported, suggesting unique contextual dynamics. The study offers actionable implications for policymakers (to prioritize IA infrastructure), university administrators (to implement effective OCM platforms), and teacher trainers (to provide targeted TETL professional development), ultimately providing a validated framework to enhance technology integration in Iranian higher education and comparable global contexts navigating post-pandemic digital transformation.
