A preliminary conceptual framework and descriptive survey of university teacher digital literacy in AI-enhanced higher education

Artificial intelligence, generative AI, learning analytics, and platform-based teaching have reshaped the digital practices expected of university teachers. This study examines general university teacher digital literacy in that changing context; it does not measure, operationalise, or validate AI-specific literacy. A sequential multi-phase design combined a structured integrative review of 68 peer-reviewed articles published between 2018 and 2025, an adapted Delphi consultation with 12 specialists, and a cross-sectional survey of 520 university teachers from 12 Chinese higher education institutions. The study proposes University Teacher Digital Literacy–Six Dimensions (UTDL-6D) as a preliminary conceptual framework comprising technological operational competence, information and data literacy, digital content creation, digital communication and collaboration, innovation consciousness and pedagogical integration, and digital ethics and critical engagement. UTDL-6D is presented as a conceptual and descriptive framework, not as a validated diagnostic instrument: item-level construct-validity evidence (standardised loadings, composite reliability, average variance extracted, and discriminant-validity indices) was not available for this report and is not claimed. Self-reported competence was higher in technological operational competence (M = 3.72, SD = 0.68) and digital communication and collaboration (M = 3.58, SD = 0.72), and lower in innovation consciousness and pedagogical integration (M = 2.65, SD = 0.88) and digital ethics and critical engagement (M = 2.78, SD = 0.85). All 15 inter-dimensional correlations were positive, moderate, and statistically significant, ranging from r = 0.42 to r = 0.62 ( N = 520, p < 0.001). Frequently reported barriers included lack of protected training time (78.3%), rapid technological change (72.5%), insufficient institutional support (68.1%), and misalignment of incentives and rewards (64.2%). Because participants were nested within 12 institutions and clustering could not be modelled, comparisons by academic rank are reported as exploratory. These findings describe perceived general digital competence rather than demonstrated AI competence; a theoretical mapping between the six dimensions and recognised AI-literacy components is offered to guide future instrument development. The Five-Pillar Enhancement Framework is presented as a provisional, hypothesised institutional roadmap that requires independent longitudinal and intervention-based evaluation.