Key points are not available for this paper at this time.
Introduction: Against the backdrop of educational digitalization and the urgent need for the "data-intelligence" transformation of Financial Management programs, this study investigates the mechanisms through which digitalization policies affect teaching and learning behaviors. To overcome the limitations of previous research, which often focused solely on either the teacher or student perspective, this study innovatively develops a "Teacher-Student Dual-Path Model." Methods: Adopting a non-matched independent sampling design, we collected survey data from 253 faculty members and 280 students across a diverse range of Chinese higher education institutions. The hypothesized paths and mediating effects were empirically tested using Structural Equation Modeling (SEM). Results: The findings reveal a striking asymmetrical mechanism. For teachers, the path follows a "Psychological Empowerment" logic: institutional policy support is ineffective unless it is internalized to significantly enhance teachers' "digital teaching self-efficacy," which in turn drives teaching innovation behaviors. For students, the path is governed by a "Value Rationality" logic: a high-quality digital learning environment promotes deep learning primarily through students' cognitive evaluation of the "perceived usefulness" of digital tools. Furthermore, heterogeneity analysis reveals a marginally significant moderating trend of teaching experience in the policy "support-efficacy" relationship. Discussion: The digital transformation of financial management education is fundamentally a profound psychological and cognitive undertaking. It is characterized by the core mechanism of being "Confidence-Driven" for teachers and "Value-Driven" for students. These findings provide a theoretical and practical basis for shifting the educational digitalization ecosystem from a "technology-centric" to a "human-centered" paradigm.
Zhang et al. (Mon,) studied this question.