Digital Education Ecosystem and Faculty Digital Competence: The Mediating Role of Professional Learning Communities

Dataset Title Digital Education Ecosystem, Professional Learning Community, and Faculty Digital Competence in Vietnamese Teacher Education Institutions Dataset Overview This repository contains the dataset supporting the study entitled: Digital Education Ecosystem and Faculty Digital Competence: The Mediating Role of Professional Learning Communities The dataset was developed to examine how institutional digital ecosystem conditions contribute to faculty digital competence through collaborative professional learning processes within teacher education institutions in Vietnam. The repository includes raw survey data, analytical datasets, codebook documentation, questionnaire instruments, and supplementary materials required for replication and secondary analysis. Research Context Digital transformation has become a strategic priority for higher education institutions worldwide. Within teacher education institutions, digital transformation carries additional importance because faculty members influence both university teaching practices and the preparation of future teachers. This dataset investigates three interrelated constructs: Digital Education Ecosystem (DEE) Professional Learning Community (PLC) Faculty Digital Competence (FDC) The study examines how organizational ecosystem conditions influence competence development directly and indirectly through collaborative professional learning processes. Data Collection Data were collected between January and May 2026 from faculty members employed at three teacher education universities in Vietnam. Data collection was conducted using an online questionnaire adapted from previously validated instruments in the fields of: Digital transformation Educational leadership Professional learning communities Teacher digital competence Participation was voluntary and anonymous. Following data screening and quality checks, the final dataset consisted of 629 valid responses. Sample Characteristics The dataset includes faculty members representing multiple teacher education disciplines. Demographic variables include: Gender Age group Teaching experience Teaching discipline Participants were drawn from: Educational Sciences Mathematics and Natural Sciences Education Social Sciences Education Languages Education Information Technology and Technology Education Arts and Physical Education Measurement Framework Digital Education Ecosystem (DEE) Higher-order construct consisting of five dimensions: Digital Infrastructure Readiness (DIR) Strategic Digital Leadership (SDL) Digital Innovation Culture (DIC) Digital Governance Support (DGS) Digital Capacity Development Support (DCD) Number of indicators: 28 Professional Learning Community (PLC) Higher-order construct consisting of five dimensions: Shared Professional Vision (SPV) Collaborative Professional Learning (CPL) Reflective Pedagogical Dialogue (RPD) Digital Knowledge Sharing (DKS) Collective Improvement Focus (CIF) Number of indicators: 23 Faculty Digital Competence (FDC) Single-dimensional reflective construct measuring faculty members’ capability to use digital technologies for teaching, assessment, communication, content creation, and responsible professional practice. Number of indicators: 6 Total survey items: 57 Response Format All measurement items were assessed using a seven-point Likert scale: 1 = Strongly Disagree 2 = Disagree 3 = Slightly Disagree 4 = Neutral 5 = Slightly Agree 6 = Agree 7 = Strongly Agree Higher values indicate stronger agreement with the corresponding statement. Repository Contents This repository contains: Raw Data Original survey responses Analytical Dataset Cleaned dataset used for statistical analyses Codebook Variable descriptions Item mappings Construct structure Coding information Questionnaire Participant information sheet Informed consent form Survey instrument Supplementary Documentation Measurement structure Construct definitions Analytical notes Analytical Approach The study employed Partial Least Squares Structural Equation Modeling (PLS-SEM). Analyses included: Measurement model assessment Higher-order construct assessment Structural model evaluation Mediation analysis Predictive relevance assessment PLSpredict evaluation The dataset is suitable for replication studies, methodological research, and alternative model testing. Potential Reuse The dataset may support future research related to: Digital transformation in higher education Teacher education Faculty development Educational leadership Professional learning communities Educational technology Artificial intelligence in education Digital competence Structural equation modeling Ethical Approval Ethical review and approval were provided in accordance with institutional research governance procedures of Vietnam National University, Hanoi, under Decision No. 3073/QĐ-ĐHQGHN dated 28 June 2024. Funding This research was supported by Vietnam National University, Hanoi under the Science and Technology Project: Project Code: QG.24.87 Conflict of Interest Statement The authors declare that there are no known financial, professional, or personal relationships that could be construed as potential conflicts of interest influencing the conduct, analysis, or interpretation of this research. Citation Users of this dataset are requested to cite both the dataset DOI and the associated publication when using the data in academic publications, reports, or derivative research.