Manuscript ID: systems-4184449

This dataset contains the survey data used in the study examining the development of systems thinking in generative artificial intelligence (GenAI)–supported logistics management education. The data were collected from undergraduate students majoring in logistics management and related disciplines at Chinese universities in 2026.The dataset includes responses to validated multi-item Likert-scale instruments measuring the following constructs: Self-Regulated Learning (SRL; including planning, monitoring, and reflection dimensions), Teacher GenAI Scaffolding (TAS), Germane Cognitive Load (GCL), Extraneous Cognitive Load (ECL), and Systems Thinking (ST). All items were measured on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).The final valid sample consists of 236 observations after data screening and cleaning. The dataset was used to conduct Partial Least Squares Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to explore both linear and configurational pathways underlying the formation of systems thinking in AI-supported learning environments.No personally identifiable information is included in the dataset. All responses were collected anonymously and processed in accordance with ethical research standards.