Replication Data for: Student Acceptance of AIGC for Sustainable Personalized Learning: A Mixed-Methods Study in Chinese Higher Education

本数据集包含一项混合方法研究的完整复现材料,该研究旨在调查中国高等教育中学生对人工智能生成内容(AIGC)的接受度。该数据集包括: Anonymized Raw Dataset (N=928): A comprehensive CSV file containing item-level Likert scale responses for all UTAUT constructs and educational sustainability indicators, alongside binary-coded SWOT variables and demographic profiles. Open-Source Replication Script (R): A functional R-script utilizing the lavaan and psych packages. This provides a transparent computational pathway to replicate the study’s reliability coefficients and structural path estimates using the provided raw data. AMOS Statistical Output Report: The original analytical results generated from IBM SPSS AMOS 24.0, providing the primary documentation for model fit indices, standardized path coefficients, and bootstrapping results as reported in the manuscript. Qualitative Coding Framework: A detailed coding scheme derived from 18 semi-structured interviews. This document captures the thematic transition from verbatim student narratives to the conceptual themes and socio-technical paradoxes discussed in the findings.