A Study of Chinese Undergraduate Intentions to Purchase AIGT Educational Products: An Empirical Analysis Based on a Multi-Theoretical Model

Aim/Purpose: This study aims to investigate the decision-making mechanisms underlying Chinese undergraduate students’ purchase intentions toward artificial intelligence generation tools (AIGT) educational products by integrating three theoretical frameworks: the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM), and the Value-based Adoption Model (VAM). Background: With the popularization of AIGT in the education field, its acceptance and demand are becoming increasingly prominent. While AIGT demonstrates substantial potential in enhancing pedagogical outcomes and personalizing learning experiences, its market penetration, particularly in adoption rates among university student populations, remains contingent upon multifactorial determinants, which are of interest to our community of practice. Methodology: This study integrates the TPB, the TAM, and the VAM to construct a theoretical framework for the purchase intention of AIGT education products. Thereafter, an online survey was conducted among 523 undergraduate students from different regions of China, and a structural equation model was used to analyze the obtained data. Contribution: This study bridges theoretical gaps by integrating TPB, TAM, and VAM into a novel framework, offering a holistic understanding of the adoption of AIGT educational products and providing empirical evidence for understanding the purchase intention of undergraduates towards AIGT educational products. Findings: The results show that while brand perception has no direct significant impact on purchase intention, the rest of the investigated factors all have significant impacts on purchase intention to varying degrees, and there are also strong correlations among the investigated factors. Among them, the perceived fee was the most critical factor with a significant negative impact. However, perceived usefulness could increase consumers’ threshold regarding perceived fee, exerting a significant positive impact on it. Brand perception did not directly affect perceived value; it influenced the latter indirectly via the mediating variable of enjoyment. Recommendations for Practitioners: Educational technology firms should prioritize enhancing product functionality and adopt tiered pricing strategies, while universities should integrate AIGT into curricula and foster industry partnerships to align products with pedagogical needs. Recommendation for Researchers: Future studies should expand sampling to diverse populations, incorporate cultural or policy variables, and employ mixed-method methodologies to deepen insights into AIGT adoption dynamics. Impact on Society: AIGT adoption could democratize access to personalized education and bridge learning gaps, but equitable pricing and ethical AI deployment are critical to prevent socioeconomic disparities. Future Research: Validate the framework in cross-cultural contexts, investigate AI ethics and cultural adaptability, and assess long-term educational outcomes of AIGT integration through longitudinal studies.