Data on Behavioural Intention to Use AI Copilot Through TAM and AI Ecological Policy Lens
Description
The data evaluates the factors influencing the adoption of AI Copilot among faculty and students at Cebu Technological University. It operates under the hypothesis that perceived usefulness and perceived ease of use of TAM alongside with the pedagogical dimension of AI Ecological Education Policy Framework(AIEEPF), impact behavioral intentions toward AI Copilot usage. The study utilized a quantitative approach through structured surveys targeted at students and instructors. A stratified random sampling method ensured representation across different educational levels and roles. The participants were informed about the study's purpose and confidentiality rights, providing written consent before responding. Surveys were distributed via university email, yielding 414 responses. After excluding 18 low-variability responses, the data were analyzed using Structural Equation Modeling (SEM), including means and correlation analyses. Findings suggest that respondents scored perceived usefulness at approximately 3.87, and perceived ease of use at 3.71, indicating general agreement on the tool's value and usability for academic tasks. A notable relationship was found between the pedagogical dimension and perceived usefulness, with a path coefficient of 0.446, confirming that well-aligned AI tools are more beneficial. High agreement levels emerged concerning the integration of AI in assessments(mean=3.89), the development of holistic competencies(mean=4.09), and the preparation of an AI-driven workforce(mean=4.02), reflecting strong support for AI-enhanced educational practices. The data suggests favorable perceptions of AI Copilot among students, highlighting the importance of aligning AI technologies with educational goals. It indicates that institutions should integrate AI tools into curricula, invest in ongoing professional development for faculty, customize AI applications for specific educational settings, and address ethical implications, such as bias and transparency. This data serves as a resource for understanding user perceptions and behavioral intentions regarding AI in education. Educational leaders can leverage these insights to inform AI integration strategies, ensuring they align with pedagogical and ethical needs. The study advocates for further research on the longitudinal effects of AI adoption, facilitating effective implementations that enhance learning outcomes and prepare students for future challenges in an AI-driven environment.