What type of study is this?

This is a Quantitative Study study.

October 23, 2025

Quantitative Analysis of Influencing Factors on AI-Integrated Teaching in Animation Major of Private Colleges and Universities

Key Points

Increased faculty impact on teaching effectiveness was found, influenced by technical infrastructure and student characteristics.
Analysis across five Liaoning private colleges used SEM and Bootstrap methods to assess respondent data from 312 samples.
Findings indicate that higher hardware availability significantly boosts faculty's teaching impact and students' independent learning.
This highlights the need for stronger university-enterprise cooperation to enhance AI teaching outcomes in resource-limited settings.

Abstract

Amid global AI education transformation, Chinese private animation majors have low AI teaching implementation and insufficient quantitative research. This study (5 Liaoning private colleges, 312 samples) used SEM/Bootstrap/group regression based on TAM-UTAUT. Results: Faculty (β=0.42, core), technical infrastructure (β=0.32), student characteristics (β=0.21) positively impact effectiveness; university-enterprise cooperation mediates (32.6%); high hardware raises faculty’s impact (β=0.28→0.51); juniors use independent learning (β=0.32) to alleviate constraints. This fills China’s research gap, providing references for global resource-constrained colleges.

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Cite This Study

Dandan Cong (Sun,) studied this question.

synapsesocial.com/papers/68f9a0eb8ea8f2f37ee94d42 https://doi.org/https://doi.org/10.54097/ry3mef85

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