Objective:

To examine the association between future orientation and motivated learning through AI self-efficacy and intrinsic motivation among university students in China.

Approach:

• Study Design: A cross-sectional, face-to-face survey was conducted with 431 university students in Hubei Province, China.
• Data Analysis: Hayes' PROCESS macro Model 6 with 5,000 bias-corrected bootstrap samples was used to test the indirect pathways.

Key Findings:

• Future orientation was positively associated with motivated learning (β = .549).
• The total indirect effect through AI self-efficacy and intrinsic motivation was significant (effect = .196, 95% CI [.129, .274]).
• AI self-efficacy and intrinsic motivation accounted for indirect associations between future orientation and motivated learning.

Interpretation:

Limitations:

• The study's cross-sectional design limits causal inferences.
• The sample was limited to one university in Hubei Province, which may affect generalizability.

Conclusion:

The study provides preliminary evidence linking future orientation with motivated learning through AI self-efficacy and intrinsic motivation.