(untitled) (JMKSP (Jurnal Manajemen, Kepemimpinan, dan Supervisi Pendidikan), 2026)
This research is conducted to comprehensively examine how the application of artificial intelligence together with blended learning contributes to variations in student learning motivation among university students located in Surakarta, utilizing a quantitative methodological framework supported by a correlational survey model that engaged 76 undergraduate participants, with empirical data gathered through a structured five level Likert scale instrument and statistically processed using multiple linear regression techniques supported by SPSS software version 26. The empirical findings demonstrate that artificial intelligence and blended learning significantly enhance student learning motivation when evaluated individually as well as collectively, with artificial intelligence emerging as the factor exerting a stronger statistical contribution to motivational improvement. These findings suggest that the integration of adaptive learning technology and well-planned blended learning can support more flexible and engaging learning environments, thereby enhancing student learning motivation in higher education.