Artificial　Intelligence　(AI)　technologies　have　rapidly　transformed　the　education　sector　and　affect　student　learning　performance,　particularly　in　China,　a　burgeoning　educational　landscape.　The　development　of　generative　artificial　intelligence　(AI)　based　technologies,　such　as　chatbots　and　large　language　models　(LLMs)　like　ChatGPT,　has　completely　changed　the　educational　environment　by　providing　individualized　and　engaging　programs.　This　study　brings　forward　a　model　and　hypothesis　based　on　social　cognitive　theory　and　appropriate　research.　This　investigation　centers　on　how　generative　AI-based　technologies　influence　students＇　learning　performance　in　higher　education　(HE)　institutions　and　the　function　of　self-efficacy,　fairness　&　ethics,　creativity,　and　trust　in　promoting　these　connections.　Data　is　collected　from　362　students　at　Chinese　universities　using　purposive　sampling.　The　proposed　structural　model　was　evaluated　using　partial　least　squares-structural　equation　modeling　(PLS-SEM).　The　findings　reveal　that　generative　AI　technologies　such　as　LLM　models　exemplified　by　ChatGPT　and　chatbots　significantly　influence　students＇　learning　performance　through　self-efficacy,　fairness　&　ethics,　and　creativity.　Furthermore,　trust　significantly　moderates　the　relationship　between　fairness　&　ethics,　creativity,　and　learning　performance　but　negatively　moderates　the　relationship　between　self-efficacy　and　learning　performance.　This　study　supports　the　new　explanatory　potential　of　social　cognitive　theory　in　technological　practices.　Additionally,　this　research　suggests　using　generative　AI　technologies　to　enhance　students＇　digital　learning　and　boost　academic　achievement.