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Technological capability may support learning without translating directly into academic value. This study examined how digital literacy (DL), generative artificial intelligence literacy (GenAIL), and creative thinking disposition (CTD) were differentially associated with perceived academic performance (PAP) among 258 pre-service Visual Arts teachers in Ghana. Cross-sectional survey data were analysed using partial least squares structural equation modelling (PLS-SEM), importance-performance map analysis (IPMA), and necessary condition analysis (NCA). DL was positively associated with GenAIL (β = 0.682), CTD (β = 0.350), and PAP (β = 0.326), while CTD was positively associated with PAP (β = 0.481). GenAIL showed no significant direct association with PAP (β = 0.001, p = .986), but it was indirectly associated with PAP through CTD (β = 0.235). GenAIL also modestly attenuated the positive DL–PAP association (β = −0.076, ΔR² = 0.010). The model explained 66.2% of the variance in PAP. Out-of-sample evidence was mixed: Q²predict values were positive, but only one of four PAP indicators had lower RMSE than the linear-model benchmark. IPMA identified DL as the construct with the highest model-based importance but comparatively lower performance, whereas CTD combined high importance with high performance. NCA identified sample-specific ceiling patterns consistent with necessary-but-insufficient conditions for DL, CTD, and GenAIL. The findings support a capability–enactment interpretation in which technological capabilities perform different academic functions. Teacher education should therefore strengthen foundational digital literacy, sustain creative dispositions, and develop GenAI literacy as a complementary capability embedded in critical, ethical, and creative disciplinary engagement.
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Setsoafia et al. (2026) studied this question.
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