Creative thinking is thought to be supported by both spontaneous associative and controlled executive processes. Recently, a new measure of associative cognition has been developed—forward flow—which uses computational semantic models (e.g., latent semantic analysis; LSA) to capture “how far” people travel in semantic space during a chained free association task. The present research aims to extend the psychometrics of forward flow by 1) leveraging multiple computational semantic models for forward flow computation (reliability) and 2) testing how this metric of associative ability relates to divergent creative thinking (validity). In addition, using structural equation modeling, we test dual-process theories of creative cognition by examining the relative contribution of associative and executive abilities to divergent thinking. Study 1 (n = 151) finds moderately improved reliability of forward flow using the new multi-model approach (compared to LSA only), as well as positive effects of both forward flow (β = .48) and general intelligence (β = .36) on divergent thinking (human creativity ratings) in the same structural regression model. This pattern of results was replicated in Study 2 (n = 150), which showed large effects of forward flow (β = .42) and general intelligence (β = .46) on divergent thinking. The results expand the psychometrics of forward flow and provide new evidence for dual process models of creative cognition.

创造性思维被认为受到自发联想和受控执行过程的支持。最近，已经开发了一种新的联想认知度量——前向流——它使用计算语义模型（例如，潜在语义分析；LSA）来捕捉人们在链式自由联想任务期间在语义空间中移动的“多远”。本研究旨在通过 1）利用多个计算语义模型进行前向流计算（可靠性）和 2）测试这种联想能力指标与发散创造性思维（有效性）的关系，从而扩展前向流的心理测量学。此外，使用结构方程模型，我们通过检查联想和执行能力对发散思维的相对贡献来测试创造性认知的双过程理论。研究 1 (n  = 151) 发现使用新的多模型方法（仅与 LSA 相比）前向流的可靠性有所提高，以及前向流 (β = .48) 和通用智能 (β = .36) 对同一结构回归模型中的发散思维（人类创造力评级）。这种结果模式在研究 2 ( n  = 150) 中得到复制，研究表明前向流动 (β = .42) 和一般智力 (β = .46) 对发散思维有很大影响。结果扩展了前向流动的心理测量学，并为创造性认知的双重过程模型提供了新的证据。