The demonstration of a sequential congruency effect in sequence learning has been offered as evidence for control processes that act to inhibit automatic response tendencies (Jiménez, Lupiáñez, & Vaquero, 2009) via unconscious conflict monitoring. Here we propose an alternative interpretation of this effect based on the associative learning of chains of sequenced contingencies. This account is supported by simulations with a Simple Recurrent Network, an associative (connectionist) model of sequence learning. We argue that the control- and associative-based accounts differ in their predictions concerning the magnitude of the sequential congruency effect across training. These predictions are tested by reanalysing data from a study by Shanks, Wilkinson, and Channon (2003). The results support the associative learning account which explains the sequential congruency effect without appealing to control processes (either conscious or unconscious).