Implicit statistical learning, whereby predictable relationships between stimuli are detected without conscious awareness, is important for language acquisition. Although a defining feature of implicit learning is that we are unaware that learning has occurred, implicit statistical learning is often assessed using measures that require explicit reflection (e.g., judgements about the grammaticality of a sequence of stimuli). However, implicit statistical learning can also be assessed without requiring conscious reflection, using ‘processing-based’ tasks, that instead measure other variables that are facilitated by implicit statistical learning, such as serial recall. Across a number of experiments, we developed and tested a novel serial visual recall task, based on the premise that frequently co-occurring stimuli may be “chunked” into a single cognitive unit, reducing working memory demands and facilitating recall. With both adults and children, we demonstrated that when participants were asked to remember and recreate sequences of serially presented images, they showed improved recall for grammatical sequences, which can be chunked, over ungrammatical sequences that cannot. These experiments demonstrate that serial recall tasks are a valuable approach to measure implicit statistical learning, without reliance on conscious decision making or explicit processing.

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