Change detection tasks are commonly used to measure and understand the nature of visual working memory capacity. Across two experiments, we examine whether the nature of the latent memory signals used to perform change detection are continuous or all-or-none, and consider the implications for proper measurement of performance. In Experiment 1, we find evidence from confidence reports that visual working memory is continuous in strength, with strong support for equal variance signal detection models. We then tested a critical implication of this result without relying on model comparison or confidence reports in Experiment 2 by asking whether a simple instruction change would improve performance when measured with K, an all-or-none-measure, compared to d’, a measure based on continuous strength signals. We found strong evidence that K values increased by roughly 30% despite no change in the underlying memory signals. By contrast, we found that d’ is fixed across these same instructions, demonstrating that it correctly separates response criterion from memory performance. Overall, our data call into question a large body of work using threshold measures, like K, to analyze change detection data since this metric confounds response bias with memory performance in standard change detection tasks.