Memory seeding: representations underlying quantitative estimations

N. R. Brown and R. S. Siegler (1996) found that training participants on a subset of country populations improved estimations for novel transfer country populations, an effect called seeding that remained intact over time. They attributed this effect to the abstraction by participants of a general metric framework for estimating populations not dependent on specific country anchors. In a series of 3 follow-up experiments, the authors found that training on seed populations produces both general metric information and durable specific country information. Moreover, minimal amounts of general (mean or range of populations) or specific (1 or 3 countries) information made available for inspection while estimating produced a significant seeding effect. Retention over long intervals was facilitated by both presenting 3 seed countries as opposed to 1 and providing names for the seed countries.