Fischer Helen, Holt Daniel V
Department of Psychology, Heidelberg University, Hauptstr. 47-51, 69117, Heidelberg, Germany.
Mem Cognit. 2017 Apr;45(3):404-412. doi: 10.3758/s13421-016-0665-0.
Predicting the development of dynamic processes is vital in many areas of life. Previous findings are inconclusive as to whether higher working memory capacity (WMC) is always associated with using more accurate prediction strategies, or whether higher WMC can also be associated with using overly complex strategies that do not improve accuracy. In this study, participants predicted a range of systematically varied nonlinear processes based on exponential functions where prediction accuracy could or could not be enhanced using well-calibrated rules. Results indicate that higher WMC participants seem to rely more on well-calibrated strategies, leading to more accurate predictions for processes with highly nonlinear trajectories in the prediction region. Predictions of lower WMC participants, in contrast, point toward an increased use of simple exemplar-based prediction strategies, which perform just as well as more complex strategies when the prediction region is approximately linear. These results imply that with respect to predicting dynamic processes, working memory capacity limits are not generally a strength or a weakness, but that this depends on the process to be predicted.
预测动态过程的发展在生活的许多领域都至关重要。先前的研究结果对于更高的工作记忆容量（WMC）是否总是与使用更准确的预测策略相关，或者更高的WMC是否也可能与使用不提高准确性的过度复杂策略相关尚无定论。在本研究中，参与者基于指数函数预测一系列系统变化的非线性过程，在这些过程中，预测准确性可以或不可以通过校准良好的规则得到提高。结果表明，WMC较高的参与者似乎更多地依赖校准良好的策略，从而对预测区域中具有高度非线性轨迹的过程做出更准确的预测。相比之下，WMC较低的参与者的预测表明他们更多地使用基于简单范例的预测策略，当预测区域近似线性时，这些策略的表现与更复杂的策略一样好。这些结果意味着，在预测动态过程方面，工作记忆容量限制通常既不是优势也不是劣势，而是取决于要预测的过程。
