Influences of source–item contingency and schematic knowledge on source monitoring: Tests of the probability-matching account

Abstract

The authors investigated conditions under which judgments in source-monitoring tasks are influenced by prior schematic knowledge. According to a probability-matching account of source guessing (Spaniol & Bayen, 2002), when people do not remember the source of information, they match source guessing probabilities to the perceived contingency between sources and item types. When they do not have a representation of a contingency, they base their guesses on prior schematic knowledge. The authors provide support for this account in two experiments with sources presenting information that was expected for one source and somewhat unexpected for another. Schema-relevant information about the sources was provided at the time of encoding. When contingency perception was impeded by dividing attention, participants showed schema-based guessing (Experiment 1). Manipulating source - item contingency also affected guessing (Experiment 2). When this contingency was schema-inconsistent, it superseded schema-based expectations and led to schema-inconsistent guessing.

Hierarchical modeling of contingency-based source monitoring: A test of the probability-matching account

“…Participants who received the information after encoding showed schema-consistent bias in their source attributions, whereas participants who had already received the information before encoding showed no such bias. However, Bayen and Kuhlmann (2011) found that source guessing in this schema-before-encoding condition was only unbiased in a full-attention condition (in contrast to a divided-attention condition) at encoding. With divided attention at encoding, schema bias occurred.…”

“…Therefore, we should find a positive relationship between participants' perceived contingencies and the source-guessing parameter g. Bayen and Kuhlmann (2011) only demonstrated this relationship at a group level. However, within the same experimental setting, individual variations in source-guessing bias are possible (cf.…”

“…Probability matching has been observed in source monitoring (e.g., Bayen & Kuhlmann, 2011;Erdfelder & Bredenkamp, 1998) and in other tasks, such as oldnew recognition (e.g., Buchner, Erdfelder, & VaterrodtPlünnecke, 1995;Ehrenberg & Klauer, 2005) and human choice behavior (e.g., Estes & Straughan, 1954). Furthermore, studies have shown that prior knowledge influences source guessing (Bayen, Nakamura, Dupuis, & Yang, 2000;Ehrenberg & Klauer, 2005;Spaniol & Bayen, 2002).…”

“…We used a new methodological approach, beta-MPT modeling (Smith & Batchelder, 2010), which allowed us to estimate individual participants' source-guessing probabilities. Bayen and Kuhlmann (2011;see also Bayen et al, 2000) used a multinomial processing tree (MPT) model, the two-high-threshold model of source monitoring (2HTSM; Bayen, Murnane, & Erdfelder, 1996), to disentangle memory and guessing in the sourcemonitoring paradigm. First we will describe the 2HTSM, then the basics of the beta-MPT approach.…”

“…We used Submodel 4 (see Bayen et al, 1996, for details), which assumes that the levels of item memory as well as source memory are equal for both sources, and which had fit the data from previous studies using the same standard source-monitoring paradigm we used in the present study (Bayen & Kuhlmann, 2011;Bayen et al, 2000;Kuhlmann, Vaterrodt, & Bayen, 2012). The model (see Fig.…”