Motivated to retrieve: How often are you willing to go back to the well when the well is dry?

Abstract

Despite the necessity of the decision to terminate memory search in many real-world memory tasks, little experimental work has investigated the underlying processes. In this study, the authors investigated termination decisions in free recall by providing participants an open-ended retrieval interval and requiring them to press a stop button when they had finished retrieving. Three variables important to assessing one's willingness to search memory were examined: (a) the time spent searching memory after the last successful retrieval before choosing to quit (the exit latency); (b) task difficulty; and (c) individual differences in motivation, as measured by Webster and Kruglanski's (1994) Need for Closure Scale. A strong negative correlation was found between individual differences in motivation and participants' exit latencies. This negative correlation was present only when the retrieval task started out as relatively difficult.Keywords: recall, memory retrieval, exit latency, stopping rules A fundamental component of memory retrieval is the decision to terminate search. This decision process characterizes many realworld memory retrieval tasks, from the generation of clinical diagnoses by physicians to the recollection of items from a grocery list left at home. Despite the necessity of the decision to terminate memory search in virtually all real-world tasks, little experimental work has investigated the underlying processes.Related to the issue of search termination is the question of what psychological factors affect one's willingness to continue to search memory. Some factors are anticipated by models of memory, such as the use of familiarity in paired-associate retrieval (Diller, Nobel, & Shiffrin, 2001) or feelings of knowing when searching for a question's answer (Barnes, Nelson, Dunlosky, Mazzoni, & Narens, 1999;Costermans, Lories, & Ansay, 1992;Nelson, Gerler, & Narens, 1984;Young, 2004). However, other variables likely are important, too. For example, you presumably would search memory longer for a relatively important task, such as retrieving your grandmother's medications upon admitting her for emergency care. In contrast, search might be truncated relatively quickly for a comparatively unimportant task, such as recollecting movies you recently watched to provide a recommendation for a friend. Variables such as the importance of the retrieval task and idiographic levels of motivation likely serve as important moderators in the process of determining the amount of time one is willing to search memory.In this article, we ask how long people will continue going back to the well (i.e., memory) when the well is dry (i.e., when retrieval has been unsuccessful). In addressing this question, we examined three variables important to assessing one's willingness to search memory: (a) the time spent searching memory after the last successful retrieval before choosing to quit; (b) task difficulty; and (c) individual differences in motivation, as measured by Webster and Kruglanski's (1994) Need for Closure (NFC) ...

The central executive as a search process: Priming exploration and exploitation across domains.

“…As shown in Figure 8, participants left the current letter set approximately 15 seconds on average after submission of the 7 th word, but took on average 34 seconds to leave the letter set after submission of the 1 st word. This pattern of decreasing latency with more submissions has been observed in other tasks involving serial search for items in memory (Dougherty & Harbison, 2007) and is consistent with the hypothesis that participants recognize they are in a depleting resource pool (see Iwasa, Higashi, & Yanamura, 1981). We capture this effect in CESP by making the probability of the letter set switch update be inversely proportional to a threshold parameter β that shrinks with each additional word submission according to the following equation: $$\beta =\kappa {\lambda }^{\mathrm{italicwordcount}}$$ To determine the appropriate values for the constants that specify β , we fit the above to the data for both conditions from Experiment 1 using the quasi-Newton method of Broyden, Fletcher, Goldfarb and Shanno (described in Nash, 1990), fitting both λ (0.86) and the scaling parameter κ (37.1).…”

Recall termination in free recall

“…In the present study, we define recall termination as occurring when the time between the last recalled item and the end of the fixed recall period was both longer than every interresponse time on the current trial and exceeded a criterion of 12 s. This value was chosen to exceed the mean exit latency of 10 s reported by Dougherty and Harbison (2007) in an open-ended retrieval period. Out of 28,015 trials, 18,829 met these criteria (67.21%).…”

“…Whereas Murdock and Okada inferred recall termination based on the final correct response given in a fixed recall period, a more recent study by Dougherty and Harbison (2007) assessed recall termination by asking participants to press a key when they could not remember any additional items. Dougherty and Harbison found that the duration between the last successful retrieval and the termination response (exit latency) decreased as the total number of items recalled increased.…”

Foraging across the life span: is there a reduction in exploration with aging?

“…In the results below, we go beyond the original analyses by Mata et al (2009) by analyzing individuals' giving-up times, that is, the time between the last resource found in a patch and the decision to leave the patch and explore a new one (see Figure 1). Giving-up times have been suggested to be reliable measures of exploratory tendencies (Dougherty and Harbison, 2007; Harbison et al, 2009) but to our knowledge there have been no investigations of age differences in giving-up times. Furthermore, we present data from two unpublished experiments on search in memory, which used an analogous design to the one in Mata et al (2009) but asked younger and older adults to search for word solutions in memory.…”

“…The adaptive hypothesis of age-related reductions in novelty seeking and exploration emphasizes the role of opportunity costs. Consequently, motivational variables such as future time perspective (Lang and Carstensen, 2002; Carstensen, 2006) and maximizing (Dougherty and Harbison, 2007) may index the subjective value of exploration and thus be linked to giving-up times. In contrast, the cognitive decline hypothesis of age-related reductions in novelty seeking and exploration suggests that age-related cognitive decline is the main factor underlying reductions in exploratory behavior, and thus could be related to measures of fluid cognitive ability (Duzel et al, 2010).…”