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Information foraging in the unknown patches across the life span.
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This study used a word search puzzle paradigm to examine the effects of task environment and individual differences in ability on information foraging. Younger and older adults attempted to maximize the number of items found in a set of 4 puzzles in which they were at liberty to search within a puzzle or switch between them. Younger adults demonstrated faster uptake (i.e., number of words found as a function of time) from individual puzzles than older adults but experienced more deceleration of rates during the search. Additionally, older adults switched less often and their switching was less dependent on the uptake rate compared to younger adults. Both younger and older adults stayed longer than was optimal in a patch, older adults were especially likely to persevere suboptimally. Collectively, these results suggest that individuals may differentially optimize information gain through self-regulation of exploration and exploitation.
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... Similarly, Mata et al. asked younger and older adults to forage for fish in a sequence of virtual ponds and found that older adults tended to search longer in a given pond compared to younger adults, suggesting that older adults may be less willing to explore new resource patches (Mata et al., 2009). One study investigated age differences in information foraging by asking younger and older adults to find words from word puzzles with the goal of maximizing the total number of words found within a limited time period (Chin et al., 2012). The results suggest that older adults were more likely to stay with a particular puzzle relative to younger adults and that the frequency of switching between puzzles-one possible index of exploration-was negatively related to higher fluid abilities. ...
... One avenue for future work would be to use other tasks that allow the use of alternative dependent measures that are not based on reaction-times to capture exploratory tendencies. Suitable tasks may include information search tasks that use switching between options (Daw et al., 2006), cues (Hills et al., 2013), or problems (Chin et al., 2012) as indicators of exploration. ...
Does foraging change across the life span, and in particular, with aging? We report data from two foraging tasks used to investigate age differences in search in external environments as well as internal search in memory. Overall, the evidence suggests that foraging behavior may undergo significant changes across the life span across internal and external search. In particular, we find evidence of a trend toward reduced exploration with increased age. We discuss these findings in light of theories that postulate a link between aging and reductions in novelty seeking and exploratory behavior.
... However, when introduced to a dynamic decision-making environment which features a strong choice-reward contingency, older adults demonstrate exploratory behavior and a performance enhancement over younger adults. Older adults have also been shown to engage in less exploratory strategies in tasks involving information foraging (Chin et al., 2012;Mata, Wilke, & Czienskowski, 2013). The present study seeks to contribute to the understanding of the role of normal aging in the exploration-exploitation trade-off by utilizing computational modeling of a dynamic decision-making task which involves multiple input sources and a hidden and complex underlying task mechanism, similar to many real-world scenarios. ...
Situations in which there are multiple changes occurring all at once and which demand complex decisions to be made are common throughout life, but little is known about how normal aging influences performance on these types of scenarios. To determine performance differences associated with normal aging, we test older and younger adults in a dynamic control task. The task involves the control of a single output variable over time via multiple and uncertain input controls. The Single Limited Input, Dynamic Exploratory Responses (SLIDER) computational model, is implemented to determine the behavioral characteristics associated with normal aging in a dynamic control task. Model-based analysis demonstrates a unique performance signature profile associated with normal aging. Specifically, older adults exhibit a positivity effect in which they are more influenced by positively valenced feedback, congruent with previous research, as well as enhanced exploratory behavior.
... The material used in this study consisted of a website and did not involve any interaction with a search engine or SERPs. A later study by [8] used word search puzzle paradigm to examine the age differences in the underlying search mechanism showing that older adults did less exploration because they monitored the change of information gain differently than younger adults. ...
This paper looks at two limitations of cognitive models of web-navigation: first, they do not account for the entire process of information search and second, they do not account for the differences in search behavior caused by aging. To address these limitations, data from an experiment in which two types of information search tasks (simple and difficult), presented to both young and old participants was used. We found that in general difficult tasks demand significantly more time, significantly more clicks, significantly more reformulations and are answered significantly less accurately than simple tasks. Older persons inspect the search engine result pages significantly longer, produce significantly fewer reformulations with difficult tasks than younger persons, and are significantly more accurate than younger persons with simple tasks. We next used a cognitive model of web-navigation called CoLiDeS to predict which search engine result a user would choose to click. Old participants were found to click more often only on search engine results with high semantic similarity with the query. Search engine results generated by old participants were of higher semantic similarity value (computed w.r.t the query) than those generated by young participants only in the second cycle. Match between model-predicted clicks and actual user clicks was found to be significantly higher for difficult tasks compared to simple tasks. Potential improvements in enhancing the modeling and its applications are discussed.
We describe the development of a computational cognitive model that explains navigation behavior on the World Wide Web. The model, called SNIF-ACT (Scent-based Navigation and Information Foraging in the ACT cognitive architecture), is motivated by Information Foraging Theory (IFT), which quantifies the perceived relevance of a Web link to a user's goal by a spreading activation mechanism. The model assumes that users evaluate links on a Web page sequentially and decide to click on a link or to go back to the previous page by a Bayesian satisficing model (BSM) that adaptively evaluates and selects actions based on a combination of previous and current assessments of the relevance of link texts to information goals. SNIF-ACT 1.0 utilizes the measure of utility, called information scent, derived from IFT to predict rankings of links on different Web pages. The model was tested against a detailed set of protocol data collected from 8 participants as they engaged in two information-seeking tasks using the World Wide Web. The model provided a good match to participants' link selections. In SNIF-ACT 2.0, we included the adaptive link selection mechanism from the BSM that sequentially evaluates links on a Web page. The mechanism allowed the model to dynamically build up the aspiration levels of actions in a satisficing process (e.g., to follow a link or leave a Web site) as it sequential assessed link texts on a Web page. The dynamic mechanism provides an integrated account of how and when users decide to click on a link or leave a page based on the sequential, ongoing experiences with the link context on current and previous Web pages. SNIF-ACT 2.0 was validated on a data set obtained from 74 subjects. Monte Carlo simulations of the model showed that SNIF-ACT 2.0 provided better fits to human data than SNIF-ACT 1.0 and a Position model that used position of links on a Web page to decide which link to select. We conclude that the combination of the IFT and the BSM provides a good description of user-Web interaction. Practical implications of the model are discussed.
Information foraging theory is an approach to understanding how strategies and technologies for information seeking, gathering, and consumption are adapted to the flux of information in the environment. The theory assumes that people, when possible, will modify their strategies or the structure of the environment to maximize their rate of gaining valuable information. The theory is developed by (a) adaptation (rational) analysis of information foraging problems and (b) a detailed process model (adaptive control of thought in information foraging [ACT-IF]). The adaptation analysis develops (a) information patch models, which deal with time allocation and information filtering and enrichment activities in environments in which information is encountered in clusters; (b) information scent models, which address the identification of information value from proximal cues; and (c) information diet models, which address decisions about the selection and pursuit of information items. ACT-IF is instantiated as a production system model of people interacting with complex information technology. (PsycINFO Database Record (c) 2009 APA, all rights reserved)
A Region of Proximal Learning model is proposed emphasizing two components to people’s study time allocation, controlled by different metacognitive indices. The first component is choice, which is further segmented into two stages: (1) a decision of whether to study or not and (2) the order of priority of items chosen. If the people’s Judgments of Learning (JOLs) are sufficiently high that they believe they know the items already, they will choose to not study. If they do choose to study, the order is from that which they believe is almost known to that which they believe is more difficult (high JOL to low JOL). The second component is perseverance, with emphasis on the rule for stopping studying once study has begun on an item. We propose that people use a previously unexplored process-oriented metacognitive marker: their judgments of the rate of learning (jROLs), to decide when to stop. When learning is proceeding quickly and the jROL value is high they continue studying. When the jROL approaches zero, and their subjective assessment indicates learning is at a standstill they stop. The extant literature bearing on this model is reviewed, and eight new experiments, all of which support the model, are presented.
Do humans search in memory using dynamic local-to-global search strategies similar to those that animals use to forage between patches in space? If so, do their dynamic memory search policies correspond to optimal foraging strategies seen for spatial foraging? Results from a number of fields suggest these possibilities, including the shared structure of the search problems-searching in patchy environments-and recent evidence supporting a domain-general cognitive search process. To investigate these questions directly, we asked participants to recover from memory as many animal names as they could in 3 min. Memory search was modeled over a representation of the semantic search space generated from the BEAGLE memory model of Jones and Mewhort (2007), via a search process similar to models of associative memory search (e.g., Raaijmakers & Shiffrin, 1981). We found evidence for local structure (i.e., patches) in memory search and patch depletion preceding dynamic local-to-global transitions between patches. Dynamic models also significantly outperformed nondynamic models. The timing of dynamic local-to-global transitions was consistent with optimal search policies in space, specifically the marginal value theorem (Charnov, 1976), and participants who were more consistent with this policy recalled more items.
Previous research has shown that older adults performed worse in web search tasks, and attributed poorer performance to a decline in their cognitive abilities. We conducted a study involving younger and older adults to compare their web search behavior and performance in ill- defined and well-defined information tasks using a health information website. In ill-defined tasks, only a general description about information needs was given, while in well-defined tasks, information needs as well as the specific target information were given. We found that older adults performed worse than younger adults in well-defined tasks, but the reverse was true in ill-defined tasks. Older adults compensated for their lower cognitive abilities by adopting a top-down knowledge-driven strategy to achieve the same level of performance in the ill-defined tasks. Indeed, path analysis showed that cognitive abilities, health literacy, and knowledge influenced search strategies adopted by older and younger adults. Design implications are also discussed.
Five experiments investigated whether people allocate their study time according to the discrepancy reduction model (i.e., to the most difficult items; J. Dunlosky & C. Hertzog, 1998) or to items in their own region of proximal learning. Consistent with the latter hypothesis, as more time was given, people shifted toward studying more difficult items. Experts, whether college students or Grade 6 children, devoted their time to items that were more difficult than did novices. However, in a multiple-trials experiment, people regressed toward easier items on Trial 2 rather than shifting to more difficult items, perhaps because Trial 1 feedback revealed poor learning of the easiest items. These findings are in opposition to the discrepancy reduction model and support the region of proximal learning hypothesis.
Younger and older adults read and immediately recalled a set of sentences which varied in propositional density. Reading was self-paced and sentence reading time was measured. Older adults spent differentially more time reading the propositionally dense sentences, and although the overall recall performance of older adults was slightly poorer than that of younger adults, age differences were constant across propositional density. Consistent with the Slowing Hypothesis, an analysis of effective reading time (time spent per proposition recalled) demonstrated that older adults were spending proportionately more time to effectively encode the sentences. In addition, a relative memorability analysis (Stine & Wingfield, 1988, 1990a) suggested that the increase in propositional density did not particularly disrupt the organization of the text representation for older adults in this self-paced reading situation. This contrasts with earlier findings in a listening situation. These data provide support for the applicability of the Slowing Hypothesis to language processing, but also suggest that older adults are able to effectively allocate reading time to propositionally dense sentences in order to facilitate organizational processing.
The Battig and Montague (1969) category norms have been an invaluable tool for researchers in many fields, with a recent literature search revealing their use in over 1600 projects published in more than 200 different journals. Since 1969, numerous changes have occurred culturally that warrant the collection of new normative data. For instance, in the mid-1960s, the waltz was a popular dance, and undergraduates wore rubbers on their feet. To meet the need for updated norms, we report an expanded version of the Battig and Montague (1969) norms, based on responses from three different sites varying in geographical locations within the United States. The norms were expanded to include new categories (e.g., ad hoc categories) and new measures, most notably latencies for the generated responses. Analyses demonstrated high levels of geographical stability across the new sites, with lower and more variable levels of generational stability between the Battig and Montague norms and the current norms.