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Despite decades of research in the fields of judgment and decision-making, social psychology, cognitive psychology, human-machine interaction, behavioral economics, and neuroscience, we still do not know what “cognitive effort” is. The definitions in use are often imprecise and sometimes diametrically opposed. Researchers with different assumptions talk past each other, and many aspects of effort conservation remain untested and difficult to measure. In this article, we explain why effort is so difficult to pin down and why it is important that researchers develop consensus on precise definitions. Next, we describe major “hidden” sources of miscommunication: areas in which researchers disagree in their underlying assumptions about the nature of effort without realizing it. We briefly review a number of methods used to both measure and manipulate the effortfulness of thinking and highlight why they often produce contradictory findings. We conclude by reviewing existing perspectives on cognitive effort and integrating them to suggest a common framework for communicating about effort as a limited cognitive resource.

We present an empirical demonstration that people rely on linguistic valence as a direct cue to a speaker’s group membership. Members of the U.S. voting public judge positive words as more likely to be spoken by members of their political in-group, and negative words as more likely to be spoken by members of their political out-group (three studies with 655 participants). We further find that participants perceive pluralized forms of nouns as more extremely valenced than singular forms (one study with 280 participants). This allowed us to control for the semantic content of words while eliciting systematic differences in the source attributions made by partisans. Our work contributes to both theory and methodology used to understand the linguistic cues people use to make social relational judgments.

As technology advances, people increasingly outsource cognitive tasks and can more easily access others' knowledge. While externalized aids often support human abilities, they may also make it more difficult for people to assess their own competence. Indeed, using online search engines leads people to treat searchable information as if they already know it (Fisher et al., Journal of Experimental Psychology: General, 2015, 144, 674). Six primary and two supplemental studies (N = 3,262) extend previous research by exploring how illusions of knowledge result from reliance on other agents. After teaming with knowledgeable partners (artificially intelligent agents or human teammates) on a trivia quiz, people overestimated how well they would perform on future quizzes for which help was not available; this bias was not evident for participants who never received help. Moreover, overconfidence was insensitive to whether assistance was provided on hard versus easy problems, or even whether the assistance was accurate. Receiving outside assistance creates an ambiguity regarding who deserves credit for success or blame for failure. When this ambiguity is removed, people become better calibrated. These results indicate that reliance on technology and outside knowledge may change our view of ourselves-convincing us we are more capable than we really are. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Lakoff's model of political ideology proposes people's beliefs about how government should operate are grounded in beliefs about how families should operate. Previous research shows the left-right political spectrum can be explained by differences in preferences for nurturant (Democrats) and disciplinarian (Republican) parenting styles. We extend the theory to another dimension, helicopter versus free range parenting styles. In Study 1, we find parenting attitudes strongly predict paternalistic policy attitudes-more than ideology, party identity, or any other measured demographic variables. In Study 2, we attempt to establish a causal link, but find manipulating preferences for helicopter parenting does not influence policy preferences as Lakoff's model would suggest. In Study 3, we identify a latent variable that predicts preferences for paternalism in parenting, policy, and a host of other domains such as business, medicine, and education. We discuss implications for Lakoff's theory, the political psychology of libertarianism/paternalism, and society at large. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Cognitive ability consists not only of one’s internal competence but also of the augmentation offered by the outside world. How much of our cognitive success is due to our own abilities, and how much is due to external support? Can we accurately draw that distinction? Here, we explored when and why people are unaware of their reliance on outside assistance. Across eight experiments ( N = 2,440 participants recruited from Amazon Mechanical Turk), people showed improved metacognitive calibration when assistance occurred after a delay or required active choice. Furthermore, these findings apply across a wide range of cognitive tasks, including semantic memory (Experiments 1a and 1b), episodic memory (Experiments 2a and 2b), and problem solving (Experiments 3a–3d). These experiments offer important insights into how we understand our own abilities when we rely on outside help.

People are very good at making relative judgments (determining where a stimulus ranks in a distribution) but not very good at making absolute judgments (determining the absolute properties of the stimulus independent of context). Thus, when evaluating various stimuli, people tend to encode ordinal rank rather than objective quality. This leads to a robust bias in memory-based judgments: when the nature of the distribution shifts, people fail to update their memories of ordinal rank, and thus incorrectly judge a stimulus that is at the top [bottom] of the distribution at Time 1 to also be at the top [bottom] of a different distribution at Time 2. In two studies, we demonstrate a crucial moderator of the relative encoding bias on memory-based judgments: category saliency at the time of encoding. More specifically, we reveal that this memory-based judgment bias is reduced if it is made salient at the time of encoding that the stimuli from Time 1 and Time 2 are from different categories and thus different distributions.

While the human visual system is sensitive to numerosity, the mechanisms that allow perception to extract and represent the number of objects in a scene remains unknown. Prominent theoretical approaches posit that numerosity perception emerges from passive experience with visual scenes throughout development, and that unsupervised deep neural network models mirror all characteristic behavioral features observed in participants. Here, we derive and test a novel prediction: if the visual number sense emerges from exposure to real-world scenes, then the closer a stimulus aligns with the natural statistics of the real world, the better number perception should be. But - in contrast to this prediction - we observe no such advantage (and sometimes even a notable impairment) in number perception for natural scenes compared to artificial dot displays in college-aged adults. These findings are not accounted for by the difficulty in object identification, visual clutter, the parsability of objects from the rest of the scene, or increased occlusion. This pattern of results represents a fundamental challenge to recent models of numerosity perception based in experiential learning of statistical regularities, and instead suggests that the visual number sense is attuned to abstract number of objects, independent of their underlying correlation with non-numeric features. We discuss our results in the context of recent proposals that suggest that object complexity and entropy may play a role in number perception.

Failure of replication attempts in experimental psychology might extend beyond p-hacking, publication bias or hidden moderators; reductions in experimental power can be caused by violations of fidelity to a set of experimental protocols. In this article, we run a series of simulations to systematically explore how manipulating fidelity influences effect size. We find statistical patterns that mimic those found in ManyLabs style replications and meta-analyses, suggesting that fidelity violations are present in many replications attempts in psychology. Scholars in intervention science, medicine, and education have developed methods of improving and measuring fidelity, and as replication becomes more mainstream in psychology, the field would benefit from adopting such approaches as well. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

In this Tutorial, we introduce a tool that allows researchers to track subjects’ on- and off-task activity on Qualtrics’ online survey platform. Our TaskMaster tool uses JavaScript to create several arrayed variables representing the frequency with which subjects enter and leave an active survey window and how long they remain within a given window. We provide code and instructions that will allow researchers to both implement the TaskMaster and analyze its output. We detail several potential applications, such as in studies of persistence and cheating, and studies that require sustained attention to experimental outcomes. The TaskMaster is designed to be accessible to researchers who are comfortable designing studies in Qualtrics, but who may have limited experience using programming languages such as JavaScript.

Previous work has demonstrated that certain speech patterns vary systematically between sociodemographic groups, so that in some cases the way a person speaks is a valid cue to group membership. Our work addresses whether or not participants use these linguistic cues when assessing a speaker’s likely political identity. We use a database of speeches by U.S. Congressional representatives to isolate words that are statistically diagnostic of a speaker’s party identity. In a series of four studies, we demonstrate that participants’ judgments track variation in word usage between the two parties more often than chance, and that this effect persists even when potentially interfering cues such as the meaning of the word are controlled for. Our results are consistent with a body of literature suggesting that humans’ language-related judgments reflect the statistical distributions of our environment.

One way to reduce waste and to make a system more robust is to allow its components to pool resources. For example, banks might insure each other or share a common capital reserve. Systems whose resources have been pooled in this way are highly prevalent in such diverse domains as finance, infrastructure, health care, emergency response and engineering. However, these systems have a combination of characteristics that leave them vulnerable to poor decision-making: non-linearity of risk; obvious rewards combined with hidden costs; and political and market incentives that encourage inadequate safety margins. Three studies demonstrate a tendency for managers of such systems to underestimate the probability of cascading failures. We describe a series of behaviorally based policy interventions to mitigate the resulting hazards.

We examined persuasive and expository writing samples collected from more than 300 college students as part of a nine-year cross-sectional and longitudinal study of undergraduate writing performance, conducted between 2000 and 2008. Using newly developed scoring rubrics, longitudinal analyses of writing scores revealed statistically significant growth in writing performance over time. These findings held for both persuasive and expository writing. Although writing performance was better among women than men, and better among students majoring in the humanities and social sciences than in natural sciences and engineering, neither women nor humanities and social science majors showed differential improvement over time from freshman to senior year. Our findings showed reliable increases in writing performance during a student’s college years, and moreover demonstrated that such longitudinal changes can be effectively measured. We call for more such outcome assessment in higher education as an essential tool to enhance student learning.

Beliefs about how effective a cause will be at achieving possible outcomes are critical inputs into a range of decisions, from how to treat an illness to which products to purchase. We identify scope-the number of distinct outcomes a cause is known to achieve-as an important input into judgments of efficacy. We compare causes that lead to worse outcomes (i.e., banes) to those leading to improvements (i.e., boons). People believe that banes with broader scope (i.e., those that lead to more possible outcomes) are more effective and lead to stronger outcomes. In contrast, people believe that boons with narrower scope (i.e., those that lead to fewer possible outcomes) are more effective and lead to stronger outcomes. We document this pattern across four experiments, finding support for differences in mental models for boons and banes.

To date, technological interventions in note-taking have been generally unsuccessful in improving performance. One reason for this lack of success may be that developers focus on making note-taking easier, while neglecting how the technologies could affect the other psychological processes underlying effective note-taking. Importantly, since note-taking serves different purposes in different situations, the effectiveness of various technologies will also be situationally dependent. In this paper, we explore four distinct note-taking settings: the classroom, the boardroom, the hospital room, and the courtroom. In each section, we quickly review important past research before addressing the current state of note-taking in that arena, with special attention given to technological interventions. We conclude each section with a short discussion of what kinds of new technologies would be most helpful for note-taking in those situations.

When forming a judgment about any unknown item, people must draw inferences from information that is already known. This paper examines causal relationships between cues as a relevant factor influencing how people determine the amount of weight to place on each piece of available evidence. We propose that people draw from their beliefs about specific causal relationships between cues when determining how much weight to place on those cues, and that understanding this process can help reconcile differences between predictions of compensatory and lexicographic heuristic strategies. As causal relationships change, different cues become more or less important. Across three experiments, we find support for the use of causal models in determining cue weights, but leave open the possibility that they work in concert with other strategies as well. We conclude by discussing relative strengths and weaknesses of the causal model approach relative to existing models, and suggest areas for future research. Copyright © 2016 John Wiley & Sons, Ltd.

Several models of judgment propose that people struggle with absolute judgments and instead represent options on the basis of their relative standing. This leads to a conundrum when people make judgments from memory: They may encode an option's ordinal rank relative to the surrounding options but later observe a different distribution of options. Do people update their representations when making judgments from memory, or do they maintain their representations based on the initial encoding? In three studies, we found that people making memory-based judgments rely on a stimulus's relative standing in the distribution at the time of encoding rather than attending to absolute quality or updating the stimulus's ordinal ranking in light of the distribution at the time of the later judgment.

People are adept at generating and evaluating explanations for events around them. But what makes for a satisfying explanation? While some scholars argue that individuals find simple explanations to be more satisfying (Lombrozo, 2007), others argue that complex explanations are preferred (Zemla, et al. 2017). Uniting these perspectives, we posit that people believe a satisfying explanation should be as complex as the event being explained-what we term the complexity matching hypothesis. Thus, individuals will prefer simple explanations for simple events, and complex explanations for complex events. Four studies provide robust evidence for the complexity-matching hypothesis. In studies 1-3, participants read scenarios and then predicted the complexity of a satisfying explanation (Study 1), generated an explanation themselves (Study 2), and evaluated explanations (Study 3). Lastly, in Study 4, we explored a different manipulation of complexity to demonstrate robustness across paradigms. We end with a discussion of mechanisms that might underlie this preference-matching phenomenon.

Giving to charity not only helps fund programs that are beneficial to society but also reliably increases the well-being of donors. However, not all donations are equally effective at improving donor happiness. This article reviews the research from psychology and behavioral economics and identifies several key factors for optimizing donor experiences. These lessons can be used to design charitable appeals that are highly effective and that create conditions that make charitable giving more rewarding to donors, which increases the likelihood that they will donate again.

While direct replications such as the “Many Labs” project are extremely valuable in testing the reliability of published findings across laboratories, they reflect the common reliance in psychology on single vignettes or stimuli, which limits the scope of the conclusions that can be reached. New experimental tools and statistical techniques make it easier to routinely sample stimuli, and to appropriately treat them as random factors. We encourage researchers to get into the habit of including multiple versions of the content (e.g., stimuli or vignettes) in their designs, to increase confidence in cross-stimulus generalization and to yield more realistic estimates of effect size. We call on editors to be aware of the challenges inherent in such stimulus sampling, to expect and tolerate unexplained variability in observed effect size between stimuli, and to encourage stimulus sampling instead of the deceptively cleaner picture offered by the current reliance on single stimuli.

Categories often have unobservable diagnostic features. For example, if a person is a lawyer, one might expect him to be both well dressed and knowledgeable about the law. However, without observing the person in a courtroom, one cannot tell whether or not he is knowledgeable about the law. How might we categorize the well-dressed person before we know whether or not he possesses a particular category feature? Two studies showed that, all else equal, individuals prefer to group exemplars into categories that specify fewer unobserved and unobservable features — i.e., those that have a narrower latent scope — to those with a broader latent scope. In Experiment 1, participants were more likely to classify novel exemplars as part of a social category that had a narrower latent scope in a verbal task. Experiment 2 demonstrated that the scope bias generalizes to contexts in which category structure is never explicitly specified.

It is well documented that student–athletes underperform academically. Some researchers have suggested that this underperformance is because student–athletes lack motivation in academic endeavors. In contrast, we find that most student–athletes hold positive private attitudes towards academic achievement, but also believe that their peers do not. In order to fit in, athletes conform to the perceived (but false) social norm in their public behaviors, thus undermining their academic performance and simultaneously reinforcing the (false) social norm for the rest of their team. This pluralistic ignorance suggests that different interventions will be needed to solve the problem than are typically proposed.

This paper proposes an original account of decision anomalies and a computational alternative to existing dynamic models of multi-attribute choice. To date, most models attempting to account for the "Big Three" decision anomalies (similarity, attraction, and compromise effects) are variants of evidence accumulation models, or rational Bayesian analysis. This paper provides an existence proof of a new approach in the form of a multi-agent system based on the principles of voting geometry. Assuming there are a number of neural systems (agents) within an individual's brain, the Big Three decision anomalies can arise as a natural consequence of aggregating preferences across these agents. We operationalize these principles in VAMP, (Voting Agent Model of Preferences), and compare its performance to existing computational models as well as to empirical data. This provides a fundamentally different lens for understanding decision anomalies in multi-attribute choice.

In this issue of Cognition , Thompson and her colleagues challenge the results from a paper we published several years ago (Alter, Oppenheimer, Epley, & Eyre, 2007). That paper demonstrated that metacognitive difficulty or disfluency can trigger more analytical thinking as measured by accuracy on several reasoning tasks. In their experiments, Thompson et al. find evidence that people process information more deeply—but not necessarily more accurately—when they experience disfluency. These results are consistent with our original theorizing, but the authors misinterpret it as counter-evidence because they suggest that accuracy (and even confidence) is a measure of deeper processing rather than a contingent outcome of such processing. We further suggest that Thompson et al. err when they discriminate between “perceptual fluency” and “answer fluency,” the former of which is an element of the latter. Thompson et al. advance research by adding reaction time as a measure of deeper cognitive processing, but we caution against misinterpreting the meaning of accuracy.

Despite the fact that the population of is rapidly aging (Ortman et al., 2014), until recently scholars of charity have largely ignored older adults. Bjalkebring et al. (2016) begin addressing this gap in the literature. By showing that increasing age is associated with stronger feelings of sympathy and compassion and that older adults are more likely to report feeling positive emotions when making donations, Bjalkebring et al. (2016) connect the literature on age-related positivity biases to the literature on philanthropy. We endorse this approach of identifying ways in which older populations differ from younger populations and exploring how those differences might inform donation behavior. Indeed, this tactic has the potential to reveal a large number of age-related differences in giving beyond those based on an age-related positivity bias. It makes sense that Bjalkebring et al. (2016) focused primarily on emotional differences between older and younger adults, as the bulk of the literature on charitable giving has shown that people often give to charity for emotional reasons, and respond more strongly to emotional (than rational) appeals for donations (e.g., Loewenstein and Small, 2007; Huber et al., 2011). In fact, there are other emotional differences aside from positivity biases that have implications for donation behavior. For example, older adults often experience greater emotional complexity—that is, experiencing positive and negative emotions together (Carstensen et al., 2011). Therefore, it may be productive to interpret the higher levels of sympathy and compassion older adults reported in Bjalkebring et al. (2016) experiment 1 through the lens of older adults' improved ability to deal with emotional complexity above and beyond any bias toward purely positive emotions. However, as important as emotion-related differences are to the study of aging and philanthropy, it is worth noting that there are also a number of cognitive factors that influence both older adults' processing of emotional information (such as manipulations of cognitive resources or goals; Reed et al., 2014; Reed and Carstensen, 2015), and giving more generally. Thus, exploring age-related cognitive differences has the potential to reveal additional insight as to how donation behavior changes across the lifespan. Aging is related to cognitive declines in processing speed (Salthouse, 1996) and working memory capacity (Hasher and Zacks, 1989). Importantly, older adults are often able to compensate for these declines by directing cognitive resources toward information of high value (Castel, 2008). Younger adults sometimes find it difficult to discriminate between high-value information and low-value information (Castel, 2008), suggesting that they may not be as effective as older adults in identifying the worthiest causes or the most impactful ways in which to give. If older adults are sensitive to value when making spending decisions, they might be more likely than younger adults to donate, especially to causes they view as important. Older adults may also be better able to effectively determine the highest-value donation in terms of efficiency, personal value, or societal outcomes (for a discussion of younger adults' errors in optimizing the value of donations, see Baron and Szymanska, 2011). Another strategy that older adults may use in light of cognitive declines is to engage in more gist-based processing, especially of monetary information (Castel, 2005). Rather than recalling exact details about studied items, older adults tend to remember general representations of those items, such as approximate value (e.g., remembering that an item costs “about $4.00” rather than “exactly $3.92”), or relative value (e.g., which item cost less than another; Flores et al., 2016). Gist-based processing may have implications for how older adults decide when, how much, and to which causes they donate. If older adults make charitable giving decisions using gist, they may derive warm glow simply from the act of giving, irrespective of the exact dollar amount they donated. Younger adults' more accurate memory for exact prices may lead to different emotional responses to donations of different dollar amounts (for a discussion of the function mapping giving to utility in younger adults, see Strahilavitz, 2011). Furthermore, one of the most widespread “take home” messages that practitioners have derived from the scientific literature on philanthropy is that people are more likely to give (and give larger amounts) when presented with specific, tangible information about a charity's outcomes, as compared to more general information (e.g., giving a milking cow to a particular family, as opposed to general “poverty alleviation”; Cryder et al., 2013). If older adults process information using gist, their giving behavior may be less affected by tangibility than younger adults, as specific details may be lost in favor of a gist-based representation. In other words, common strategies for charitable appeals may be less effective on older populations. Scholars should also pay attention to a number of philanthropy-relevant demographic differences across age groups. For example, older adults' net worth is significantly higher on average than younger adults' (Taylor et al., 2011), and income is a major factor in charitable giving (Gittell and Tebaldi, 2006; Choi and Chou, 2010). Similarly, religious participation has been positively correlated with giving behavior (Jackson et al., 1995) and may be related to age (Davie and Vincent, 1998). These demographic differences are worth considering both because they themselves may be interesting avenues for exploring age-related differences in donation behavior, but also because they represent potential confounds in (inherently quasi-experimental) investigations on how aging affects giving. As noted by Bjalkebring et al. (2016), these sorts of confounds can make it difficult to distinguish between influences of aging, per se, and cohort effects. In sum, findings by Bjalkebring et al. (2016) demonstrate how cognitive aging can influence charitable decision making and serve as motivation for many future avenues of exploration, including how emotional complexity, subjective value, and gist-based processing may affect charitable giving in younger and older adults. Established theories of cognitive aging can be a fruitful source of novel questions about how donation behavior changes across the lifespan, and may have applications for developing charitable appeals aimed at a rapidly increasing segment of the population.

Previous research has shown that disfluency – the subjective experience of difficulty associated with cognitive operations – leads to deeper processing. Two studies explore the extent to which this deeper processing engendered by disfluency interventions can lead to improved memory performance. Study 1 found that information in hard-to-read fonts was better remembered than easier to read information in a controlled laboratory setting. Study 2 extended this finding to high school classrooms. The results suggest that superficial changes to learning materials could yield significant improvements in educational outcomes.

Summary Recent research has demonstrated that, under the right circumstances, making fonts harder to read can improve educational outcomes. However, the initial demonstrations did not fully map out the boundary conditions for where this effect will and will not be observed. In this paper, we identify some of the most plausible moderators of the effect and provide some cautionary notes on how to interpret and report findings regarding disfluency in education. Copyright © 2014 John Wiley & Sons, Ltd.

What makes a good explanation? We examine the function of latent scope, i.e., the number of unobserved phenomena that an explanation can account for. We show that individuals prefer narrow latent scope explanations-those that account for fewer unobserved effects-to broader explanations. In Experiments 1a-d, participants found narrow latent scope explanations to be both more satisfying and more likely. In Experiment 2 we directly manipulated base rate information and again found a preference for narrow latent scope explanations. Participants in Experiment 3 evaluated more natural explanations of unexpected observations, and again displayed a bias for narrow latent scope explanations. We conclude by considering what this novel bias tells us about how humans evaluate explanations and engage in causal reasoning.

A prominent metaphor in American politics associates left with liberals and right with conservatives. Three studies investigate the extent to which this metaphor not only shapes how people talk about politics, but how people think about politics. Participants who are oriented to their right report more conservative political attitudes, while those who are oriented toward their left report more liberal attitudes. This supports the notion that spatial metaphor is a key ingredient underlying abstract thinking even for important belief systems.

Understanding when people reveal unfavorable information about themselves is both practically and theoretically important. Existing research suggests that people tend not to adopt stable disclosure strategies, and consequently disclose too much information in some situations (e.g., embarrassing personal information on Face-book) and too little in other situations (e.g., risky sexual behavior to a physician during diagnosis of a possible sexually transmitted disease). We sought to identify a domain-general cue that predicts self-disclosure patterns. We found that metacognitive ease, or fluency, promoted greater disclosure, both in tightly controlled lab studies (Studies 1a, 1b, and 3) and in an ecologically valid on-line field study (Study 4). Disfluency tended to prime thoughts and emotions associated with risk, which might be one reason why people who experience disfluency are less comfortable with self-disclosure (Studies 2 and 3). We conclude by discussing the implications of these results for theory and clinical practice.

Recent work on judgment and decision making has focused on how people preferentially use cues, or pieces of relevant information, that are easy to access when making decisions. In this article, we discuss a framework for understanding the ways that cues become accessible. We begin by identifying two components of cues and show how these components can become accessible during different parts a decision process. We highlight evidence for the use of accessible information and discuss implications for future research on heuristics.

Past research suggests that semantic and numerical medical risk descriptors may lead to miscommunication and misinterpretation of risk. However, little research has been conducted on systematic features of this bias, and the resulting potential risks to people contemplating or receiving treatment. Three studies explore the influence of verbal versus numerical medical risk descriptions. In Study 1a, San Francisco Bay area residents (N = 59) were presented with semantic descriptors for low-likelihood events and reported their perceived quantitative risk for the events. In Study 1b, undergraduates (N = 29) were presented with semantic versus numerical information about side effects for a prescribed medication and reported their perceived risk and adherence intentions. In Study 1c, San Francisco Bay area residents (N = 125) were presented with semantic versus numerical information about their risk for a disease and reported their perceived risk and intention to adhere to a prescribed treatment. The results of the first study suggest that people systematically overestimate the likelihood of low probability events described in semantic terms such as "low risk" or "people may occasionally experience." The results of the second and third experiment suggest that presenting semantic information about the risks of engaging in a new behavior makes people less likely to engage in that behavior, whereas presenting semantic information about the risks of not engaging in a new behavior makes people more likely to engage in the behavior. The decision to present semantic versus probabilistic information is tantamount to a decision about whether to encourage risk acceptance versus risk avoidance.

Participants are not always as diligent in reading and following instructions as experimenters would like them to be. When participants fail to follow instructions, this increases noise and decreases the validity of their data. This paper presents and validates a new tool for detecting participants who are not following instructions – the Instructional manipulation check (IMC). We demonstrate how the inclusion of an IMC can increase statistical power and reliability of a dataset.

Although many researchers use Wagenaar’s framework for understanding the factors that people use to determine whether a process is random, the framework has never undergone empirical scrutiny. This paper uses Wagenaar’s framework as a starting point and examines the three properties of his framework—independence of events, fixed alternatives, and equiprobability. We find strong evidence to suggest that independence of events is indeed used as a cue toward randomness. Equiprobability has an effect on randomness judgments. However, it appears to work only in a limited role. Fixedness of alternatives is a complex construct that consists of multiple sub-concepts. We find that each of these sub-concepts influences randomness judgments, but that they exert forces in different directions. Stability of outcome ratios increases randomness judgments, while knowledge of outcome ratios decreases randomness judgments. Future directions for development of a functional framework for understanding perceptions of randomness are suggested. Copyright # 2008 John Wiley & Sons, Ltd.

People tend to believe that sequences of random events produce fewer and shorter streaks than is actually the case. Although this error has been demonstrated repeatedly and in many forms, nearly all studies of randomness cognition have focused on how people think about random events occurring in the present or future. This article examines how our biased beliefs about randomness interact with properties of memory to influence our judgments about and memory for past random events. We explore this interaction by examining how beliefs about randomness affect our memory for random events and how certain properties of memory alter our tendency to categorize events as random. Across three experiments, we demonstrate an interaction between randomness cognition and three well-established but distinct properties of memory: (1) the reconstructive nature of memory, (2) primacy and recency effects, and (3) duration neglect. Theoretical and practical implications are discussed.