Publications by authors named "Jason M Tangen"

This paper distils seven key lessons about 'error' from a collaborative webinar series between practitioners at Victoria Police Forensic Services Department and academics. It aims to provide the common understanding of error necessary to foster interdisciplinary dialogue, collaboration and research. The lessons underscore the inevitability, complexity and subjectivity of error, as well as opportunities for learning and growth.

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Visual categorisation relies on our ability to extract useful diagnostic information from complex stimuli. To do this, we can utilise both the "high-level" and "low-level" information in a stimulus; however, the extent to which changes in these properties impact the decision-making process is less clear. We manipulated participants' access to high-level category features via gradated reductions to image resolution while exploring the impact of access to additional category features through a dual-stimulus presentation when compared with single stimulus presentation.

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Expert fingerprint examiners demonstrate impressive feats of memory that may support their accuracy when making high-stakes identification decisions. Understanding the interplay between expertise and memory is therefore critical. Across two experiments, we tested fingerprint examiners and novices on their visual short-term memory for fingerprints.

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Decisions in forensic science are often binary. A firearms expert must decide whether a bullet was fired from a particular gun or not. A face comparison expert must decide whether a photograph matches a suspect or not.

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Perhaps it is no accident that insight moments accompany some of humanity's most important discoveries in science, medicine, and art. Here we propose that feelings of insight play a central role in (heuristically) selecting an idea from the stream of consciousness by capturing attention and eliciting a sense of intuitive confidence permitting fast action under uncertainty. The mechanisms underlying this Eureka heuristic are explained within an active inference framework.

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People can fail to notice objects and events in their visual environment when their attention is engaged elsewhere. This phenomenon is known as inattentional blindness, and its consequences can be costly for important real-world decisions. However, not noticing certain visual information could also signal expertise in a domain.

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False "Aha!" moments can be elicited experimentally using the False Insight Anagram Task (FIAT), which combines semantic priming and visual similarity manipulations to lead participants into having "Aha!" moments for incorrect anagram solutions. In a preregistered experiment ( = 255), we tested whether warning participants and explaining to them exactly how they were being deceived, would reduce their susceptibility to false insights. We found that simple warnings did not reduce the incidence of false insights.

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We used a longitudinal randomized control experiment to compare the effect of specific practice (training on one form of a task) and varied practice (training on various forms of a task) on perceptual learning and transfer. Participants practiced a visual search task for 10 hours over 2 to 4 weeks. The specific practice group searched for features only in fingerprints during each session, whereas the varied practice group searched for features in five different image categories.

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The FIAT paradigm (Grimmer et al., 2021) is a novel method of eliciting 'Aha' moments for incorrect solutions to anagrams in the laboratory, i.e.

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Our basic beliefs about reality can be impossible to prove and yet we can feel a strong intuitive conviction about them, as exemplified by insights that imbue an idea with immediate certainty. Here we presented participants with worldview beliefs such as "people's core qualities are fixed" and simultaneously elicited an aha moment. In the first experiment (N = 3000, which included a direct replication), participants rated worldview beliefs as truer when they solved anagrams and also experienced aha moments.

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Insight experiences are sudden, persuasive, and can accompany valuable new ideas in science and art. In this preregistered experiment, we aim to validate a novel visceral and continuous measure of insight problem solving and to test whether and embodied feelings of insight can predict correct solutions. We report several findings.

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Experts outperform novices on many cognitive and perceptual tasks. Extensive training has tuned experts to the most relevant information in their specific domain, allowing them to make decisions quickly and accurately. We compared a group of fingerprint examiners to a group of novices on their ability to search for information in fingerprints across two experiments-one where participants searched for target features within a single fingerprint and another where they searched for points of difference between two fingerprints.

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When a fingerprint is located at a crime scene, a human examiner is counted upon to manually compare this print to those stored in a database. Several experiments have now shown that these professional analysts are highly accurate, but not infallible, much like other fields that involve high-stakes decision-making. One method to offset mistakes in these safety-critical domains is to distribute these important decisions to groups of raters who independently assess the same information.

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Some ideas that we have feel mundane, but others are imbued with a sense of profundity. We propose that Aha! moments make an idea feel more true or valuable in order to aid quick and efficient decision-making, akin to a heuristic. To demonstrate where the heuristic may incur errors, we hypothesized that facts would appear more true if they were artificially accompanied by an Aha! moment elicited using an anagram task.

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Humans can see through the complexity of scenes, faces, and objects by quickly extracting their redundant low-spatial and low-dimensional global properties, or their style. It remains unclear, however, whether semantic coding is necessary, or whether visual stylistic information is sufficient, for people to recognize and discriminate complex images and categories. In two experiments, we systematically reduce the resolution of hundreds of unique paintings, birds, and faces, and test people's ability to discriminate and recognize them.

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Forensic science techniques are often used in criminal trials to infer the identity of the perpetrator of crime and jurors often find this evidence very persuasive. Unfortunately, two of the leading causes of wrongful convictions are forensic science testing errors and false or misleading forensic testimony (Saks and Koehler, 2005). Therefore, it is important to understand jurors' pre-existing beliefs about forensic science, as these beliefs may impact how they evaluate forensic evidence in the courtroom.

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Arguably, it is not possible to study insight moments during problem solving without being able to accurately detect when they occur (Bowden and Jung-Beeman, 2007). Despite over a century of research on the insight moment, there is surprisingly little consensus on the best way to measure them in real-time experiments. There have also been no attempts to evaluate whether the different ways of measuring insight converge.

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Scarf et al. (Proc Natl Acad Sci 113(40):11272-11276, 2016) demonstrated that pigeons, as with baboons (Grainger et al. in Science 336(6078):245-248, 2012; Ziegler in Psychol Sci.

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Perceptual expertise is notoriously specific and bound by familiarity; generalizing to novel or unfamiliar images, objects, identities, and categories often comes at some cost to performance. In forensic and security settings, however, examiners are faced with the task of discriminating unfamiliar images of unfamiliar objects within their general domain of expertise (e.g.

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Human factors and their implications for forensic science have attracted increasing levels of interest across criminal justice communities in recent years. Initial interest centred on cognitive biases, but has since expanded such that knowledge from psychology and cognitive science is slowly infiltrating forensic practices more broadly. This article highlights a series of important findings and insights of relevance to forensic practitioners.

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Are strategies for learning in education effective for learning in applied visual domains, such as fingerprint identification? We compare the effect of practice with immediate corrective feedback (feedback training), generating labels for features of matching and mismatching fingerprints (labels training), and contrasting matching and mismatching fingerprints (contrast training). We benchmark these strategies against a baseline of regular practice discriminating fingerprints. We found that all 3 training protocols-feedback, labels, and contrasts-resulted in a significantly greater ability to discriminate new pairs of prints (independent of response bias) than the baseline training protocol.

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It is a compelling idea that an image as simple as a Necker cube, or a duck-rabbit illusion, can reveal something about a person's creativity. Surprisingly, there are now multiple examples showing that people who are better at discovering 'hidden' images in a picture, are also better at solving some creative problems. Although this idea goes back at least a century, little is known about how these two tasks-that seem so different on the surface-are related to each other.

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Experience identifying visual objects and categories improves generalization within the same class (e.g., discriminating bird species improves transfer to new bird species), but does such perceptual expertise transfer to coarser category judgments? We tested whether fingerprint experts, who spend their days comparing pairs of prints and judging whether they were left by the same finger or two different fingers, can generalize their finger discrimination expertise to people more broadly.

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Previous demonstrations of context effects in the forensic comparison sciences have shown that the number of "match" responses a person makes can be swayed by case information. Less clear is whether these effects are a result of changes in accuracy (e.g.

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