Misdirection in magic: Implications for the relationship between eye gaze and attention

Kuhn, Gustav; Tatler, Benjamin W.; Findlay, John M.; Cole, Geoff G.

doi:10.1080/13506280701479750

Cited by 87 publications

(104 citation statements)

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“…In a replication of the Simons and Chabris inattentional blindness study (1999), Memmert (2006) showed that the fixation location of children did not predict their likelihood of detecting the unexpected gorilla. Similar evidence of object detection without fixation has been shown by Kuhn and colleagues across a series of studies using magic tricks (Kuhn, Amlani, & Rensink, 2008;Kuhn & Tatler, 2005;Kuhn, Tatler, Findlay, & Cole, 2008). Recording eye fixation during live and pre-recorded magic tricks revealed no effect of eccentricity of gaze on detection of the event critical to the trick (Kuhn & Tatler, 2005;Kuhn, Tatler, et al, 2008).…”

supporting

confidence: 51%

“…Similar evidence of object detection without fixation has been shown by Kuhn and colleagues across a series of studies using magic tricks (Kuhn, Amlani, & Rensink, 2008;Kuhn & Tatler, 2005;Kuhn, Tatler, Findlay, & Cole, 2008). Recording eye fixation during live and pre-recorded magic tricks revealed no effect of eccentricity of gaze on detection of the event critical to the trick (Kuhn & Tatler, 2005;Kuhn, Tatler, et al, 2008). Failure to detect changes to object features has also been shown during an interactive task in virtual reality (Triesch, Ballard, Hayhoe, & Sullivan, 2003).…”

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The Penny Drops: Change Blindness at Fixation

2012

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Our perception of the visual world is fallible. Unattended objects may change without us noticing as long as the change does not capture attention (change blindness). However, it is often assumed that changes to a fixated object will be noticed if it is attended. In this experiment we demonstrate that participants fail to detect a change in identity of a coin during a magic trick even though eyetracking indicates that the coin is tracked by the eyes throughout the trick. The change is subsequently detected when participants are instructed to look for it. These results suggest that during naturalistic viewing attention can be focused on an object at fixation without including all of its features.

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The Penny Drops: Change Blindness at Fixation

2012

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“…In fact, having the model present live or on video might have adverse effects on the learner's attention. On the one hand, eye tracking research has shown that our gaze allocation is socially directed, that is, we tend to follow another person's gaze (which is often used in magic tricks to misdirect observers' attention; Kuhn et al 2008). On the other hand, eye tracking research has shown that we tend to look primarily at the person's face (as much as 95% of the time in face-to-face situations and 89% of the time on video), rather than at his or her gestures, for example (Gullberg and Holmqvist 2002).…”

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Example-Based Learning: Integrating Cognitive and Social-Cognitive Research Perspectives

2010

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Example-based learning has been studied from different perspectives. Cognitive research has mainly focused on worked examples, which typically provide students with a written worked-out didactical solution to a problem to study. Social-cognitive research has mostly focused on modeling examples, which provide students the opportunity to observe an adult or a peer model performing the task. The model can behave didactically or naturally, and the observation can take place face to face, on video, as a screen recording of the model's computer screen, or as an animation. This article reviews the contributions of the research on both types of example-based learning on questions such as why examplebased learning is effective, for what kinds of tasks and learners it is effective, and how examples should be designed and delivered to students to optimize learning. This will show both the commonalities and the differences in research on example-based learning conducted from both perspectives and might inspire the identification of new research questions. Bandura's (1977Bandura's ( , 1986) social learning theory. Both argue that it would be Educ Psychol Rev (2010) 22:155-174 Keywords

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“…There are some studies that use measures that are unrelated to the dynamics, such as the distance of eye fixation to a critical place at a single point in time (Kuhn, Tatler, Findlay, & Cole, 2007), or the probability of saccades during film edits (Smith & Henderson, 2008). The focus of the present article, however, is on studies of eye movements toward the dynamic objects within their stimuli.…”

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DynAOI: A tool for matching eye-movement data with dynamic areas of interest in animations and movies

Papenmeier¹,

Huff²

2010

Behavior Research Methods

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Analyzing gaze behavior with dynamic stimulus material is of growing importance in experimental psychology; however, there is still a lack of efficient analysis tools that are able to handle dynamically changing areas of interest. In this article, we present DynAOI, an open-source tool that allows for the definition of dynamic areas of interest. It works automatically with animations that are based on virtual three-dimensional models. When one is working with videos of real-world scenes, a three-dimensional model of the relevant content needs to be created first. The recorded eye-movement data are matched with the static and dynamic objects in the model underlying the video content, thus creating static and dynamic areas of interest. A validation study asking participants to track particular objects demonstrated that DynAOI is an efficient tool for handling dynamic areas of interest.

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Misdirection in magic: Implications for the relationship between eye gaze and attention

Abstract: Misdirection in magic: Implications for the relationship between eye gaze and attention, Visual Cognition, 16:2-3, 391-405,

Cited by 87 publications

References 33 publications

The Penny Drops: Change Blindness at Fixation

The Penny Drops: Change Blindness at Fixation

Example-Based Learning: Integrating Cognitive and Social-Cognitive Research Perspectives

DynAOI: A tool for matching eye-movement data with dynamic areas of interest in animations and movies

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