Testing for statistically significant differences between groups of scan patterns

Feusner, Matt; Lukoff, Brian

doi:10.1145/1344471.1344481

Cited by 28 publications

(26 citation statements)

References 17 publications

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“…In the present study the Levenshtein distance was used to compare the sequences of the gaze locations across participants (cf. Feusner & Lukoff, 2008).…”

Section: Gaze Datamentioning

confidence: 99%

In the eyes of the beholder: How experts and novices interpret dynamic stimuli

Jarodzka

Scheiter

Gerjets

et al. 2010

Learning and Instruction

320

181

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Jarodzka, H., Scheiter, K., Gerjets, P., & Van Gog, T. (2010). In the eyes of the beholder: How experts and novices interpret dynamic stimuli. Learning and Instruction, 20, 146-154. doi:10.1016/j.learninstruc.2009.02.019Tasks with a complex, dynamic visual component require not only the acquisition of conceptual/procedural but also of perceptual/attentional skills. This study examined expertise differences in perceiving and interpreting complex, dynamic visual stimuli on a performance and on a process level, including perceptual and conceptual strategies. Performance, eye movement, and verbal report data were obtained from seven experts and 14 novices. Results show that experts compared to novices attend more to relevant aspects of the stimulus, use more heterogeneous task approaches, and use knowledge-based shortcuts. Implications for instructional design for the acquisition of perceptual skills are discussed

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“…In the present study the Levenshtein distance was used to compare the sequences of the gaze locations across participants (cf. Feusner & Lukoff, 2008).…”

Section: Gaze Datamentioning

confidence: 99%

In the eyes of the beholder: How experts and novices interpret dynamic stimuli

Jarodzka

Scheiter

Gerjets

et al. 2010

Learning and Instruction

320

181

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“…For this reason, we used corrected post-hoc contrasts (Games-Howell test) when this assumption was violated. Further, we employed a nonparametric procedure [Feusner and Lukoff, 2008] to confirm the ANOVA results and found general agreement. C-C (n=55) .333 .086 I-I (n=78)…”

Section: Analysis and Resultsmentioning

confidence: 78%

Using ScanMatch scores to understand differences in eye movements between correct and incorrect solvers on physics problems

Madsen

Larson

Loschky

et al. 2012

Proceedings of the Symposium on Eye Tracking Research and Applications

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Using a ScanMatch algorithm we investigate scan path differences between subjects who answer physics problems correctly and incorrectly. This algorithm bins a saccade sequence spatially and temporally, recodes this information to create a sequence of letters representing fixation location, duration and order, and compares two sequences to generate a similarity score. We recorded eye movements of 24 individuals on six physics problems containing diagrams with areas consistent with a novice-like response and areas of high perceptual salience. We calculated average ScanMatch similarity scores comparing correct solvers to one another (C-C), incorrect solvers to one another (I-I), and correct solvers to incorrect solvers (C-I). We found statistically significant differences between the C-C and I-I comparisons on only one of the problems. This seems to imply that top down processes relying on incorrect domain knowledge, rather than bottom up processes driven by perceptual salience, determine the eye movements of incorrect solvers. IntroductionResearchers have found consistent patterns of wrong answers to many simple conceptual physics questions [Trowbridge and McDermott 1980;McDermott et. al 1987]. Several cognitive topdown explanations have been provided, including misconceptions formed through interactions with the natural world or misapplication of conceptual resources [Docktor and Mestre 2011]. However, recent claims by Heckler [2011] have suggested a perceptual basis for students' incorrect answers, which are based on attention being directed to the most perceptually salient and plausibly relevant features in a problem. The most salient features capture attention through perceptual processes and less salient features have little opportunity to be considered. Heckler shows some evidence for perceptually-driven responses; however, no eye movement data supporting this hypothesis is provided. Further, he does not provide a specific definition of salience. Therefore, incorrect answers may be governed either by top-down processes relying on incorrectly learned or applied information, or by bottom-up perceptual processes resulting in certain elements capturing attention and leading to activation of reasoning resources based on theseelements.An eye-movement study was used to test these competing hypotheses. Introductory and graduate physics students answered conceptual physics problems regarding a diagram [Madsen et al., 2011]. Three areas of interest (AOIs) were defined for each diagram. First, thematically-relevant AOIs that contained information necessary to correctly answer the question were determined by experts in physics. Second, novice-like AOIs were defined based on coded interview data from novices [Madsen et al. 2011], and third, perceptually salient AOIs were defined as the area(s) on the diagram with the highest saliency rating according to the salience maps produced by a computational algorithm [Itti 2000]. For each problem, the percentage of time spent in each type of interest area was compared be...

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“…Sometimes, the overall aim is to compare whole groups of participants with each other. One solution for performing the according statistical comparison is delivered by Feusner and Lukoff [2008]. They present a method to combine many pairwise comparisons in a meaningful and computational efficient way.…”

Section: Discussionmentioning

confidence: 99%

“…In practice, the need to compare and analyze scanpaths often results in considerable manual data analysis and description of surface features of single scanpath visualizations [Ehmke and Wilson 2007;Josephson and Holmes 2006]. Statistical testing of scanpath similarity between groups has been considered difficult to the level of unachievable [Tzanidou et al 2005], and the solutions recently invented are bordering to computationally intractable [Feusner and Lukoff 2008].…”

mentioning

confidence: 99%

A vector-based, multidimensional scanpath similarity measure

Jarodzka¹,

Holmqvist

Nyström

2010

Proceedings of the 2010 Symposium on Eye-Tracking Research &Amp; Applications - ETRA '10

141

112

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Figure 1: Are these scanpaths similar? Scanpaths from two participants looking at the same stimulus. AbstractA great need exists in many fields of eye-tracking research for a robust and general method for scanpath comparisons. Current measures either quantize scanpaths in space (string editing measures like the Levenshtein distance) or in time (measures based on attention maps). This paper proposes a new pairwise scanpath similarity measure. Unlike previous measures that either use AOI sequences or forgo temporal order, the new measure defines scanpaths as a series of geometric vectors and compares temporally aligned scanpaths across several dimensions: shape, fixation position, length, direction, and fixation duration. This approach offers more multifaceted insights to how similar two scanpaths are. Eight fictitious scanpath pairs are tested to elucidate the strengths of the new measure, both in itself and compared to two of the currently most popular measures -the Levenshtein distance and attention map correlation.

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Testing for statistically significant differences between groups of scan patterns

Cited by 28 publications

References 17 publications

In the eyes of the beholder: How experts and novices interpret dynamic stimuli

In the eyes of the beholder: How experts and novices interpret dynamic stimuli

Using ScanMatch scores to understand differences in eye movements between correct and incorrect solvers on physics problems

A vector-based, multidimensional scanpath similarity measure

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