Post on 02-Jan-2016
An Eye Tracking StudyShannon Fitzhugh, Thomas F Shipley, Nora Newcombe,
Dominique DumayTemple University
June 14, 2008
Individual Differences in Mental Rotation of Real World Shepard-
Metzler Figures
OverviewBrief Review of Individual Differences
literatureIdentification of “new” group (Geisler,
Lehmann, & Eid 2006)Eye Movements in Mental Rotation
Just & Carpenter (1976) 3-dimensional stimuliMethodsResultsDiscussionQuestions????
Individual differencesFocus on Gender differences
Biological mechanismsHormones (Hausmann et al.)Different areas of activation in the brain (Hugdahl et
al., 2006)
Experience mediatesComputer experience (Terlecki & Newcombe,
2005)Training (Sorby & Baartmans, 1996;
Wiedenbauer et al., 2007; Hand & Uttal, in prep)
Introducing….Non-rotatorsLatent class analysis of MRT-A (Geisler et
al., 2006)5 “groups” of rotators
Two “low” – poor MRT-A performanceThree “high” – good MRT-A performance
High groups – only differ in speedResponse probabilities drop off after 12 (no drop
off), 8, & 4 Low groups
Poor mental rotators – low solution probabilities for all items
Non – rotators Identified by response patterns on the MRT-AQualitative differences between target and
distracter
Eye Movements and Mental RotationJust & Carpenter (1976)
Number of fixations increased for low ability rotators
Number of times switched between figures increased monotonically
Search, Transform, CompareOur Expansions
Greater number of subjects (them=8; us=33)Three groups of rotators (high, low, non)Statistical analysis
3-Dimensional StimuliMRT research uses 2-Dimensional
perspective drawings3D-like virtual items (Wohlschlager &
Wohlschlager, 1998)Manual training using Virtual Reality stimuli
(Ruddle & Jones, 2001)Non-rotators
Create stimuli amenable to their strategy to keep them above floor
Application to STEM disciplinesGeology, Engineering, Chemistry, Biology,
Imaging
Methods Vandenberg MRT (1988)
Why not MRT-A? Did not have it Same items for non-rotator identification
present in both testsReal World MRT
3 rotations – 0,45, and 90 degrees 2 axis rotation catch trials30 cm viewing distance – each cube 2.5o
visual angleApplied Science Laboratories MobileEye
0.5o error, 60hz Eye Response Technologies - GazeTracker
Data Analysis Software
Dependent Variables Reaction Time
Predict Linear functionNumber of Fixations
Figure switching number of times participants switch
consecutive fixations between the left and right figures
Fixation Duration
Intra-object v. inter-object fixations
Results – Getting Away from the Descriptive
Time course of intra-object to inter-object fixationsChanges over time?No differences between highs/lows
Search, Transform, CompareInitially defined Transform – others by defaultSome preliminary evidence – although
pattern a bit differentDetermining ways to quantify so statistical
analysis can be preformed
SummaryReplicate traditional MR functions with real
world stimuliLinear RT function Better overall performance
Replicate Just & Carpenter – with non-rotatorsgreater number of fixations for low abilityMonotonic function switching between
figures for high/lowNon-rotators trending toward doubling this
Longer fixation duration for non-rotatorsHigher proportion of intra-object to inter-
object fixations for high and low ability
DiscussionReal World 3D stimuli behave similarly to 2D
Linear reaction timeMonotonic switching between figures for high/low
abilitySimilar eye movement patterns for high/low
ability Including non-rotators in low groups may have
masked these similaritiesSimilar strategies or differing strategies resulting
in similar eye movements?Non-rotators
Pattern of eye movements consistent with feature comparison strategy
Longer fixation durations indicative of increase processing timeCounting strategies
Future DirectionsTraining study – Don’t Sleep In!!
The Effects of Working Memory Training versus Spatial Visualization training on spatial skills
Gesture studyEye movements, verbal report, and
spontaneous gesture (Levine & Goldin-Meadow)
This research was supported by a National Science Foundation grant to support the Spatial Intelligence and Learning Center (No. SBE0541957).
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