visual perception of international traffic signs: influence of e-learning and culture on eye...

Visual Perception of International Traffic Signs:

Influence of e-Learning and Culture on Eye Movements

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Gergely Rakoczi

Andrew T. Duchowski

Helena Casas-Tost

Margit Pohl

2013 Aug. 29th - Gergely Rakoczi et al @ ETSA 2

Authors

Gergely Rakoczi

Andrew T. Duchowski

Helena Casas-Tost

Margit Pohl

Vienna University of Technology

Vienna University of Technology

Clemson University

Universitat Autónoma de Barcelona

2013 Aug. 29th - Gergely Rakoczi et al @ ETSA

Besides eye tracking …

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• Study goals:

– Analysis of eye movements when viewing traffic signs within e-learning scenario

– Investigation of two levels of learner’s preparation (absent or given teaching materials)

– Cultural differences expressed by eye movements

• Why? Motivation:

– Improvement of visual efficiency, user experience in e-learning, usability, HCI of e-learning environments

– (collecting more) recommendations for better design

– Better perception of traffic signs in driving education systems

– E-learning is becoming increasingly important for obtaining drivers license

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So, but now …


Related work

• Eye tracking & Driving

– Studies almost exclusively on visual attention when performing act of driving

• Recognition of traffic signs in various conditions

• Eye movements in driving simulators, drivers‘ fatigue, etc.

– Yan, Guan and Xu: predict the visual perception of traffic signs

• effective for letters and symbols, but not for complex signs

– Ng and Chan: questionnaire on Chinese traffic signs

• 5 cognitive design aspects (familiarity, simplicity, …)

• But: no eye movements

http://www.engineeringletters.com/issues_v14/issue_1/EL_14_1_3.pdf


Related work

• Eye tracking & prior preparation

– Numerous reports on effect of task instruction on eye movements

– E.g reading, visual scene perception (Yarbus)

– Amadieu, Van Gog, Paas, Tricot, and Mariné: Studies on learner’s level of preparation – related to novices and experts

• Eye tracking & e-learning

– Only few eye tracking studies on e-learning systems

– Contextually related are tests on perception of multimedia (text, images, simulations …)

– (fewer) usability tests


Related work

• Eye tracking & Culture

– Chua, Boland and Nisbett: Cultural differences in scene perception

• Different visual strategies for Westerners and Easterners

• Westerns (Americans) fixate faster and longer on foreground and perceive more visual details

• Easterners (Chinese) tend to move eye a holistic manner

– Hellige and Cox: evidence from reading

• English left-hemispheric dominance more sequential/analytic (attention on single letters)

• Chinese right-hemispheric dominance holistical(attention on entire configuration of characters)


Methodology

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Procedure

• 3 x 2 x 2 mixed factorial design

• Between-subjects factors

– Ethnicity (Austrian, Chinese, American)

– Teaching materials (absent, given)

• Within-subject factor

– Sign origin (foreign, domestic signs)

• Study blocked by task types (matching, search, true/false)

• Pairwise comparison using t-test (pooled SD and Bonferronicorrection)


• All Test items Counter-balanced via Latin square in TUWEL

• Mixed and homogeneous tasks

Procedure


Eye Metrics

• Eye tracking metrics in focus:– Total gaze duration

– Time to first fixation

– Total fixation count

– Mean fixation duration

– Overall regression rate on traffic signs

– Task success rate Overall Results

Search Tasks

Mixed

Task Scenario

Homogeneous

Task Scenario

Mean fixation duration

Gaze duration

Task success rate*

Regression rate

Fixation count

Matching Tasks

Gaze duration

...

Mixed

Task Scenario

Homogeneous

Task Scenario

True/false Tasks

Mixed

Task Scenario

Homogeneous

Task Scenario

Gaze duration

...

Gaze duration

...

Gaze duration

...

Gaze duration

...

(for each) Parameter:

Teaching material

Sign origin

Ethnicity

Time tofirst fixation

* … not an eye tracking metric


• Two labs, both equipped with Tobii (50 series)

• 50 Hz, 1280x1024, no chin rest …

• Manual calibration using 9-point grid

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Apparatus

AustriaUSA


• TUWEL (e-learning environment of my home university)

• Based on

• System Languages:

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Stimulus

German English Chinese


• Test involved different task types:

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Tasks and Groups

Search task True/false task Matching task

• Treatment group received

teaching lessons prior to the test


• Austria: closest to the international norm

• China: similar to norm, but changes in coloring

• USA: no adoption of the international norm, differences in coloring, shape and style

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Traffic signs


• 3 countries of 3 different continents– Europe (Austria)

– North America (USA)

– Asia (China)

• N=36

• 12 from each country

• 6 females, 6 males for each country

• 3 of male/female of each country in treatment group (teaching lessons) for balance

• Average age: 26.3 (between 22 and 34)

• Recruitment criteria: driving license

• Additional recruitment criteria for Chinese

• 3 experiments excluded (calibration difficulties)

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Participants


Results

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• No significant influence of prior preparation

• Possible reasons?

– Were teaching lessons confusing? Low quality?

– Not really, …Questionnaire revealed that online instructions perceived rather simple than

complex, easy to understand and rather useful than unusable. Low standard deviation indicates coherency among participants’ feedbacks.

– Participants’ level of knowledge on traffic signs already high prior to the study

• average of 7 years of driving experience

• Rather cognitive heuristics were used to solve tasks

– … or did participants skipped reading them?

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Influence of teaching materials


Teaching material 1

Teaching material 2

Austrian American Chinese

Influence of teaching materials


• strong influence for all metrics AND task types

• strongest effect on search tasks, weakest on true/false tasks

• Foreign signs provoke …

– longer gaze duration & lower scores,

– higher fixation counts & regression rates

– Lower times to first fixation (out-of context object?)

– longer mean fixation durations

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domestic (Chinese) foreign (American) foreign (Austrian)

Same participant!

Influence of sign origin


Matching task Austrian heatmap

Chinese heatmap American heatmap

• Most significant results for eye movement in mixed scenarios

Different participants!

Influence of sign origin


• Similar among all conditions

• Exception: significantly lower for every task type and scenario for Americans

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Culture: mean fixation durations

• Interesting: Chinese fixated almost twice as fast on traffic signs

• Visual strategies to fixate faster on all elements to get overview

• Or Chinese more likely to be distracted by figurative visuals?

Culture: time to first fixation


• Corroborate the finding foreground objects, retrieve more visual detail

• Differences in motivation, concentration, impatience, expertise?

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Chinese gazepath Austrian gazepath

American gazepathTrue/false task

Example: US mean fixation durationsDifferent participants!


Usability issues


• “Americanized” Chinese participants

• 12 participants per ethnic group “weak”

for statistical significance

• The driving experience of Chinese participants was more than half of Austrians and Americans

• Narrow group of participants (students, alumnis only)

• Not 100% real test scenario, as conducted in lab

• Eye tracking data is very “noisy”– the more complex the stimulus gets …

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Limitations

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Thanks for listening … Questions?


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• Inman, V.W. 2012. Conspicuity of traffic signs assessed by eye tracking and immediate recall. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting 56, 2251-2255.

• Kaakinen, J.K., Hyönä, J. 2010. Task effects on eye movements during reading. Journal of experimental psychology. Learning, memory, and cognition 36, 6, 1561-6.

• Nielsen, J., Pernice, K. 2010. Eyetracking Web Usability. Voices That Matter. New Riders, Berkeley.

• Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H. 2011. Eye Tracking: A Comprehensive Guide to Methods and Measures. Oxford University Press, Oxford.

• Amadieu, F., Van Gog, T., Paas, F., Tricot, A., Mariné, C. 2009. Effects of prior knowledge and concept-map structure on disorientation, cognitive load, and learning. Learning and Instruction 19, 5, 376-386.

• Chua, H.F., Boland, J.E., Nisbett, R.E. 2005. Cultural variation in eye movements during scene perception. In Proceedings of the National Academy of Sciences of the United States of America 102, 35, 12629-12633.

• Hellige, J.B., Cox, P.J. 1976. Effects of concurrent verbal memory on recognition of stimuli from the left and right visual fields. Journal of Experimental Psychology: Human Perception and Performance 2, 210-221.

• Tan, L.H., Liu, H.L., Perfetti, C.A., Spinks, J.A., Fox, P.T., Gao, J.H. 2001. The neural system underlying Chinese logograph reading. NeuroImage 13, 836-846.

• Ng, A.W.Y., Chan, A.H.S. 2007. Cognitive design features on traffic signs. Engineering Letters 14, 13-18.

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• Jacob, R.J.K., Karn, K.S. 2003. Eye Tracking in Human Computer Interaction and Usability Research: Ready to Deliver the Promises. In The Mind’s Eye: Cognitive and Applied Aspects of Eye Movement Research, Hyönä, J., Radach, R., Deubel, H., Eds. Elsevier Science, Amsterdam, 573-605.

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