Identification of user confusion in a web application · Identification of user confusion in a web...

IdentificationofuserconfusioninawebapplicationAuthor:MichalHuckoSupervisor: prof.MáriaBieliková

”Confusionisasituationinwhichpeopleareuncertainaboutwhattodoorareunabletounderstandsomethingclearly.”

Histogram representation

of features

Mouse movements

Extracted features

velocity, acceleration, distance,

duration, jerk, ...

Confusion

classifier

If user confused,

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Predict user confusion in real time for webapplications based on logged mouse interactiondata

Goal

• 6 tasks at FiroTour travel agency’s portal• 59 participants• confusionwasloggedwithasoftwarebutton

(exclamationmark)situatedintherighttopcornerofthescreen

• 95 out of 354 tasks with button press

Eyetrackinguserstudy

Results• 99% precision on not confused data (real time)• 40% precision on confused data (real time)• 94% precisiononnotconfuseddata

(predictionaftersession)• 40% precisiononconfuseddata

(predictionaftersession)Wecomparedlogisticregression,randomforestandmultilayerperceptron classifier.

Our method is part of an ongoing commercial projectYesElf. We implemented a production ready module ableto predict the confusion in real time. Hundreds of YesElf’scustomers can use our solution daily.

YesElf

Mousefeatures• Horizontal velocity• Vertical velocity• Velocity• Acceleration• Distance

• Jerk• Num. of movements