sap lean ux visit to tech3lab

Do you know how users really feel?

SYLVAIN SÉNÉCAL, Ph.D.Co-director

MArC FreDette, Ph.D.Researcher

PIerre-MAJOrIQUe LÉGer, Ph.D.Co-director

#uxt3l @tech3lab_hec

© Copyright Tech3Lab 2015

Do you know how users really feel?

SYLVAIN SÉNÉCAL, Ph.D.Co-directorFull Professor

PIerre-MAJOrIQUe LÉGer, Ph.D.Co-directorFull Professor

MArC FreDette, Ph.D.ResearcherAssociate Professor

EASE OF USE?

© Copyright Tech3Lab 2015© Copyright Tech3Lab 2015

EASE OF USE?


UXManaging Business User Experience

BUSINeSS INteLLIGeNCe

MArketING AND eLeCtrONIC COMMerCe

INFOrMAtION teChNOLOGIeS

INNOVAtION 2013

Management comittee

SYLVAIN SÉNÉCAL, Ph.D.Co-directorFull Professor

FrANÇOIS COUrteMANChe, Ph.D.Research professional

MArC FreDette, Ph.D.ResearcherAssociate Professor

PIerre-MAJOrIQUe LÉGer, Ph.D.Co-directorFull Professorn

eLISe LABONtÉ-LeMOYNe, Ph.D.Post-Doctoral researcher

Principal researchers Other membersCaroline AUBÉ Management

Gilbert BABIN TI

* Ann-Frances CAMERON TI

Michel COSSETTE Gestion des ressources haimaines

Danilo C. DANTAS Marketing

* Marc FREDETTE Science de la décision

Camille GRANGE TI

Yany GRÉGOIRE Marketing

Réal LABELLE Sciences comptables

* Sandra LAPORTE Marketing

* Pierre-Majorique LÉGER TI

* Renaud LEGOUX Marketing

* Ana ORTIZ DE GUINEA TI

* Jacques ROBERT TI

* Sylvain SÉNÉCAL Marketing

Louis-Philippe SIROIS Sciences comptables

Stefan TAMS Marketing

* Ryad TITAH TI

* Membres de l’équipe FQRSC en fonctionnement

Henri BARKI TI HEC Montréal

Éric BRUNELLE Management HEC Montréal

Patrick CHARLAND Didactique UQAM

Aude DUFRESNE Communication U de Montréal

Alina Maria DULIPOVICI TI HEC Montréal

Jean-François GAJEWSKI Finance IAE Savoie

Abdelouahab MEKKI Marketing U. Sherbrooke

Julien MERCIER Didactique UQAM

René RIEDL TI Université Linz

Research assistants OperationsSabrina ALARIE-CARRIèRE Département de psychologie U de Montréal

Emma CAMPBELL Département de psychologie U de Montréal

Gabrielle CHÉNIER-LEDUC Département de psychologie U de Montréal

Régine GAGNON Département de psychologie U de Montréal

Cindy MADDALENA Département de psychologie U de Montréal

Beverly RESSEGUIER Département de psychologie U de Montréal

Marianne VADEZ Département de psychologie U de Montréal

Adélaïde VAUTIER Département de psychologie U de Montréal

Analystes Marie-Christine BASTARACHE ROBERGE

Département TI HEC Montréal

Laurence DUMONT Département de psychologie U de Montréal

Félix LAROCHELLE-BRUNET Département de psychologie U de Montréal

David BRIEUGNE Département TI HEC Montréal

Vanessa GEORGES Département du marketing HEC Montréal

Shirley-Anne PAGÉ Département TI HEC Montréal

Brendan SCULLY Département TI HEC Montréal


Partners


Financing Agencies


Tech3Lab 2015 : The most important UX Lab in North America

Microprogramme in User Experience

http://www.hec.ca/ux/


Microprogramme in User ExperienceEN fraNçais MicroprograMME dE 15 créditsduréE MiNiMalE : 2 triMEstrEsduréE MaxiMalE : 3 aNs

adMissioN : HiVEr 2016lEs 5 cours :

aNalysE Et iNférENcE statistiquE

WEb aNalytiquE

ux : foNdEMENts Et MEsurEs

1 2

coNcEptioN dEs systèMEs d’iNforMatioN

4

3

réalisatioN d’uN projEt EN ux

5


What is eye-tracking?


tobii eyetracker X60



Source: http://eyetracking.me/?page_id=9

What is Eye Tracking

(A)

(B)

Figure 1. Illustration of pupillary responses in cognitive task execution, (A) Mental multiplication task and pupil size change, (B) Difficulty effect on pupil dilation evoked by mental multiplication of

two numbers displayed together for eight seconds (adopted from Klingner's Dissertation (Figure 5.5) [1]).

cognitive tasks. Figure 1(A) illustrates cognitive tasks (easy, hard) with respect to pupil dilations. The change of pupil diameter was shown in [1, 32] with three curves representing easy (black), medium (blue) and hard (red) with time (Figure 1B).

Cognitive load dynamics is considered as the change of cognitive load over time. It may manifest in one of the two forms: cognitive dissonance and cognitive overload. The cognitive psychology defines cognitive dissonance as inconsistency or psychologically uncomfortable situation [12, 13]. More specifically, cognitive dissonance states the uncomfortable feeling by holding two contradictory ideas simultaneously in working memory. For example, the differences between “how we should act” and “how we act” in a particular situation may cause dissonance. Cognitive dissonance [or lock-up] acts as a key factor mediating conceptual change in response to human-machine interactions [4]. Psychologists explain two hypothesis of cognitive dissonance: (1) The existence of dissonance [or conflict / inconsistency], being psychologically uncomfortable, will motivate the person to try to reduce the dissonance and achieve consonance [or consistency]. (2) When dissonance is present, in addition to trying to reduce it, the person will actively avoid situations and information which would likely increase the dissonance [13]. Cognitive

overload may arise in the context of a goal oriented, time bound and complex task interaction.

TABLE II. CATEGORIZATION OF COGNITIVE LOAD MEASUREMENT [29, 21]

Objectivity Causal RelationshipIndirect Direct

Subjective Self-reported invested mental effort [21, 23]

Self-reported stress level Self-reported difficulty of

materials [24] Objective Physiological measure

[25] Behavioral measure [24]

Learned outcome measure [ 22]

Brain activity measure (e.g., EEG, fMRI) [25] Dual-task performance

[27, 22]

Cognitive overload may arise in the context of a goal

oriented, time bound and complex task interaction. Complex (hard) mental multiplication task, used in [1] is an example. In the context of human-computer (device/machine/system) interaction, load can be measures with the number of ways categorized as subjective/objective or direct/indirect which is shown in Table II.

III. RESEARCH METHOD

Highly precise pupillimetry data collection depends on a good setup in which the pupil spans many pixels in the camera image. To avoid data integrity issues we analyzed a sample from a benchmark dataset [1] for secondary evaluation. Pupil size variation logs are averaged and matched with task performance to identify cognitive load, dissonance and overload. Figure 2 shows two stages of processing: cognitive load assessment and cognitive load effect assessment. This study emphasizes on the later part of the study, considering the result of the first part as a baseline. Initially, the data was passed through some pre-processing steps (e.g., averaging both left and right pupil size, management of missing values, and interpolation) to have a form of time series data. As the main goal of this work is to study dynamics in terms of overload and dissonance, we applied Hilbert transform to see cognitive load effects.

A. The Hilbert Transform Hilbert transform returns a complex sequence sometimes

called the analytic signal, from a real data sequence. It is useful in calculating instantaneous attributes of time series, especially the amplitude and frequency.

The instantaneous amplitude is the amplitude of the complex Hilbert transform; the instantaneous frequency is the time rate of change of the instantaneous phase angle[15].

Let us consider ( )tx is a real-valued time domain signal. The

Hilbert Transform of ( )tx is another real-valued time

domain signal, can be denoted by ( )tx~ , such that ( ) )(~)( txjtxtz += is an analytic signal [12].

376

Source: Hossein & Yeasin, 2014


Processing order: Gaze path


Visual attention: Heatmap


Traditionnel approach Tech3Lab approach


Attentional heatmap in during software interaction


ERPsim on SAP HANA

Now available on SAP hANA

Automated administrative tasks

Simulated market

Simulated passing of time

Business analytics

Business decisions

VIrtUAL SYSteM PArtICIPANtSerP SYSteM

1 12 23


Mobile Eye-tracking ASSeSSING AtteNtION AND BehAVIOUr IN SOFtwAre AND MeChANICAL DeVeLOPMeNt


Understanding problem solvingASSeSSING SeLeCtIVe AtteNtION IN A MULtIPLAN eNVIrONMeNt

Project Photobooth

Pierre-Majorique Léger Sylvain Sénécal Marc Fredette Francois Courtemanche

Confidential

Courtemanche, F., et al., Method and Product for Visualizing the Emotions of a User, in Provisional patent application 2015. p. p. 14.

The Problem

Conclusion


Example of industrial research financial assistance

Thank you!

sap lean ux visit to tech3lab

Education

psychologie u

copyright tech3lab

guinea ti

pierremajorique lger

ryad titah ti

jacques robert ti

dantas marketing

codirector marc fredette