past, present and research challenge in adaptive user interfaces

Past, Present and ResearchChallenges in Adaptive User

Interfaces

Eduardo Castillejo, PhD. student

DeustoTech - Deusto Institute of Technology, University of Deustohttp://www.morelab.deusto.es

December 9, 2013

http://www.morelab.deusto.es

Outline

Introduction

User Interfaces

Personal research

Contributions

Evaluation

Conclusions

Questions And Feedback

Outline

IntroductionUniversity of Deusto

User Interfaces

Personal research

Contributions

Evaluation

Conclusions


University of Deusto - Bilbao Campus

Past, Present and Research Challenges in Adaptive User InterfacesIntroduction 4 / 99

University of Deusto

I 997 staffI > 12 K students (15% international)I 125 anniversary in 2012I 2 campus: Bilbao & San Sebastian


DeustoTech - Deusto Institute of Technology

I Associated to Faculty ofEngineering, it belongs toFundacion Deusto

I 150 people divided in 7 researchunits

I RepresentingDeustoTech-INTERNET, a.k.a.MORElab – envisioning futureInternet research group

I http://www.morelab.deusto.es



DeustoTech-INTERNET

I Motto: “User-centred Intelligent Services for Anything,Anywhere at Anytime”

I Areas of research:I Context-aware Mobile Computing for Enhanced

User-Environment InteractionI Semantic Middleware for Embedded Wirelessly-connected

DevicesI Smart Environments of Augmented Internet-connected

ObjectsI Ambient Assisted Living (AAL): adaptive accessible interfaces

and social roboticsI Future Internet: Internet of Services, Internet/Web of Things

and Web of Data


DeustoTech-INTERNET Unit

I Principal researcher:I Diego Lopez-de-Ipina,

http://paginaspersonales.deusto.es/dipina/

I It comprises:I 4 lecturers

I 4 PostDoc

I 6 full-time researchers

I 7 PhD grant holders

I 3 MSc grant holders

I 24 people


http://paginaspersonales.deusto.es/dipina/

DeustoTech-INTERNET Performance

I Scientific:I 2012: 66 publications

I 8 JCRs, 12 book chapters, 33 indexed conferences, 13 otherpublications

I 2011: 48 publicationsI 8 JCRs, 13 book chapters, 3 indexed conferences, 24 other

publications


Active projects

I European projects:1. Go-Lab: Global Online Science Labs for Inquiry Learning at

School (FP7-ICT-2011-8, Nr. 317601, IP project)2. IES CITIES: Internet-Enabled Services for the Cities across

Europe, FP7, Comision Europea, CIP-ICT-PSP-2012-6, PilotType B - CIP-ICT-PSP-P

3. SONOPA: SOcial Networks for Older adults to Promote anActive life (AAL-2012-5-187 and AAL-010000-2013-13), AALcall 5.


Active projects

I Spanish projects (mostly applied research):1. THOFU: Future Hotel Technologies, CENIT 2010, Spanish

IP-like project2. ADAPTA. Adapting, validating and integrating open data for

governments and companies, IPT-2011-0949-4300003. Social Awareness Based Emergency Situation Solver.

SABESS, IPT-2011-1052-3900004. Migration towards the Cloud - mCLOUD,

IPT-2011-1558-4300005. TALIS+ENGINE: Hybrid Cooperative and Semantic Reasoning

for Service Orchestration in Assistive Environments(TIN2010-20510-C04-03), Basic Research project


Active projects

I Basque projects (mostly basic research):1. DYNUI: Capability and Context-aware Dynamic Adaptation of

User Interfaces for Ambient Assisted Living (PC2012-73A)2. UCADAMI: User and Context-aware Dynamically Adaptable

Mobile Interfaces (S-PE12FD006)3. SmarTUR: Tourism in Smart Intelligent Environments4. DEUSTEK3: Research group recognized by the Basque

University system (IT745-13)5. . . . upto 8


What we actually do?

I Remote Labs & Internet-connected Objects:I GO-LAB – federation of remote labs to enable

cross-organization remote experimentsI WebLab-Deusto – open platform to ease the deployment of

remote labsI Enabling Smart Assistive Environments:

I THOFU – creating the ICT infrastructure for next generationhotels and tourism including smart objects and sentimentanalysis

I SONOPA – activity-aware social networks to promote socialinteraction among elderlies

I TALIS+ENGINE – fostering personal autonomy by ambiguouscontext modeling, reasoning and services coordinationthrough triple spaces

I DYNUI – user interfaces adaptable to user context, capabilitiesand devices



I Social Data Mining & Opinion Mining:I SABESS – extracting structured knowledge about

emergencies from social networksI THOFU – analysing information about hotel reviews to perform

sentiment analysisI Linked Data & Linked Data Apps:

I IES CITIES – urban app ecosystems based on council andgovernment open data where users prosume data

I ADAPTA – enabling a holistic LinkedData platform to adapt,validate and exploit open data (dataset recommendation)

I SmarTUR – tourism related LinkedData Apps (LinkedQR)



I Semantic Embedded Middleware:I TALIS+ENGINE – coordination of distributed embedded

objects through Triple SpacesI Sustainable IoT – persuasive interfaces and cooperation

among smart connected objects to foster sustainabilityI Cloud Computing:

I mCLOUD – migration of enterprise applications to the CloudI Mobile Computing for Enhanced User-Environment

Interaction:I Q-Apps - Quality-in-use assessment framework for mobile

appsI KONTATU - Context-Aware Communication Means

RecommendationI LaguNFC - Enabling access to the digital world to the elderly



I More info about our projects:I Projects page:

http://www.morelab.deusto.esI Semantic searcher and RDF descriptions



Sentiment analysis: Hotel review analysis

I THOFU projectI Localization data fusionI Reality Mining from user data


Social trends analysis

I Imhotep projectI What do we consider a “big” screen for a mobile phone?I Would a Japan individual consider the same screen “big”?


Web of Data: Waste-related LinkedStats

I http://helheim.deusto.es/linkedstats/


http://helheim.deusto.es/linkedstats/

SABESS: Social Data Mining for EmergencyDetection

I Data gathered from social networksI NLPI Alarms triggering


Federating Labs for Remote Experimentationusing the Web

http://www.weblab.deusto.es

Scalable, web-based and experiment-agnostic remotelaboratory management system:

https://github.com/weblabdeusto/weblabdeusto/Past, Present and Research Challenges in Adaptive User InterfacesIntroduction 21 / 99

http://www.weblab.deusto.es

https://github.com/weblabdeusto/weblabdeusto/

Social Coffee

https://twitter.com/Social_Coffee


https://twitter.com/Social_Coffee

Collaborative Eco-aware Everyday Things


Persuasive Eco-aware Everyday Things


PhDs defended in the group

I “CONCERT: A new framework for contextual computing intourism to support human mobility”, by Carlos Lamsfus,supervised by Diego Lopez-de-Ipina y Aurkene Alzua,29/10/2010

I “Middleware Framework for the Configuration andPersonalisation of Ubiquitous Environments by the FinalUser” by Aitor Uribarren, supervised by Diego Lopez-de-Ipinaand Rosa Iglesias, 01/07/2011

I “The web as a suitable execution platform to preciselyrepresent audio-visual contents and registering userinteraction” by Pablo Garaizar, supervised by Dr. DiegoLopez-de-Ipina y Dr. Miguel Angel Vadillo, 29/04/2013

I “New protocols for the discovery and automatic compositionof services in ad hoc mobile networks”, by Unai Aguilera,supervised by Dr. Diego Lopez-de-Ipina, 3/05/2013


PhDs defended in the group

I “Transitive and Scalable Federation Model for RemoteLaboratories” by Pablo Orduna Fernandez, supervised by Dr.Javier Garcıa Zubia, 31/05/2013

I “Plataforma web y metodologıa para el desarrollo desistemas sensibles al contexto basada en la colaboracionentre programadores y expertos en el dominio” by DavidMartın del Canto, supervised by Dr. Diego Lopez-de-Ipina yDra. Aurkene Alzua, 7/6/2013

I “Towards more Reliable and Efficient IntelligentEnvironments: Uncertainty, Vagueness and ReasoningDistribution” by Aitor Almeida Escondrillas, supervised by Dr.Diego Lopez-de-Ipina, 10/06/2013


Some selected publicationsI User-Aware Location Management of Prosumed

Micro-services. Bernhard Klein, Diego Lopez-de-Ipina,Christian Guggenmos and Jorge Perez. Interacting withComputers, ACCEPTED, in press, ISSN:0953-5438, JCRImpact Factor (2012): 1.158, Q2(COMPUTER SCIENCE,CYBERNETICS), ranked 10/21, OXFORD UNIV PRESS

I Towards federated interoperable bridges for sharingeducational remote laboratories. Pablo Orduna, Philip HBailey, Kimberly DeLong, Diego Lopez-de-Ipina, JavierGarcia-Zubia. Computers in Human Behavior (Journal),http://dx.doi.org/10.1016/j.chb.2013.04.029, ISSN 0747-5632,JCR Impact Factor (2011): 2.293, Q1(PSYCHOLOGY,MULTIDISCIPLINARY), ranked 22/125,PERGAMON-ELSEVIER SCIENCE LTD, March 2013.

I Software Engineering Aspects of Ubiquitous Computing andAmbient Intelligence. Diego Lopez-de-Ipina, Sergio F. Ochoaand Jose Bravo. Science of Computer Programming,http://dx.doi.org/10.1016/j.scico.2013.03.001, ISSN0167-6423, JCR Impact Factor (2011): 0.622,Q3(COMPUTER SCIENCE, SOFTWAREENGINEERINGATION), ranked 70/104, ELSEVIERSCIENCE BV, March 2013.

I RFID breadcrumbs for enhanced care data management anddissemination. Jose Bravo, Diego Lopez-de-Ipina and RamonHervas. Personal and Ubiquitous Computing, JCR ImpactFactor (2011): 0.938, Q2(COMPUTER SCIENCE,INFORMATION SYSTEMS), ranked 66/133.http://dx.doi.org/10.1007/s00779-012-0557-73. May 2012.


Some selected publications

I Assessing Ambiguity of Context Data in IntelligentEnvironments: Towards a More Reliable Context ManagingSystem, Aitor Almeida and Diego Lopez-de-Ipina, Sensors(Journal). Volume 12, Issue 4, pp 4934-4951. MDPI. JCRImpact Factor (2011): 1.739,Q1(INSTRUMENTS&INSTRUMENTATION), ranked 14/58.http://dx.doi.org/10.3390/s120404934. April 2012

I Imhotep: an approach to user and device conscious mobileapplications, Aitor Almeida, Pablo Orduna, EduardoCastillejo, Diego Lopez-de-Ipina, Marcos Sacristan, Personaland Ubiquitous Computing (Journal). Springer. Vol. 15, no.4.pp.419-429. JCR Impact Factor (2011): 0.938,Q2(COMPUTER SCIENCE, INFORMATION SYSTEMS),ranked 66/133. ISSN: 1617-4909.http://dx.doi.org/10.1007/s00779-010-0359-8. January 2011


Some selected publicationsI For more details look at:

I http://paginaspersonales.deusto.es/dipina/

publications.htmlI http://www.morelab.deusto.es/labman/publications/


http://paginaspersonales.deusto.es/dipina/publications.html

http://paginaspersonales.deusto.es/dipina/publications.html

http://www.morelab.deusto.es/labman/publications/

Other achievements

I 1 spin-off came up from the research group,http://www.symplio.com/

I Open source contributions:I Imhotep framework (Apache license):

http://www.morelab.deusto.es/imhotep/I WebLabDeusto – https://www.weblab.deusto.es/web/I Otsopack – http://code.google.com/p/otsopack/I Zxing – databar – http://code.google.com/p/zxing/

(Barcode Scanner - Android)I Open dataset released in CKAN about MORElab’s people,

projects and publications:I http://ckan.linkeddata.es/dataset/morelabI Our datasets are scheduled to appear in next

http://lod-cloud.net/I MORElab researcher Pablo Orduna was awarded MIT TR35

SPAIN in 2012


http://www.symplio.com/

http://www.morelab.deusto.es/imhotep/

https://www.weblab.deusto.es/web/

http://code.google.com/p/otsopack/

http://code.google.com/p/zxing/

http://ckan.linkeddata.es/dataset/morelab

Activities Organized @ MORElab

I Open Hack Day 2013:I http://dev.morelab.deusto.es/hackathon/index.php/P%

C3%A1gina_principal#Resultados

I Random Hacks for Kindness @BilbaoI http:

//www.morelab.deusto.es/index.php/news-287822021/

past-news/405-random-hacks-for-kindness-bilbao

I AppCircus in BilbaoI http://appcircus.com/event/appcircus-en-bilbao

I Apps4BetterWorldI http://www.morelab.deusto.es/concurso/index.html


http://dev.morelab.deusto.es/hackathon/index.php/P%C3%A1gina_principal#Resultados

http://dev.morelab.deusto.es/hackathon/index.php/P%C3%A1gina_principal#Resultados

http://www.morelab.deusto.es/index.php/news-287822021/past-news/405-random-hacks-for-kindness-bilbao



http://appcircus.com/event/appcircus-en-bilbao

http://www.morelab.deusto.es/concurso/index.html

MORElab’s website




Outline

Introduction

User InterfacesUIs, GUIs, AUIs and more

Personal research

Contributions

Evaluation

Conclusions


UIs, GUIs, AUIs and more

I User Interfaces is the space where interaction betweenhumans and machines occurs.

I The goal of this interaction is effective operation and controlof the machine on the user’s end, and feedback from themachine.

Past, Present and Research Challenges in Adaptive User InterfacesUser Interfaces 34 / 99


I Evolution:



I Graphical User Interfaces are a type of user interface thatallows users to interact with electronic devices throughgraphical icons and visual indicators

I The actions in GUI are usually performed through directmanipulation of the graphical elements.



I Adaptive User Interfaces are a type of user interface thatchange their layout and elements to the needs of the useror context and is similarly alterable by each user.

I Examples.I PC web browsing Vs. mobile (content adaptation)I Accessibility tools for mobile devicesI SW tools menus personalizationI . . .

I Adaptive Vs. Adaptable.I Adaptable: Android brightness control, Office menus, etc.I No context-aware...



I It is becoming more and more difficult to distinguish betweenuser interfaces, graphical and adaptive user interfaces

I Technology and interaction boundaries allow researches toseek for alternatives

I For example:



I Beyond – Collapsible Input Device for Direct 3D Manipulationbeyond the Screen

http://vimeo.com/11015834




I Samsung Galaxy Note 3 display adaptability



I Mobile physical adaptive display (fake)



I inFORM - Interacting With a Dynamic Shape Display




Outline

Introduction

User Interfaces

Personal researchAdaptive User InterfacesFrom the Imhotep framework. . .. . . To New Research ChallengesAddressed Research Areas

Contributions

Evaluation

Conclusions


Adaptive User Interfaces (I)

I Each user has his own preferences.I Moreover, there are some groups of users who have special

needs and capabilities: people with disabilities and theelderly.

I Furthermore, people with the same disability do not react inthe same way.

Past, Present and Research Challenges in Adaptive User InterfacesPersonal research 44 / 99

Adaptive User Interfaces (II)

I One of the main objectives of Adaptive User Interfaces is toreduce the interaction problems that these groups suffer.

I In Europe the share of people aged 65 represent a 17% ofthe current population. By the year 2060 this figure isprojected to rise to 30% 1.

I In fact, the European Commission states, “the EU wouldmove from having four people of working-age to each personaged over 65 years to about two people of working-age”

1http://ec.europa.eu/economy finance/articles/structural reforms/2012-05-15 ageing report en.htm


Adaptive User Interfaces (III)

I Limitations:I Adaptive systems solutions are very domain dependent.

I Airport scenarios for recommending services (users anddevices are modeled), smart homes for controlling and shareinformation between devices (again, users and devices),desktop to mobile web content adaptation (user’spreferences). . .

I But it is true that sometimes it is inevitable. . . (e.g., medicalenvironments).

I This means: similar entities considered but using differentmodels, techniques, approaches. . .


Adaptive User Interfaces (IV)

Limitations:I Unrelated models (users, context, devices. . . ).

I They usually are considered like independent entities. But. . .I Context might affect user’s capabilities.I Devices can bother the user.

I There is no standardization for designing these systems.I Not for the models.I Not for the methodology.I Only for several quality and usability goals (ISO 9126-I, ISO

9241-II. . . ).


Adaptive User Interfaces (V)

I Limitations:I External server dependency.I Static information about the user or the device.I . . .I In fact, there are several accessibility tools in mobile devices

(Android, iPhone. . . )I The problem is that they are not adaptative. They are

adaptable.I It requires the user intervention for configuring the model2.

I They do not evolve through time. They are static.I No learning.

2Heckmann, D., 2005. Ubiquitous user modeling. IOS Press.Past, Present and Research Challenges in Adaptive User InterfacesPersonal research 48 / 99

The Imhotep Framework (I)

I Imhotep3 is a framework that tries to ease the development ofaccessible and adaptable user interfaces taking intoaccount both the user capabilities and the devicecharacteristics.

I Preprocessor directives within the application’s source codeevaluated in the server.

I User’s disability (e.g., blindness) is configured in aconfiguration mobile application.

I The configured profile is sent to the server, which compiles theapplication’s source code taking into account the received userprofile and the defined preprocessor directives.

I Once the binaries have been generated by the server, theadapted application is sent back to the user’s device.

3Almeida, A., Orduna, P., Castillejo, E., Lopez-de-Ipina, D., Sacristan, M.,2011. Imhotep: an approach to user and device conscious mobile applications.Personal and Ubiquitous Computing 15, 419–429.


The Imhotep Framework (II)

I Imhotep:

I Preprocessor directives:


Example: AssistedCity

a) Adapted user interface for a tour-guide applicationfor a blind user configuration profile. The interactionchannel is mainly conducted by voice commandsand text-to-speech.

b) Default tour-guide application, where the interactionchannel is mostly visual.


The Imhotep Framework (III)

I Imhotep main limitations:I Static.I External server dependency.I Pre-known and static user and device capabilities.I Unreal user capabilities:

I What (sight) graduation is the maximum for justifying a userinterface change? 30%? 40%?

I We are no doctors. . .

I No context-awareness.I New challengesI http://www.morelab.deusto.es/imhotep/


http://www.morelab.deusto.es/imhotep/

User’s Context Disabilities

I There are several groups of people who suffer from severaldisabilities: people with disabilities and elder people.

I These people have conditions which make difficult to carryout diary tasks.

I But the truth is that all of us suffer from certain disabilitiesduring the day. . .

I When sunlight reflects on a glossy screen (e.g., oursmartphones’ screen) our sight capability is reduced.

I When we try to call a friend in a concert, in the subway, in acrowded street. . . our hearing capability is “harmed”.

I User’s context disability depends on how context mightaffect user’s capabilities when several tasks are being carriedout.


User’s Context Disabilities

I Example:


Research Objectives (I)

I Now, regarding all these problems, what is my researchabout?

To reduce the users’ context disabilities through adynamic methodology which employs several dynamicmodels and considers users’ configured capabilities,the set of characteristics which defines the currentenvironment where users actually are and the actualdevices they use by adapting mobile applications’ userinterfaces to the current situation.


Research Objectives (II)

Main goals:1. To design a methodology where users, context and devices

evolve because of the context variability.2. To model this evolution through a process which will be able

to dynamically adapt the best and most suitable user interfacefor each precise context situation.

3. To validate the results by capturing the interaction betweenthe user and the adapted user interface.

4. To demonstrate that it is possible to develop dynamicadaptive applications which are able to reduce users’disabilities taking into account their own characteristics, thedevices’ ones and those which belong to the current context.


Areas of research

I This research tackles the following areas:I Context-awarenessI Human-Computer InteractionI Adaptive user interfacesI Inclusive designI Considerate computing


Outline

Introduction

User Interfaces

Personal research

ContributionsInterdependencesModelsAdaptation Process

Evaluation

Conclusions


Interdependences (I)

I An analysis of thecontext/user anddevice/user influence.

I For example, whichcontext parametersaffect users’capabilities.

Past, Present and Research Challenges in Adaptive User InterfacesContributions 60 / 99

Interdependences (II)I An influence association between entities (user, context,

device) and the final adaptation of each UI component.

DEVICE CONTEXT USER

US_VOLUMECTX_TEMPERATUREDV_CONTRAST US_BRIGHTNESS US_VIEW_SIZEUS_CONTRAST US_TEXT_COLOR DV_VIEW_COLORDV_VIEW_SIZEUS_TEXT_SIZE DV_VOLUMEDV_TEXT_SIZEUS_VIEW_COLOR

BRIGHTNESS CONTRAST VIEW_SIZE VIEW_COLOR TEXT_SIZE TEXT_COLOR VOLUME

INPUT

OUTPUT

INPUT OUTPUT

US_INPUTCTX_LUMINOSITY CTX_NOISEDV_BRIGHTNESS DV_INPUTDV_TEXT_COLORUS_OUTPUT DV_BATTERY DV_ORIENTATIONDV_OUTPUT DV_ACCELERATION


Models

I A user, context and device model which is:I Domain independent. It gathers most of the most significant

models in the literature.I HCI, Smart Environments, Ubiquitous Computing. . .

I Physical/medical user’s disabilities independent.I The user “configures” his/her capabilities.

I A usability model (based on usability metrics) which allowsto analyze the interaction between the user and the adapteduser interface (this model will be necessary for theevaluation).

I Collect user dataI Extra: A Java (Android) library for developers to ease the

design of dynamic adaptive user interfaces.


Literature Context Models (I)


Context Model (II)

I Proposed model:


Context Model (III)

I Divided into two main groups:I Primary:

Physical context : Environment information from sensors(e.g., temperature, absolute location, time. . . ).

High-level context : Physical richen information (e.g., “it’scold”, “office”, “morning”. . . ).


Context Model (IV-a)

I Secondary:Environment metadata : Environment knowledge is

associated to sensors. A sensor can provideinformation about the temperature (23oC). Butthis information by itself is poor in acontext-aware system. Environment metadatacan describe and enrich this knowledge,providing time and location data. For example,“the current temperature at 12:00 AM in Bilbao is13oC”.. . .


Context Model (IV-b)

I Secondary:Virtual environment : Combining the knowledge of the

categories above it is possible to extracthigh-level information. For example, if a sensorshows that there is a light turned on at office, wecan deduce that there are people working. Thisway, we avoid the usage of other sensors toindicate this activity.. . .

“Stressful conditions” : ???


Context Model (V)

Stressful conditions :I We need something more to characterize the

current situation that involves user, its currentcontext and the device.

I Incongruent adaptations: defined by severalenvironment parameters that induce the platformto perform a certain adaptation for the currentconditions. However, the result of thisadaptation, although it can be linearly alignedwith the context characteristics, can beincongruent.


Context Model (VI)

Stressful conditions :I Activities help to understand the current user,

context and device situation.I Activities enrich the environment information.

Manipulating with hands or being at a certainlocation (like a library, where people are insilence) are aspects that we should considerwhen we model context. For example, driving orcooking restrict user capabilities momentarily.This way, we can state that these activitiesimpede the user.


Context Model (VII)

I Several groups of activities that should be considered:I Activities that limit the use of the hands.I Activities that limit the use of the voice.I Activities that limit the user’s sight capability.I Activities that limit the user’s hearing capability.I Activities that limit the user’s mobility? (not sure)I Activities that limit the user attention.I Combinations of these activities.


Literature user models


User model (I)

I Proposed model:I Modeling users’ concrete disabilities is troublesome (we are

no doctors) 4.I Instead of this, it is possible to let the users to “configure” their

disabilities.

4Casas, R., Blasco Marın, R., Robinet, A., Delgado, A., Yarza, A., Mcginn, J.,Picking, R., Grout, V., 2008. User modelling in ambient intelligence for elderlyand disabled people. Computers Helping People with Special Needs 114–122.


User model (II)


User model (III)

I The model is categorized as follows:Interface : which models the I/O “preferences” (e.g., if the

user is blind or has any sight problem, he/shewould like to interact with gestures, voice control,etc.).

Display : for taking care about the orientation,brightness, colors (color blindness). . .

Audio : volume, language. . .View : it configures each View or Control displayed in

the device’s screen (i.e., a Label, EditText,ComboBox. . . ).

Others : which gathers several extra interactionfeatures.

I Minimum UI


Device Model (I)

I Proposed model:


Device Model (II)

I It models several dynamic capabilities (“Status”).I These capabilities should be taken into account when facing

any adaptation process (e.g., current brightness could beenough to avoid an adaptation, current battery levels mightadvise against new processing activities. . . )


Models’ granularity (I)

“The performance of a model depends critically on thegranularity, for example the choice of precision of theparameters. Too high precision generally involves modeling ofaccidental noise and too low precision may lead to confusionof models that should be distinguished” 5

5Gao, Q., Li, M., Vitanyi, P., 2000. Applying MDL to learn best modelgranularity. Artificial Intelligence 121, 1–29.


Models’ granularity (II)

How do I tackle this?I Each modeled entity is considered separately:

I Context:I Different levels (low-level parameters from sensors Vs.

high-level information)I “Activities” (stressful conditions) are not considered as a list of

specific activities (instead of “cooking” we consider an activitythat impedes the use of the hands and distracts user attention)

I User:I Capabilities are not “medical-based”, they are configured

I Device:I As Context, several “physical” data is required

(battery levels, screen orientation, available memory. . . )


User’s model granularity


Context’s model granularity


Device’s model granularity


Modeling technique

I The power of the mark-up languageI The power of semanticsI So. . . Ontologies Vs. XML

I The problem with ontologies is to find those that already modelthose parameters that I’m interested in (e.g., the temperature,luminosity, etc.)


Usability (I)

I A usability model is proposed to collect the user interactiondata with the adapted user interface.

I This model is based on several “quality of use” metricsfocused on usability:

I Task effectiveness.I Task completion.I Error frequency.I Task time:

I Time to start the task.I Time to finish the task.

I Satisfactory clicks.I Error clicks.I . . .

I ISO/IEC 9126-4.


Usability (II)

I The idea is to get a % of the compatibility between the userand the adapted user interface.

I The user is his own “expert”.I This way the platform learns from the interaction refining the

UI results.


Usability (III)

I The % of the compatibility is calculated comparing a bestsituation scenario with the adapted user interface.

I The best scenario is the one on which the user can perfectlyinteract and perform the desired task.

I To “capture” this scenario a mobile user interface configuratorhas been developed.

I The idea is to compare the usability metrics between theperfect and the adapted user interfaces.


Usability (IV)

The user-interaction “configurator”:

I https://github.com/edlectrico/dynamic-capability-tester


https://github.com/edlectrico/dynamic-capability-tester

Adaptation Process (I)

Dynamic process:


Adaptation Process (II)

Context Manager : It gathers data from the environment.User Capabilities Reasoner : It “mixes” context and user’s

capabilities (user’s context capabilities) to generatean updated user capabilities profile using thecontext-user influence taxonomy.

UI Reasoner : With the updated user capabilities and the device’sones it search for the best user interface for thecurrent situation. It searches in a repository forprevious similar configurations to avoid unnecessaryadaptations. It uses several rules to recommend thebest configuration.

UI Adaptation Engine : It is a dynamic Android module whichperforms on-the-fly user interface adaptations.


Adaptation Process (III)I Historical adaptation.I Standard UI.


Outline

Introduction

User Interfaces

Personal research

Contributions

Evaluation

Conclusions


Evaluation (I)

I Of the model:I Scenarios definition.

I Not adapted Vs. adapted user interfaces.I Android accessibility user interface Vs. adapted user interfaces.I . . .

I State of the art models comparison. the resulting UIs.I Of the generated/adapted UI: Through the interaction model

(Best case Vs. Adapted case)I Usability models.

Past, Present and Research Challenges in Adaptive User InterfacesEvaluation 91 / 99

Evaluation (II)

I Spanish Blind Organization:

I Basque Deaf Organization:

Past, Present and Research Challenges in Adaptive User InterfacesEvaluation 92 / 99

Outline

Introduction

User Interfaces

Personal research

Contributions

Evaluation

Conclusions


Contributions status (I)

I Objective: To reduce user’s context disabilities by using anadaptive user interface dynamic process.

I Contributions:1. An analysis of the context/user and device/user influence.

Status : First version.2. An interdependency table that shows how each entity (user,

context, device) affects the final adaptation.Status : First version.

3. A user, context and device dynamic model for adaptive userinterface domains.

Status : First XML versions. Integrated with the Androidprocess.

Past, Present and Research Challenges in Adaptive User InterfacesConclusions 94 / 99

Contributions status (II)

I A usability matrix (based on usability metrics) which allowsto analyze the interaction between the user and the adapteduser interface.

Status : Not started. First: analyze whichusability/productivity metrics are needed (ISO9126-4).

I A dynamic process which using these models andinterdependencies allows developers to design adaptiveapplications.

Status : A first operative Android version (next slide).I The evaluation scenarios definition.

Status : Not started yet. . .


Contributions status (III)

Updated methodology:


Outline

Introduction

User Interfaces

Personal research

Contributions

Evaluation

Conclusions



I . . . ?

Past, Present and Research Challenges in Adaptive User InterfacesQuestions And Feedback 98 / 99

past, present and research challenge in adaptive user interfaces

Technology

research challenges

user context

applied research

research units

areas of research

adaptive accessible

basic research projectpast

internet of services