EMPOWER Artificial Intelligence webinar week: by Jesus Boticario

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EMPOWERING EDUCATION BY ARTIFICIAL
INTELLIGENCE
Webinar: Wednesday 17 June 2020 (Artificial
Intelligence Education week)
Jesus G Boticario jgb@dia.uned.es

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Key questions 1st (Facts)
Background topics (PL)
Roadmap towards PL at HE

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Vicerrectorado de Digitalización e Innovación
Is this a confirmation (DTU)?

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1st things 1st
Facts:
1. HEIs have been more focused on Education rather than learning
2. Our classrooms resemble those others created back in the old days (1840? or 1300?)
alumno
Tutor
alumno
alumno
alumno
Comunidad virtual
del curso
B) Esquema de tutorización cooperativa
Student
Student Student
Student
Tutor/Professor
Learning
Communities

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Catering for differences …?
PL = Myth ??

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WHAT AI TOPICS?

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Background Topics
What has been
developed?
• ADAPT• DM
• UM• HCI-FD
10 27
2117
OSA
ISO/IEC/IMS
…
UX
CSCL
UCD AFFECT
SAERS
Personalisation needs
Big Data &
Learning Analytics

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The potential of context
• AGENTS INTERACTING
• DEVICES COMMUNICATION SUPPORT
Ambient Intelligent Systems Multimodal UM Approaches

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PL = The potential of Diverse
Functionalities
Bringing EVERYONE on board
Inclusive Education
Large-scale adaptive systems (UM + UX → FDA)
User agents
Assistive Technologies

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LMS-
EVATutor
Support
Needs
Assessment
Accessibility
support
Upload and tagging
Material
Accessibility
Support + Communication
Needs
Description
Evaluation
Material
Adaptation
Needs
Related
Guidance
Accessibility
Evaluation
& Guidance
Adaptation
Request &
Supervision
Trans-
formation
Tagging
Supervision
Feedback
Resource-Course
Feedback
Profesor
Student
Student
Personalised
resource
Librarian
Format adaptation
expert
Resource
Feedback
Resource
Feedback
UM
MR
CP
RS
Curse
Accessibility
Senior
Manager
Decision
Taking
DM
Framework
component
EU4ALL
eService
Disability
Officer
(Boticario et al., RIED, 2010; Journal of Universal Computer
Science, 2012; )
(Pascual-Nieto et al, International Joint Conference on Artificial
Intelligence, 2011)
(Santos & Boticario, Eds.. Educational Recommender Systems
and Technologies: Practices and Challenges, 2012;
Recommender Systems to Support The Dynamics of Virtual
Learning Communities; AIED 2011)
(Olga et al., 2008; UMAP, 2011; IEEE TCLT 2011; UAHCI/HCI
2013)
(Rodriguez-Ascaso et al., UAHCI/HCI 2011, DRT4ALL, 2011; 2013
Course Awards for OpenCourseWare Excellence, 2014; RIED,
2015; Expert Systems, 2015; Expert Systems, 2017)

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Courses
Accessible
Digital
Materials
(3 editions)
ICT
accessibility
in public
procurement
(3 editions)
Human-
Computer
Interaction.
Design for All
and Support
Products
(4 editions)
Mobile
phones
accessible
to everyone
(3 editions)
Accessibility
in customer
service
Accessible
housing for
all
(2 editions)
2016
Kick-off
2018
6.300+ students enrolled
900+ students completed
AA compliance with WCAG 2.1 for both edx platform and materials
All audiovisual materials have captions, Spanish Sign Language and
oral narration of visual information

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Evidence based learning: CSCL
(Anaya et al., 2013; 2016: ESWA), (Anaya & Boticario,
2013: IJAIT), (Anaya et al., 2015: EDM; CSCL), (Santos &
Boticario, 2013: AIED –Affect*), (Santos & Boticario,
2014: SCP), (Santos & Boticario, 2015: EXSY)
(Lobo etal., 2016: EXSY), (Lobo et. al., 2013: AIED; 2014:
UMAP)
ML + SNA & OLM

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Adaptive Learning Life Cycle
Still Pending ??
Design Phase
Admin Phase
Interaction Phase
Audit Phase
aLFanet, ADAPTAPlan, FAA, ALPE, EU4ALL
HCI +
UM +
LD +
PL
(Boticario, J.G. and Santos, O.C. (Journal of Interactive
Media in Education, 2007; User Modeling, 2007; Journal
of Universal Computer Science, 2008)
(Santos, O. C., & Boticario, J. G. (LNCS 4227, 2006; AIED,
2007; ICALT 2008; ICALT 2009)
(Santos et al., CAEPIA’07; UM 2007; LNCS 4556, 2007;
FLOSS, 2007)

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Text-based Recommenders in Education Cautious Approach
aLFanet, …EU4ALL…,MAMIPEC, BIG-AFF
Don’t worry
keep
trying…
(Santos, O. C., & Boticario, J. G. (ECAI, 2008; ICALT 2008;
Web Intelligence/IAT, 2008; AAAI 2008; AIED 2009; EC-
TEL 2009; RecSysTEL 2010; ICALT 2009; UMAP2009;
Algorithms MDPI, 2011; Journal of Web Based
Communities, 2012; Expert Systems, 2015, Computers &
Education 2015)
(Santos et al; LNCS 4832, 2008; ICALT, 2008; UMAP2009;
RecSysTEL 2010; AIED, 2011)

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© UNED©Vicerrectorado de Digitalización e Innovación (UNED)
Sensitive AMI
Multimodal UM
New Observable Features
RFID tracking
Movements tracking
Face tracking
Pressure tracking
Physiological
signal tracking
Sensitive AMI
Multimodal UM
New Observable Features
RFID tracking
Movements tracking
Face tracking
Pressure tracking
Physiological
signal tracking
(Salmeron-Majadas et al., UMAP, 2013; EDM, 2013;
CAEPIA, 2013; EDM 2014; UMAP 2014; Procedia
Computer Science, 2014; AIED, 2015; IEEE Access, 2018;
(Arevalillo-Herráez et al., UMAP, 2014; , UMAP, 2013;
33rd annual European Simulation and Modelling
Conference, 2019)
(Saneiro et al., The Scientific World Journal, 2014)
(Barba et al, International Journal of Distributed Sensor
Networks, 2015) (Boticario et al., UMAP, 2017)
(Cabestrero ta l., Behaviour & Information Technology,
2018) (Santos, O. C., & Boticario, J. G. LNCS 8597, 2014;
EC-TEL, 2012)(Santos et al., New Review of Hypermedia
and Multimedia, 2014; AMADL’15; IEEE Sensors, 2016)
(Gutiérrez-Restrepo et al., DSAI 2012; EDULEARN 210;
CAFVIR 2012; CE/ITMC 2017)
(Manjarrés-Riesco et al., LNCS 7899, 2013; UMAP, 2013)
(Uria-Rivas et al, Sensors, 2019)

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UNED Roadmap towards personalised
learning
1. Ethical and social issues
2. Data gathering
3. Data analysis
4. Evidence based-interventions
5. Putting in place predictive models

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Vicerrectorado de Digitalización e Innovación
1st step: Framework for the ethical use of
data

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Experts’ feedback
Building on found answers (OOFHEC / ICDE 2019)

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Thank you
Muchas gracias