Education and Artificial intelligence

Future education and Artificial
Intelligence (AI)
Dr.C. Febe Angel Ciudad Ricardo, P.T.
https://fciudad.wordpress.com
https://es.slideshare.net/fciudad
University of Holguín “Oscar Lucero Moya”, November 19th
, 2018.

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Education challenges in
the digital age
● Promote a fair and knowledge-based society.
● Strengh the national identities in a globalized
world.
● Promote the life-long learning.
● Enhance the school-society relationship to
satisfy the social needs.
● Training from the work places and/or live
places.
● Use the social dymanic tools in the
educational dynamic.
● Equally available for everyone (open).
● Accesible and global (ubiquitous).
Education for the future
Artificial Intelligence for
education
Conclusions

Trainers challenges in the
digital age
● Move from a knowledge owner approach to a
knowledge self-search and learn guide
approach.
● Have virtual identity & presence in addition to
the face-to-face homologues.
● Have skills for ICT-based work and education.
● Use of collective work and distance-based
educational methods.
● Train for a life-long learning.
● Be available and accessible with limited
space-time restrictions.
● Produce, re-use and share educational
resources.
education
Conclusions

Are the
education and
trainers ready to
face those
challenges?
education
Conclusions

What is
the Cuban
current
situation?
education
Conclusions

Main attributes for Cuban
education
● Goverment support.
● National system.
● Initial ICT usages.
● Sistematized
phycological
foundations.
● Quality population
trust.
● Safe environments.
Strengths
● Face to face
processes.
● Printed text
supported.
● Close environments.
● Rational-based
learning processes.
LimitationsEducation for the future
education
Conclusions

Practical contradiction
Face to face-based
educational dynamic
with a diffusive use
of ICT and a rational
teaching approach
by the staff
and programmes.
Social dynamic
of the students
(and staff) enhanced
(or supported)
by ICT for a
self-directed learning
and a collaborative
and inter-disciplinary
approach for
problem solution.
education
Conclusions

What is “education”?
EDUCATION
Activity Communication
Personality Human development
Languages Codes
education
Conclusions

Human communication
ORAL: sounds
code.
(understand,
speak)
WRITTEN: graphic
symbols code.
(read, write)
VIRTUAL: digital code.
(surf, interact, collaborate)
education
Conclusions

Cuban university
HORRUITINER, P. La universidad cubana: el modelo de
formación. La Habana: Félix Varela, 2006.
UNIVERSITY
Scientific
Humanistic
Technological
education
Conclusions

Educational contextEducational context
University in the
digital era
education
Conclusions
University
Scientific
Technological
Digital presence
& Identity
HumanisticInterconnected
Society
Globalcontext

Personal Learning
Environment (PLE)
«System of virtual spaces supported in a
technological and interconnected services
scenario, that constitutes an educational context
with a non formal structure and determined by
the needs and interests of the person who build
it, to promote her/his communication and
collective work synchronous and asynchronous;
as well as her/his virtual presence and identity»
(p. 24)
CIUDAD, F. Diseño de entornos virtuales para la integración academia-
industria. Implementación en la Disciplina Ingeniería y Gestión de Software.
Saarbrücken, Alemania: Publicia, 2016. ISBN: 978-3-8416-8050-1
education
Conclusions

Facebook
Twiter
Android
tools
CD & DVD
contents
Distance Learning
Tools
Web Pages & Personal
Blogs
E-mail
Digital
animations
Digital
videos
Links to other
Internet
locations
Academic
Google
Professional
Tools
education
Conclusions

Virtual Learning
Environment
«System of virtual spaces with a technological
and interconnected services scenario, that
constitutes an educational context with a formal
structure and determined by didactic
foundations and principles, and its managed and
evolve technically and pedagogically; as well as
through a didactic strategy and system, promote
the communication and collective work
synchronous and asynchronous, among the
participants» (p. 16)
education
Conclusions

Virtual Learning
Environment
VLE in the educational context
VLE as an educational context
determine transform
education
Conclusions

VLE in the educational
context
education
Conclusions
Learning
demands
Social
demands
Diagnostic of
knowledge and
motivations of
the staff
Diagnostic of
knowledge and
motivations of the
students
Fundations and
principles of the
didactical design

VLE as an educational
context
education
Conclusions
VLE in the educational context
VLE as an educational context
Semantic
Practical
Technological
Management
Spatial
Personal
Transform

Learning Technological
Ecosystem (LTE)
«Technologies, applications and informatics
services self-regulated system, that makes
possible to a professional community in a socio-
historical concrete context, develops all its
processes automatically and with
interoperability, for being associated and to be
able to collaborate with alike professional
organizations with the goal to obtain a scientific
development of mutual benefit and having in
front of such a scientific community a common
virtual presence and identity» (p. 22)
education
Conclusions

education
Conclusions
Ecosystem
Content
manage-
ment Synchronic
commu-
nication
Asynchronic
commu-
nication
Evaluation
and
learning
trace
Professional
organi-
zation
Informa-
tiono
manage-
ment
Institutional
Repository
Virtual
Library
Library
Manage-
ment
Ontologies
Distance
Learning
Tools

Inter-collaborative
Level
Collaborative
Level
PLE – VLE – LTE
PLE
VLE
LTE
Diffusion Level
education
Conclusions

f(uture)-university
«Institution of higher education that manage a
group of communications and exchange of
scientific-technological information from a
networked infrastructure supported by Internet,
to favourably transform and develop the society
and its members through the use of ICT and its
digital presence and identity as organization»
CIUDAD, F. Transformación 7: Acciones metodológicas y administrativo-
normativas para modificar los modos de pensar y hacer la enseñanza, 2018.
education
Conclusions

How an
institution can
become a
f-university?
education
Conclusions

Model A-D-O-M-U
education
Conclusions
CIUDAD, F. Transformación 7: Acciones metodológicas y administrativo-
normativas para modificar los modos de pensar y hacer la enseñanza, 2018.
A-ccessible (a-university)
D-ispensable (d-university)
O-pen (o-university)
M-obile (m-university)
U-biquitous (u-university)

Model A-D-O-M-U
education
Conclusions
U-bicuos (u-university)
Network of institutional web pages
with an informative purpose but
not for interaction with the cybernauts.

Model A-D-O-M-U
education
Conclusions
U-bicuos (u-university)
Network of institutional web pages
from where the cybernauts can download
any part or resource of the
content (diffusion).

Model A-D-O-M-U
education
Conclusions
 System of informatics tools
supported on Internet and
the ICT.
 Accessible from anywhere
through a wired connection
inside the campus.
 Support all the institutional
processes.
 Interconnect all the nodes
in the organization.
 Connect the organization
with the national government
and the society.
 Learn with the data from
inside the campus.

Model A-D-O-M-U
education
Conclusions
 System of informatics tools supported on Internet, and the
mobile technology.
 Accessible from anywhere (fix and/or mobile devices) inside
the campus.
 Support all the institutional processes.
 Interconnect all the nodes in the organization.
 Interconnect the organization with the national government and
society.
 Learn with the data of the national government and the society.

Model A-D-O-M-U
education
Conclusions
 System of informatics tools supported on the cloud.
 Accessible from anywhere (fix and/or mobile devices) inside
and outside the campus.
 Support all the institutional processes.
 Interconnect all the nodes in the organization.
 Interconnect the organization with the national government
and the international society.
 Learn with the data of the national government and the
international society.

Can Artificial
Intelligence (AI)
enhance the
f-university
approach?
education
Conclusions

Artificial Intelligence
«[…] branch of the Computer Science devoted to the
creation of hardware and software to imitate the
human thinking […] that takes care about the
representation, acquisition and process of
knowledge in an computerized way […] as well as
the computational modelling of the cognitive
processes, as well as the perception, the
comprehension, and the synthesis of natural
language, the smart robotic, reasoning modelling,
automatic programming and others, all of them non
numeric and inside the heuristic domain» (p.9)
BELLO, R. Curso introductorio a la Inteligencia Artificial, 1996.
Santa Clara: CEIS-UCLV.
education
Conclusions

What can be done
with AI?
education
Conclusions

What can be done
with AI?
education
Conclusions
- Learning data mining.
- Learning pattern recognition.
- Adaptive learning.
- Learning case-based discovery.
- Natural language processing.
- Behavioural language processing.
- Learning prediction.
- Learning analytics.

Improve the f-university
education
Conclusions
AI
VLE
LTE
PLE
Learning data
mining
Adaptive
learning
Learning pattern
recognition
Natural language
processing
Behavioural language
processing
Learning
analytics
Learning
prediction
Learning case-base
discovery

Possible further work
education
Conclusions
- Learning data mining.
- Learning pattern recognition.
● Harvest data from PLE, VLE & LTE to know
how students develop themselves.
● Behavioural-based analysis to know the
speed and deepness of students learning.
● Discover the students preferences and re-
use that data to improve education &
technology.

education
Conclusions
- Natural language processing.
- Behavioural language processing.
● Compare writing vs behavioural language in
tests.
● Discover emotions and feelings about the
education and the technology use.
● Discover the students preferences and re-
use that data to improve education &
technology.

education
Conclusions
- Learning prediction.
- Learning analytics.
● Give trainers more accurate data about
students and their learning processes.
● Show students their own learning data to
improve self-direct learning.
● Discover the further learning needs of the
students based on their behaviour.

education
Conclusions
What is needed to
improve the current
Cuban education
towards a
f-university
approach?

education
Conclusions
What is needed to
improve the current
Cuban education
towards a
f-university
approach?
OPEN
EDUCATION

f-university & AI = changes
education
Conclusions
● ICT-supported learning processes.
● Open and collaborative education
methodologies.
● Open educational resources production and
re-use.
● Promotion of an Internet and cloud-based
behavior.
● Staff training.
● Technological infrastructure.

f-university & AI = changes
education
Conclusions
● ICT-supported learning processes.
● Open and collaborative education
methodologies.
● Open educational resources production and
re-use.
● Promotion of an Internet and cloud-based
behavior.
● Staff training.
● Technological infrastructure.
Improve the
pedagogical
model to
really
embrace
technology
Design
technology
to meet the
needs of
society
about
education

Future education and Artificial
Intelligence (AI)
Dr.C. Febe Angel Ciudad Ricardo, P.T.
University of Holguín “Oscar Lucero Moya”, November 19th
, 2018.

Education and Artificial intelligence

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